diff --git a/develop/_sources/guides/cli.md b/develop/_sources/guides/cli.md
index 134461c60..339c5405b 100644
--- a/develop/_sources/guides/cli.md
+++ b/develop/_sources/guides/cli.md
@@ -230,7 +230,7 @@ optional arguments:
--tracking.kf_node_indices TRACKING.KF_NODE_INDICES
For Kalman filter: Indices of nodes to track. (default: )
--tracking.kf_init_frame_count TRACKING.KF_INIT_FRAME_COUNT
- For Kalman filter: Number of frames to track with other tracker. 0 means no Kalman filters will be used. (default: 0)
+ For Kalman filter: Number of frames to track with other tracker. 0 means no Kalman filters will be used. (default: 0) Kalman filters require TRACKING.KF_NODE_INDICES, TRACKING.MAX_TRACKING and TRACKING.MAX_TRACKS or TRACKING.TARGET_INSTANCE_COUNT, TRACKING.TRACKER to be simple or simplemaxtracks, and TRACKING.SIMILARITY to not be normalized_instance.
```
#### Examples:
@@ -285,6 +285,12 @@ sleap-track --gpu 1 ...
sleap-track -m "models/my_model" --frames 1000-2000 "input_video.mp4"
```
+**9. Use Kalman tracker (not recommended since flow is preferred):**
+
+```none
+sleap-track -m "models/my_model" --tracking.similarity instance --tracking.tracker simplemaxtracks --tracking.max_tracking 1 --tracking.max_tracks 4 --tracking.kf_init_frame_count 10 --tracking.kf_node_indices 0,1 -o "output_predictions.slp" "input_video.mp4"
+```
+
## Dataset files
(sleap-convert)=
diff --git a/develop/api/sleap.nn.inference.html b/develop/api/sleap.nn.inference.html
index 5681a012d..302664f90 100644
--- a/develop/api/sleap.nn.inference.html
+++ b/develop/api/sleap.nn.inference.html
@@ -638,7 +638,7 @@ <h2> Contents </h2>
function which provides a simplified interface for creating <a href="#id3"><span class="problematic" id="id4">`</span></a>Predictor`s.</p>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpInferenceLayer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2695-L2961"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2697-L2963"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer" title="Permalink to this definition">#</a></dt>
<dd><p>Keras layer that predicts instances from images using a trained model.</p>
<p>This layer encapsulates all of the inference operations required for generating
predictions from a centered instance confidence map model. This includes
@@ -761,7 +761,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpInferenceLayer.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2896-L2961"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2898-L2963"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -795,13 +795,13 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpInferenceLayer.find_peaks">
-<span class="sig-name descname"><span class="pre">find_peaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cms</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">offsets</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2850-L2894"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer.find_peaks" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">find_peaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cms</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">offsets</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2852-L2896"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer.find_peaks" title="Permalink to this definition">#</a></dt>
<dd><p>Run peak finding on predicted confidence maps.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpInferenceLayer.forward_pass">
-<span class="sig-name descname"><span class="pre">forward_pass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2822-L2848"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer.forward_pass" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">forward_pass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2824-L2850"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceLayer.forward_pass" title="Permalink to this definition">#</a></dt>
<dd><p>Run preprocessing and model inference on a batch.</p>
</dd></dl>
@@ -809,7 +809,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpInferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2964-L3010"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2966-L3012"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>Bottom-up instance prediction model.</p>
<p>This model encapsulates the bottom-up approach where points are first detected by
local peak detection and then grouped into instances by connectivity scoring using
@@ -823,7 +823,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpInferenceModel.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2984-L3010"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceModel.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2986-L3012"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpInferenceModel.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -856,7 +856,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassInferenceLayer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpMultiClassInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3309-L3547"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpMultiClassInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3311-L3549"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer" title="Permalink to this definition">#</a></dt>
<dd><p>Keras layer that predicts instances from images using a trained model.</p>
<p>This layer encapsulates all of the inference operations required for generating
predictions from a centered instance confidence map model. This includes
@@ -962,7 +962,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassInferenceLayer.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3483-L3547"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3485-L3549"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -993,13 +993,13 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassInferenceLayer.find_peaks">
-<span class="sig-name descname"><span class="pre">find_peaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cms</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">offsets</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3451-L3481"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer.find_peaks" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">find_peaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cms</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">offsets</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3453-L3483"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer.find_peaks" title="Permalink to this definition">#</a></dt>
<dd><p>Run peak finding on predicted confidence maps.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassInferenceLayer.forward_pass">
-<span class="sig-name descname"><span class="pre">forward_pass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3425-L3449"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer.forward_pass" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">forward_pass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3427-L3451"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceLayer.forward_pass" title="Permalink to this definition">#</a></dt>
<dd><p>Run preprocessing and model inference on a batch.</p>
</dd></dl>
@@ -1007,7 +1007,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassInferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpMultiClassInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3550-L3592"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpMultiClassInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3552-L3594"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>Bottom-up multi-class instance prediction model.</p>
<p>This model encapsulates the bottom-up multi-class approach where points are first
detected by local peak finding and then grouped into instances by their identity
@@ -1021,7 +1021,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassInferenceModel.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3566-L3592"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceModel.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3568-L3594"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassInferenceModel.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1054,7 +1054,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassPredictor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpMultiClassPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.BottomUpMultiClassInferenceModel" title="sleap.nn.inference.BottomUpMultiClassInferenceModel"><span class="pre">BottomUpMultiClassInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.Track" title="sleap.instance.Track"><span class="pre">Track</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3596-L3818"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassPredictor" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpMultiClassPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.BottomUpMultiClassInferenceModel" title="sleap.nn.inference.BottomUpMultiClassInferenceModel"><span class="pre">BottomUpMultiClassInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.Track" title="sleap.instance.Track"><span class="pre">Track</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3598-L3820"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassPredictor" title="Permalink to this definition">#</a></dt>
<dd><p>Bottom-up multi-instance predictor.</p>
<p>This high-level class handles initialization, preprocessing and tracking using a
trained bottom-up multi-instance SLEAP model.</p>
@@ -1173,7 +1173,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpMultiClassPredictor.from_trained_models">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.BottomUpMultiClassPredictor" title="sleap.nn.inference.BottomUpMultiClassPredictor"><span class="pre">BottomUpMultiClassPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3654-L3705"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.BottomUpMultiClassPredictor" title="sleap.nn.inference.BottomUpMultiClassPredictor"><span class="pre">BottomUpMultiClassPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3656-L3707"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpMultiClassPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
<dd><p>Create predictor from a saved model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1212,7 +1212,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpPredictor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bottomup_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">bottomup_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.BottomUpInferenceModel" title="sleap.nn.inference.BottomUpInferenceModel"><span class="pre">BottomUpInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_edge_length_ratio</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_penalty_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">paf_line_points</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_line_scores</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3014-L3306"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpPredictor" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">BottomUpPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bottomup_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">bottomup_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.BottomUpInferenceModel" title="sleap.nn.inference.BottomUpInferenceModel"><span class="pre">BottomUpInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_edge_length_ratio</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_penalty_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">paf_line_points</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_line_scores</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3016-L3308"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpPredictor" title="Permalink to this definition">#</a></dt>
<dd><p>Bottom-up multi-instance predictor.</p>
<p>This high-level class handles initialization, preprocessing and tracking using a
trained bottom-up multi-instance SLEAP model.</p>
@@ -1396,7 +1396,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.BottomUpPredictor.from_trained_models">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_edge_length_ratio</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_penalty_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">paf_line_points</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_line_scores</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.BottomUpPredictor" title="sleap.nn.inference.BottomUpPredictor"><span class="pre">BottomUpPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3109-L3186"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_edge_length_ratio</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dist_penalty_weight</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">paf_line_points</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_line_scores</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.25</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.BottomUpPredictor" title="sleap.nn.inference.BottomUpPredictor"><span class="pre">BottomUpPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3111-L3188"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.BottomUpPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
<dd><p>Create predictor from a saved model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1449,7 +1449,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.CentroidCrop">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">CentroidCrop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1625-L1941"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.CentroidCrop" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">CentroidCrop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1627-L1943"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.CentroidCrop" title="Permalink to this definition">#</a></dt>
<dd><p>Inference layer for applying centroid crop-based models.</p>
<p>This layer encapsulates all of the inference operations requires for generating
predictions from a centroid confidence map model. This includes preprocessing,
@@ -1643,7 +1643,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.CentroidInferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">CentroidInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2169-L2209"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.CentroidInferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">CentroidInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2171-L2211"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.CentroidInferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>Centroid only instance prediction model.</p>
<p>This model encapsulates the first step in a top-down approach where instances are detected by
local peak detection of an anchor point and then cropped.</p>
@@ -1657,7 +1657,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.CentroidInferenceModel.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2185-L2209"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.CentroidInferenceModel.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2187-L2211"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.CentroidInferenceModel.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -1685,7 +1685,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.FindInstancePeaks">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">FindInstancePeaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1944-L2166"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.FindInstancePeaks" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">FindInstancePeaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1946-L2168"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.FindInstancePeaks" title="Permalink to this definition">#</a></dt>
<dd><p>Keras layer that predicts instance peaks from images using a trained model.</p>
<p>This layer encapsulates all of the inference operations required for generating
predictions from a centered instance confidence map model. This includes
@@ -1766,7 +1766,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.FindInstancePeaks.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2027-L2166"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.FindInstancePeaks.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2029-L2168"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.FindInstancePeaks.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict confidence maps and infer peak coordinates.</p>
<p>This layer can be chained with a <a class="reference internal" href="#sleap.nn.inference.CentroidCrop" title="sleap.nn.inference.CentroidCrop"><code class="xref py py-obj docutils literal notranslate"><span class="pre">CentroidCrop</span></code></a> layer to create a top-down
inference function from full images.</p>
@@ -1949,14 +1949,14 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.InferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">InferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L970-L1158"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.InferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">InferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L970-L1160"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.InferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>SLEAP inference model base class.</p>
<p>This class wraps the <code class="xref py py-obj docutils literal notranslate"><span class="pre">tf.keras.Model</span></code> class to provide SLEAP-specific inference
utilities such as handling different input data types, preprocessing and variable
output shapes.</p>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.InferenceModel.export_model">
-<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1081-L1158"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.InferenceModel.export_model" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1081-L1160"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.InferenceModel.export_model" title="Permalink to this definition">#</a></dt>
<dd><p>Save the frozen graph of a model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2066,7 +2066,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.MoveNetInferenceLayer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">MoveNetInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4593-L4638"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceLayer" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">MoveNetInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4595-L4640"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceLayer" title="Permalink to this definition">#</a></dt>
<dd><p>Inference layer for applying single instance models.</p>
<p>This layer encapsulates all of the inference operations requires for generating
predictions from a single instance confidence map model. This includes
@@ -2116,7 +2116,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.MoveNetInferenceLayer.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ex</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4628-L4638"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceLayer.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ex</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4630-L4640"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceLayer.call" title="Permalink to this definition">#</a></dt>
<dd><p>Call the model with preprocessed data.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2132,7 +2132,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.MoveNetInferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">MoveNetInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4641-L4665"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">MoveNetInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4643-L4667"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>MoveNet prediction model.</p>
<p>This model encapsulates the basic MoveNet approach. The images are passed to a model
which is trained to detect all body parts (17 joints in total).</p>
@@ -2149,7 +2149,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.MoveNetInferenceModel.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4664-L4665"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceModel.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4666-L4667"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetInferenceModel.call" title="Permalink to this definition">#</a></dt>
<dd><p>Calls the model on new inputs and returns the outputs as tensors.</p>
<p>In this case <a class="reference internal" href="#sleap.nn.inference.MoveNetInferenceModel.call" title="sleap.nn.inference.MoveNetInferenceModel.call"><code class="xref py py-obj docutils literal notranslate"><span class="pre">call()</span></code></a> just reapplies
all ops in the graph to the new inputs
@@ -2183,7 +2183,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.MoveNetPredictor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">MoveNetPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.MoveNetInferenceModel" title="sleap.nn.inference.MoveNetInferenceModel"><span class="pre">MoveNetInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lightning'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4669-L4810"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetPredictor" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">MoveNetPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.MoveNetInferenceModel" title="sleap.nn.inference.MoveNetInferenceModel"><span class="pre">MoveNetInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'lightning'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4671-L4812"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetPredictor" title="Permalink to this definition">#</a></dt>
<dd><p>MoveNet predictor.</p>
<p>This high-level class handles initialization, preprocessing and tracking using a
trained MoveNet model.
@@ -2250,7 +2250,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.MoveNetPredictor.from_trained_models">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.MoveNetPredictor" title="sleap.nn.inference.MoveNetPredictor"><span class="pre">MoveNetPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4721-L4743"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.MoveNetPredictor" title="sleap.nn.inference.MoveNetPredictor"><span class="pre">MoveNetPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4723-L4745"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.MoveNetPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
<dd><p>Create the predictor from a saved model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2416,7 +2416,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.SingleInstanceInferenceLayer">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">SingleInstanceInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1216-L1367"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceLayer" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">SingleInstanceInferenceLayer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1218-L1369"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceLayer" title="Permalink to this definition">#</a></dt>
<dd><p>Inference layer for applying single instance models.</p>
<p>This layer encapsulates all of the inference operations requires for generating
predictions from a single instance confidence map model. This includes
@@ -2505,7 +2505,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.SingleInstanceInferenceLayer.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1306-L1367"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceLayer.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1308-L1369"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceLayer.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instance confidence maps and find peaks.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2533,7 +2533,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.SingleInstanceInferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">SingleInstanceInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1370-L1402"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">SingleInstanceInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1372-L1404"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>Single instance prediction model.</p>
<p>This model encapsulates the basic single instance approach where it is assumed that
there is only one instance in the frame. The images are passed to a peak detector
@@ -2548,7 +2548,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.SingleInstanceInferenceModel.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1387-L1402"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceModel.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1389-L1404"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstanceInferenceModel.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2574,7 +2574,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.SingleInstancePredictor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">SingleInstancePredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">confmap_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.SingleInstanceInferenceModel" title="sleap.nn.inference.SingleInstanceInferenceModel"><span class="pre">SingleInstanceInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1406-L1622"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstancePredictor" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">SingleInstancePredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">confmap_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.SingleInstanceInferenceModel" title="sleap.nn.inference.SingleInstanceInferenceModel"><span class="pre">SingleInstanceInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1408-L1624"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstancePredictor" title="Permalink to this definition">#</a></dt>
<dd><p>Single instance predictor.</p>
<p>This high-level class handles initialization, preprocessing and tracking using a
trained single instance SLEAP model.</p>
@@ -2678,7 +2678,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.SingleInstancePredictor.export_model">
-<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1602-L1622"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstancePredictor.export_model" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1604-L1624"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstancePredictor.export_model" title="Permalink to this definition">#</a></dt>
<dd><p>Export a trained SLEAP model as a frozen graph. Initializes model,
creates a dummy tracing batch and passes it through the model. The
frozen graph is saved along with training meta info.</p>
@@ -2707,7 +2707,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.SingleInstancePredictor.from_trained_models">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.SingleInstancePredictor" title="sleap.nn.inference.SingleInstancePredictor"><span class="pre">SingleInstancePredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1466-L1519"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstancePredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.SingleInstancePredictor" title="sleap.nn.inference.SingleInstancePredictor"><span class="pre">SingleInstancePredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1468-L1521"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.SingleInstancePredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
<dd><p>Create the predictor from a saved model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2746,7 +2746,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownInferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2212-L2277"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownInferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2214-L2279"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownInferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>Top-down instance prediction model.</p>
<p>This model encapsulates the top-down approach where instances are first detected by
local peak detection of an anchor point and then cropped. These instance-centered
@@ -2771,7 +2771,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownInferenceModel.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2239-L2277"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownInferenceModel.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2241-L2279"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownInferenceModel.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -2805,7 +2805,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassFindPeaks">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownMultiClassFindPeaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3821-L4087"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassFindPeaks" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownMultiClassFindPeaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3823-L4089"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassFindPeaks" title="Permalink to this definition">#</a></dt>
<dd><p>Keras layer that predicts and classifies peaks from images using a trained model.</p>
<p>This layer encapsulates all of the inference operations required for generating
predictions from a centered instance confidence map and multi-class model. This
@@ -2913,7 +2913,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassFindPeaks.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3929-L4087"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassFindPeaks.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L3931-L4089"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassFindPeaks.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict confidence maps and infer peak coordinates.</p>
<p>This layer can be chained with a <a class="reference internal" href="#sleap.nn.inference.CentroidCrop" title="sleap.nn.inference.CentroidCrop"><code class="xref py py-obj docutils literal notranslate"><span class="pre">CentroidCrop</span></code></a> layer to create a top-down
inference function from full images.</p>
@@ -2974,7 +2974,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassInferenceModel">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownMultiClassInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4090-L4160"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassInferenceModel" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownMultiClassInferenceModel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4092-L4162"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassInferenceModel" title="Permalink to this definition">#</a></dt>
<dd><p>Top-down instance prediction model.</p>
<p>This model encapsulates the top-down approach where instances are first detected by
local peak detection of an anchor point and then cropped. These instance-centered
@@ -2999,7 +2999,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassInferenceModel.call">
-<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4117-L4145"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassInferenceModel.call" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">call</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">example</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4119-L4147"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassInferenceModel.call" title="Permalink to this definition">#</a></dt>
<dd><p>Predict instances for one batch of images.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3031,7 +3031,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassInferenceModel.export_model">
-<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4147-L4160"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassInferenceModel.export_model" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4149-L4162"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassInferenceModel.export_model" title="Permalink to this definition">#</a></dt>
<dd><p>Save the frozen graph of a model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3062,7 +3062,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassPredictor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownMultiClassPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">centroid_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.TopDownMultiClassInferenceModel" title="sleap.nn.inference.TopDownMultiClassInferenceModel"><span class="pre">TopDownMultiClassInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.Track" title="sleap.instance.Track"><span class="pre">Track</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4164-L4553"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownMultiClassPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">centroid_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.TopDownMultiClassInferenceModel" title="sleap.nn.inference.TopDownMultiClassInferenceModel"><span class="pre">TopDownMultiClassInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.Track" title="sleap.instance.Track"><span class="pre">Track</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4166-L4555"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor" title="Permalink to this definition">#</a></dt>
<dd><p>Top-down multi-instance predictor with classification.</p>
<p>This high-level class handles initialization, preprocessing and tracking using a
trained top-down multi-instance classification SLEAP model.</p>
@@ -3221,7 +3221,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassPredictor.export_model">
-<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4526-L4553"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor.export_model" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4528-L4555"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor.export_model" title="Permalink to this definition">#</a></dt>
<dd><p>Export a trained SLEAP model as a frozen graph. Initializes model,
creates a dummy tracing batch and passes it through the model. The
frozen graph is saved along with training meta info.</p>
@@ -3250,7 +3250,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassPredictor.from_trained_models">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.TopDownMultiClassPredictor" title="sleap.nn.inference.TopDownMultiClassPredictor"><span class="pre">TopDownMultiClassPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4263-L4351"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.TopDownMultiClassPredictor" title="sleap.nn.inference.TopDownMultiClassPredictor"><span class="pre">TopDownMultiClassPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4265-L4353"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
<dd><p>Create predictor from saved models.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3293,7 +3293,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownMultiClassPredictor.make_pipeline">
-<span class="sig-name descname"><span class="pre">make_pipeline</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_provider</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Provider</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="sleap.nn.data.pipelines.html#sleap.nn.data.pipelines.Pipeline" title="sleap.nn.data.pipelines.Pipeline"><span class="pre">Pipeline</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4371-L4405"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor.make_pipeline" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">make_pipeline</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_provider</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Provider</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="sleap.nn.data.pipelines.html#sleap.nn.data.pipelines.Pipeline" title="sleap.nn.data.pipelines.Pipeline"><span class="pre">Pipeline</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4373-L4407"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownMultiClassPredictor.make_pipeline" title="Permalink to this definition">#</a></dt>
<dd><p>Make a data loading pipeline.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3315,7 +3315,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownPredictor">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">centroid_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.TopDownInferenceModel" title="sleap.nn.inference.TopDownInferenceModel"><span class="pre">TopDownInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2281-L2692"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">TopDownPredictor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">centroid_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.config.training_job.html#sleap.nn.config.training_job.TrainingJobConfig" title="sleap.nn.config.training_job.TrainingJobConfig"><span class="pre">TrainingJobConfig</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.nn.model.html#sleap.nn.model.Model" title="sleap.nn.model.Model"><span class="pre">Model</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inference_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.inference.TopDownInferenceModel" title="sleap.nn.inference.TopDownInferenceModel"><span class="pre">TopDownInferenceModel</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">report_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2283-L2694"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor" title="Permalink to this definition">#</a></dt>
<dd><p>Top-down multi-instance predictor.</p>
<p>This high-level class handles initialization, preprocessing and tracking using a
trained top-down multi-instance SLEAP model.</p>
@@ -3476,7 +3476,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownPredictor.export_model">
-<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2665-L2692"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor.export_model" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2667-L2694"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor.export_model" title="Permalink to this definition">#</a></dt>
<dd><p>Export a trained SLEAP model as a frozen graph. Initializes model,
creates a dummy tracing batch and passes it through the model. The
frozen graph is saved along with training meta info.</p>
@@ -3505,7 +3505,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownPredictor.from_trained_models">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.TopDownPredictor" title="sleap.nn.inference.TopDownPredictor"><span class="pre">TopDownPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2392-L2488"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">from_trained_models</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">centroid_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">confmap_model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">integral_patch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.TopDownPredictor" title="sleap.nn.inference.TopDownPredictor"><span class="pre">TopDownPredictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2394-L2490"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor.from_trained_models" title="Permalink to this definition">#</a></dt>
<dd><p>Create predictor from saved models.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3552,7 +3552,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.inference.TopDownPredictor.make_pipeline">
-<span class="sig-name descname"><span class="pre">make_pipeline</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_provider</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Provider</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="sleap.nn.data.pipelines.html#sleap.nn.data.pipelines.Pipeline" title="sleap.nn.data.pipelines.Pipeline"><span class="pre">Pipeline</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2500-L2546"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor.make_pipeline" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">make_pipeline</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_provider</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Provider</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="sleap.nn.data.pipelines.html#sleap.nn.data.pipelines.Pipeline" title="sleap.nn.data.pipelines.Pipeline"><span class="pre">Pipeline</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L2502-L2548"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.TopDownPredictor.make_pipeline" title="Permalink to this definition">#</a></dt>
<dd><p>Make a data loading pipeline.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3628,13 +3628,13 @@ <h2> Contents </h2>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.inference.export_cli">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">export_cli</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">list</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4998-L5013"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.export_cli" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">export_cli</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">list</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L5000-L5015"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.export_cli" title="Permalink to this definition">#</a></dt>
<dd><p>CLI for sleap-export.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.inference.export_model">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'exported_model'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4955-L4995"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.export_model" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">export_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'exported_model'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">signatures</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'serving_default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_traces</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unrag_outputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4957-L4997"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.export_model" title="Permalink to this definition">#</a></dt>
<dd><p>High level export of a trained SLEAP model as a frozen graph.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3662,7 +3662,7 @@ <h2> Contents </h2>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.inference.find_head">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">find_head</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1191-L1213"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.find_head" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">find_head</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1193-L1215"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.find_head" title="Permalink to this definition">#</a></dt>
<dd><p>Return the index of a head in a model’s outputs.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3703,7 +3703,7 @@ <h2> Contents </h2>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.inference.get_model_output_stride">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">get_model_output_stride</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_ind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_ind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1161-L1188"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.get_model_output_stride" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">get_model_output_stride</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Model</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_ind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_ind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L1163-L1190"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.get_model_output_stride" title="Permalink to this definition">#</a></dt>
<dd><p>Return the stride (1/scale) of the model outputs relative to the input.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3729,7 +3729,7 @@ <h2> Contents </h2>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.inference.load_model">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">load_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'integral'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">disable_gpu_preallocation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">progress_reporting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.Predictor" title="sleap.nn.inference.Predictor"><span class="pre">Predictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4813-L4952"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.load_model" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">load_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">refinement</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'integral'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker_max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">disable_gpu_preallocation</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">progress_reporting</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'rich'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resize_input_layer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#sleap.nn.inference.Predictor" title="sleap.nn.inference.Predictor"><span class="pre">Predictor</span></a></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4815-L4954"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.load_model" title="Permalink to this definition">#</a></dt>
<dd><p>Load a trained SLEAP model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3788,7 +3788,7 @@ <h2> Contents </h2>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.inference.main">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">main</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">list</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L5503-L5719"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.main" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">main</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">args</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">list</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L5505-L5721"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.main" title="Permalink to this definition">#</a></dt>
<dd><p>Entrypoint for <code class="xref py py-obj docutils literal notranslate"><span class="pre">sleap-track</span></code> CLI for running inference.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -3799,7 +3799,7 @@ <h2> Contents </h2>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.inference.make_model_movenet">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">make_model_movenet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Model</span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4556-L4590"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.make_model_movenet" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.inference.</span></span><span class="sig-name descname"><span class="pre">make_model_movenet</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Model</span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/inference.py#L4558-L4592"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.inference.make_model_movenet" title="Permalink to this definition">#</a></dt>
<dd><p>Load a MoveNet model by name.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
diff --git a/develop/api/sleap.nn.tracking.html b/develop/api/sleap.nn.tracking.html
index 8f63b9c08..56c394bcd 100644
--- a/develop/api/sleap.nn.tracking.html
+++ b/develop/api/sleap.nn.tracking.html
@@ -549,7 +549,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.tracking.FlowMaxTracker">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">FlowMaxTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_similarity></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">greedy_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1172-L1179"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.FlowMaxTracker" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">FlowMaxTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_similarity></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">greedy_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1205-L1212"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.FlowMaxTracker" title="Permalink to this definition">#</a></dt>
<dd><p>Pre-configured tracker to use optical flow shifted candidates with max tracks.</p>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.tracking.FlowMaxTracker.matching_function">
@@ -600,13 +600,13 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.tracking.FlowTracker">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">FlowTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_similarity></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">greedy_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1161-L1166"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.FlowTracker" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">FlowTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_similarity></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">greedy_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1194-L1199"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.FlowTracker" title="Permalink to this definition">#</a></dt>
<dd><p>A Tracker pre-configured to use optical flow shifted candidates.</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.tracking.KalmanTracker">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">KalmanTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">init_tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.tracking.Tracker" title="sleap.nn.tracking.Tracker"><span class="pre">Tracker</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">KalmanInitSet</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kalman_tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">BareKalmanTracker</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cull_function</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_frame_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">re_init_cooldown</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">re_init_after</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_done</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_tracked</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_t</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_init_t</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1279-L1472"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.KalmanTracker" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">KalmanTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">init_tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.tracking.Tracker" title="sleap.nn.tracking.Tracker"><span class="pre">Tracker</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_set</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">KalmanInitSet</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kalman_tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">BareKalmanTracker</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cull_function</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_frame_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">re_init_cooldown</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">re_init_after</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_done</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_tracked</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_t</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_init_t</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1312-L1510"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.KalmanTracker" title="Permalink to this definition">#</a></dt>
<dd><p>Class for Kalman filter-based tracking pipeline.</p>
<p>Kalman filters need to be initialized with a certain number of already
tracked instances.</p>
@@ -647,7 +647,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.tracking.KalmanTracker.make_tracker">
-<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">make_tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">init_tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.tracking.Tracker" title="sleap.nn.tracking.Tracker"><span class="pre">Tracker</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">node_indices</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">instance_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">instance_iou_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_frame_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1331-L1382"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.KalmanTracker.make_tracker" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">make_tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">init_tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#sleap.nn.tracking.Tracker" title="sleap.nn.tracking.Tracker"><span class="pre">Tracker</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">node_indices</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">instance_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">instance_iou_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">init_frame_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1364-L1419"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.KalmanTracker.make_tracker" title="Permalink to this definition">#</a></dt>
<dd><p>Creates KalmanTracker object.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
@@ -672,7 +672,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.tracking.KalmanTracker.track">
-<span class="sig-name descname"><span class="pre">track</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">untracked_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">InstanceType</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">img</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">InstanceType</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1384-L1462"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.KalmanTracker.track" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">track</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">untracked_instances</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">InstanceType</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">img</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">t</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">InstanceType</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1421-L1500"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.KalmanTracker.track" title="Permalink to this definition">#</a></dt>
<dd><p>Tracks individual frame, using Kalman filters if possible.</p>
</dd></dl>
@@ -686,7 +686,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.tracking.SimpleMaxTracker">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">SimpleMaxTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_iou></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">hungarian_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">int</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1192-L1199"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.SimpleMaxTracker" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">SimpleMaxTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_iou></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">hungarian_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">int</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1225-L1232"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.SimpleMaxTracker" title="Permalink to this definition">#</a></dt>
<dd><p>Pre-configured tracker to use simple, non-image-based candidates with max tracks.</p>
</dd></dl>
@@ -698,13 +698,13 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.tracking.SimpleTracker">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">SimpleTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_iou></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">hungarian_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1183-L1188"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.SimpleTracker" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">SimpleTracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_iou></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">hungarian_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1216-L1221"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.SimpleTracker" title="Permalink to this definition">#</a></dt>
<dd><p>A Tracker pre-configured to use simple, non-image-based candidates.</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.tracking.TrackCleaner">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">TrackCleaner</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instance_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1476-L1501"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.TrackCleaner" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">TrackCleaner</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">instance_count</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">iou_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1514-L1539"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.TrackCleaner" title="Permalink to this definition">#</a></dt>
<dd><p>Class for merging breaks in the predicted tracks.</p>
<p>Method:
1. You specify how many instances there should be in each frame.
@@ -743,7 +743,7 @@ <h2> Contents </h2>
<dl class="py class">
<dt class="sig sig-object py" id="sleap.nn.tracking.Tracker">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">Tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_similarity></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">greedy_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L542-L1157"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.Tracker" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">Tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">max_tracks:</span> <span class="pre">~typing.Optional[int]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_window:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">similarity_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">instance_similarity></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">matching_function:</span> <span class="pre">~typing.Callable</span> <span class="pre">=</span> <span class="pre"><function</span> <span class="pre">greedy_matching></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">candidate_maker:</span> <span class="pre">object</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_tracking:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cleaner:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">target_instance_count:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pre_cull_function:</span> <span class="pre">~typing.Optional[~typing.Callable]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">post_connect_single_breaks:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">robust_best_instance:</span> <span class="pre">float</span> <span class="pre">=</span> <span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_new_track_points:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue:</span> <span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstances]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">track_matching_queue_dict:</span> <span class="pre">~typing.Dict[~sleap.instance.Track</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.Deque[~sleap.nn.tracking.MatchedFrameInstance]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spawned_tracks:</span> <span class="pre">~typing.List[~sleap.instance.Track]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_tracked_instances:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracked_instances:</span> <span class="pre">~typing.Dict[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">~typing.List[~sleap.nn.tracker.components.InstanceType]]</span> <span class="pre">=</span> <span class="pre">_Nothing.NOTHING</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">last_matches:</span> <span class="pre">~typing.Optional[~sleap.nn.tracker.components.FrameMatches]</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L542-L1190"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.Tracker" title="Permalink to this definition">#</a></dt>
<dd><p>Instance pose tracker.</p>
<p>Use by instantiated with the desired parameters and then calling the
<a class="reference internal" href="#sleap.nn.tracking.Tracker.track" title="sleap.nn.tracking.Tracker.track"><code class="xref py py-obj docutils literal notranslate"><span class="pre">track</span></code></a> method for each frame.</p>
@@ -847,7 +847,7 @@ <h2> Contents </h2>
<dl class="py method">
<dt class="sig sig-object py" id="sleap.nn.tracking.Tracker.final_pass">
-<span class="sig-name descname"><span class="pre">final_pass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frames</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.LabeledFrame" title="sleap.instance.LabeledFrame"><span class="pre">LabeledFrame</span></a><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L816-L828"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.Tracker.final_pass" title="Permalink to this definition">#</a></dt>
+<span class="sig-name descname"><span class="pre">final_pass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frames</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.LabeledFrame" title="sleap.instance.LabeledFrame"><span class="pre">LabeledFrame</span></a><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L816-L835"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.Tracker.final_pass" title="Permalink to this definition">#</a></dt>
<dd><p>Called after tracking has run on all frames to do any post-processing.</p>
</dd></dl>
@@ -880,7 +880,7 @@ <h2> Contents </h2>
<dl class="py function">
<dt class="sig sig-object py" id="sleap.nn.tracking.run_tracker">
-<span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">run_tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frames</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.LabeledFrame" title="sleap.instance.LabeledFrame"><span class="pre">LabeledFrame</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#sleap.nn.tracking.BaseTracker" title="sleap.nn.tracking.BaseTracker"><span class="pre">BaseTracker</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.LabeledFrame" title="sleap.instance.LabeledFrame"><span class="pre">LabeledFrame</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1504-L1542"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.run_tracker" title="Permalink to this definition">#</a></dt>
+<span class="sig-prename descclassname"><span class="pre">sleap.nn.tracking.</span></span><span class="sig-name descname"><span class="pre">run_tracker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">frames</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.LabeledFrame" title="sleap.instance.LabeledFrame"><span class="pre">LabeledFrame</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tracker</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#sleap.nn.tracking.BaseTracker" title="sleap.nn.tracking.BaseTracker"><span class="pre">BaseTracker</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="sleap.instance.html#sleap.instance.LabeledFrame" title="sleap.instance.LabeledFrame"><span class="pre">LabeledFrame</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference external" href="https://github.com/talmolab/sleap/blob/v1.4.1/sleap/nn/tracking.py#L1542-L1580"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sleap.nn.tracking.run_tracker" title="Permalink to this definition">#</a></dt>
<dd><p>Run a tracker on a set of labeled frames.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
diff --git a/develop/guides/cli.html b/develop/guides/cli.html
index bb886e10a..88e405088 100644
--- a/develop/guides/cli.html
+++ b/develop/guides/cli.html
@@ -572,7 +572,7 @@ <h2>Inference and Tracking<a class="headerlink" href="#inference-and-tracking" t
--tracking.kf_node_indices TRACKING.KF_NODE_INDICES
For Kalman filter: Indices of nodes to track. (default: )
--tracking.kf_init_frame_count TRACKING.KF_INIT_FRAME_COUNT
- For Kalman filter: Number of frames to track with other tracker. 0 means no Kalman filters will be used. (default: 0)
+ For Kalman filter: Number of frames to track with other tracker. 0 means no Kalman filters will be used. (default: 0) Kalman filters require TRACKING.KF_NODE_INDICES, TRACKING.MAX_TRACKING and TRACKING.MAX_TRACKS or TRACKING.TARGET_INSTANCE_COUNT, TRACKING.TRACKER to be simple or simplemaxtracks, and TRACKING.SIMILARITY to not be normalized_instance.
</pre></div>
</div>
<section id="examples">
@@ -610,6 +610,10 @@ <h4>Examples:<a class="headerlink" href="#examples" title="Permalink to this hea
<div class="highlight-none notranslate"><div class="highlight"><pre><span></span>sleap-track -m "models/my_model" --frames 1000-2000 "input_video.mp4"
</pre></div>
</div>
+<p><strong>9. Use Kalman tracker (not recommended since flow is preferred):</strong></p>
+<div class="highlight-none notranslate"><div class="highlight"><pre><span></span>sleap-track -m "models/my_model" --tracking.similarity instance --tracking.tracker simplemaxtracks --tracking.max_tracking 1 --tracking.max_tracks 4 --tracking.kf_init_frame_count 10 --tracking.kf_node_indices 0,1 -o "output_predictions.slp" "input_video.mp4"
+</pre></div>
+</div>
</section>
</section>
</section>
diff --git a/develop/searchindex.js b/develop/searchindex.js
index 7820c5cdc..d79c29dfc 100644
--- a/develop/searchindex.js
+++ b/develop/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["CODE_OF_CONDUCT", "CONTRIBUTING", "api", "api/sleap.info.align", "api/sleap.info.feature_suggestions", "api/sleap.info.labels", "api/sleap.info.metrics", "api/sleap.info.summary", "api/sleap.info.trackcleaner", "api/sleap.info.write_tracking_h5", "api/sleap.instance", "api/sleap.io.convert", "api/sleap.io.dataset", "api/sleap.io.format.adaptor", "api/sleap.io.format.alphatracker", "api/sleap.io.format.coco", "api/sleap.io.format.csv", "api/sleap.io.format.deeplabcut", "api/sleap.io.format.deepposekit", "api/sleap.io.format.dispatch", "api/sleap.io.format.filehandle", "api/sleap.io.format.genericjson", "api/sleap.io.format.hdf5", "api/sleap.io.format.labels_json", "api/sleap.io.format.leap_matlab", "api/sleap.io.format.main", "api/sleap.io.format.ndx_pose", "api/sleap.io.format.nix", "api/sleap.io.format.sleap_analysis", "api/sleap.io.format.text", "api/sleap.io.legacy", "api/sleap.io.pathutils", "api/sleap.io.video", "api/sleap.io.videowriter", 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"command-line-interfaces"]], "GUI": [[89, "gui"], [92, "gui"]], "sleap-label": [[89, "sleap-label"]], "Training": [[89, "training"]], "sleap-train": [[89, "sleap-train"]], "sleap-export": [[89, "sleap-export"]], "Inference and Tracking": [[89, "inference-and-tracking"]], "sleap-track": [[89, "sleap-track"]], "Examples:": [[89, "examples"]], "Dataset files": [[89, "dataset-files"]], "sleap-convert": [[89, "sleap-convert"]], "sleap-inspect": [[89, "sleap-inspect"]], "Rendering": [[89, "rendering"]], "sleap-render": [[89, "sleap-render"]], "Debugging": [[89, "debugging"]], "sleap-diagnostic": [[89, "sleap-diagnostic"]], "Run training and inference on Colab": [[90, "run-training-and-inference-on-colab"]], "About Colab": [[90, "about-colab"]], "Moving Data to/from Colab": [[90, "moving-data-to-from-colab"]], "Creating a custom training profile": [[91, "creating-a-custom-training-profile"]], "Menus": [[92, "menus"]], "File": [[92, "file"]], "Go": [[92, "go"]], "View": [[92, "view"]], "Labels": [[92, "labels"]], "Predict": [[92, "predict"]], "Help": [[92, "help"], [100, "help"]], "Application GUI": [[92, "application-gui"]], "Mouse": [[92, "mouse"]], "Navigation Keys": [[92, "navigation-keys"]], "Selection Keys": [[92, "selection-keys"]], "Seekbar": [[92, "seekbar"]], "Labeling Suggestions": [[92, "labeling-suggestions"]], "Guides": [[93, "guides"]], "General": [[93, "general"]], "Getting better results": [[93, "getting-better-results"]], "Running remotely": [[93, "running-remotely"]], "SLEAP with Bonsai": [[93, "sleap-with-bonsai"]], "Importing predictions for labeling": [[94, "importing-predictions-for-labeling"]], "Tracking and proofreading": [[95, "tracking-and-proofreading"]], "Tracking methods": [[95, "tracking-methods"]], "More training data?": [[95, "more-training-data"]], "The \u201ctrack cleaning\u201d script": [[95, "the-track-cleaning-script"]], "Color palettes": [[95, "color-palettes"]], "Proofreading": [[95, "id1"]], "Orientation": [[95, "orientation"]], "Running SLEAP remotely": [[96, "running-sleap-remotely"]], "Remote training": [[96, "remote-training"]], "Remote inference": [[96, "remote-inference"]], "Skeleton design": [[97, "skeleton-design"]], "Tips": [[97, "tips"]], "Training with GUI": [[98, "training-with-gui"]], "Troubleshooting workflows": [[99, "troubleshooting-workflows"]], "Installation": [[100, "installation"], [102, "installation"]], "I can\u2019t get SLEAP to install!": [[100, "i-cant-get-sleap-to-install"]], "Can I install it on a computer without a GPU?": [[100, "can-i-install-it-on-a-computer-without-a-gpu"]], "What if I already have CUDA set up on my system?": [[100, "what-if-i-already-have-cuda-set-up-on-my-system"]], "Usage": [[100, "usage"]], "How do I use SLEAP?": [[100, "how-do-i-use-sleap"]], "Does my data need to be in a particular format?": [[100, "does-my-data-need-to-be-in-a-particular-format"]], "I get strange results where the poses appear to be correct but shifted relative to the image.": [[100, "i-get-strange-results-where-the-poses-appear-to-be-correct-but-shifted-relative-to-the-image"]], "How do I get predictions out?": [[100, "how-do-i-get-predictions-out"]], "What do I do with the output of SLEAP?": [[100, "what-do-i-do-with-the-output-of-sleap"]], "Getting more help": [[100, "getting-more-help"]], "I\u2019ve found a bug or have another problem!": [[100, "ive-found-a-bug-or-have-another-problem"]], "Can I just talk to someone?": [[100, "can-i-just-talk-to-someone"]], "Improving SLEAP": [[100, "improving-sleap"]], "How can I help improve SLEAP?": [[100, "how-can-i-help-improve-sleap"]], "What is usage data?": [[100, "what-is-usage-data"]], "Social LEAP Estimates Animal Poses (SLEAP)": [[101, "social-leap-estimates-animal-poses-sleap"]], "Features": [[101, "features"]], "Get some SLEAP": [[101, "get-some-sleap"]], "Quick install": [[101, "quick-install"]], "Learn to SLEAP": [[101, "learn-to-sleap"]], "References": [[101, "references"]], "Contact": [[101, "contact"]], "Contributors": [[101, "contributors"]], "License": [[101, "license"]], "SLEAP Documentation": [[101, "sleap-documentation"]], "Contents": [[102, "contents"]], "Package Manager": [[102, "package-manager"]], "Miniforge (recommended)": [[102, "miniforge-recommended"]], "Miniconda": [[102, "miniconda"]], "Installation methods": [[102, "installation-methods"]], "Testing that things are working": [[102, "testing-that-things-are-working"]], "GUI support": [[102, "gui-support"]], "Importing": [[102, "importing"]], "GPU support": [[102, "gpu-support"]], "Upgrading and uninstalling": [[102, "upgrading-and-uninstalling"]], "Getting help": [[102, "getting-help"]], "Analysis examples": [[103, "analysis-examples"], [112, "id4"]], "Example analysis data": [[103, "example-analysis-data"]], "Loading the data": [[103, "loading-the-data"]], "Fill missing values": [[103, "fill-missing-values"]], "Visualize thorax movement across video": [[103, "visualize-thorax-movement-across-video"]], "More advanced visualizations": [[103, "more-advanced-visualizations"]], "Visualizing thorax x-y dynamics and velocity for fly 0": [[103, "visualizing-thorax-x-y-dynamics-and-velocity-for-fly-0"]], "Visualize thorax colored by magnitude of fly speed": [[103, "visualize-thorax-colored-by-magnitude-of-fly-speed"]], "Find covariance in thorax velocities between fly-0 and fly-1": [[103, "find-covariance-in-thorax-velocities-between-fly-0-and-fly-1"]], "Clustering": [[103, "clustering"]], "Data structures": [[104, "data-structures"], [112, "id5"]], "1. Setup SLEAP and data": [[104, "setup-sleap-and-data"]], "2. Data structures and inference": [[104, "data-structures-and-inference"]], "Interactive and realtime inference": [[105, "interactive-and-realtime-inference"], [112, "id8"]], "1. Setup SLEAP": [[105, "setup-sleap"], [106, "setup-sleap"], [108, "setup-sleap"]], "2. Setup data": [[105, "setup-data"], [108, "setup-data"]], "3. Interactive inference": [[105, "interactive-inference"]], "4. Realtime performance": [[105, "realtime-performance"]], "Interactive and resumable training": [[106, "interactive-and-resumable-training"], [112, "id7"]], "2. Setup training data": [[106, "setup-training-data"]], "3. Setup training job": [[106, "setup-training-job"]], "4. Training": [[106, "training"]], "5. Continuing training": [[106, "continuing-training"]], "Model evaluation": [[107, "model-evaluation"], [112, "id9"]], "Post-inference tracking": [[108, "post-inference-tracking"], [112, "id6"]], "Install": [[108, "install"]], "Test": [[108, "test"]], "3. Track": [[108, "track"]], "4. Inspect and save": [[108, "inspect-and-save"]], "Training and inference on an example dataset": [[109, "training-and-inference-on-an-example-dataset"], [112, "id2"]], "Install SLEAP": [[109, "install-sleap"], [110, "install-sleap"]], "Download sample training data into Colab": [[109, "download-sample-training-data-into-colab"]], "Train models": [[109, "train-models"]], "Inference": [[109, "inference"], [117, "inference"]], "Training and inference on your own data using Google Drive": [[110, "training-and-inference-on-your-own-data-using-google-drive"], [112, "id3"]], "Import training data into Colab with Google Drive": [[110, "import-training-data-into-colab-with-google-drive"]], "Create and export the training job package": [[110, "create-and-export-the-training-job-package"]], "Upload training job package to Google Drive": [[110, "upload-training-job-package-to-google-drive"]], "Mount your Google Drive": [[110, "mount-your-google-drive"]], "Train a model": [[110, "train-a-model"]], "Note on training profiles": [[110, "note-on-training-profiles"]], "Note on training process": [[110, "note-on-training-process"]], "Run inference to predict instances": [[110, "run-inference-to-predict-instances"]], "Predicting instances in suggested frames": [[110, "predicting-instances-in-suggested-frames"]], "Predicting and tracking instances in uploaded video": [[110, "predicting-and-tracking-instances-in-uploaded-video"]], "Inference with top-down models": [[110, "inference-with-top-down-models"]], "Notebooks": [[112, "notebooks"]], "Basic usage": [[112, "basic-usage"]], "Advanced SLEAPing": [[112, "advanced-sleaping"]], "Overview": [[113, "overview"]], "Export Data For Analysis": [[114, "export-data-for-analysis"]], "MATLAB": [[114, "matlab"]], "Python": [[114, "python"]], "Prediction-assisted labeling": [[115, "prediction-assisted-labeling"]], "Reviewing and fixing predictions": [[115, "reviewing-and-fixing-predictions"]], "Initial Labeling": [[116, "initial-labeling"]], "Selecting frames to label": [[116, "selecting-frames-to-label"]], "Labeling the first frame": [[116, "labeling-the-first-frame"]], "Saving": [[116, "saving"]], "Labeling more frames": [[116, "labeling-more-frames"]], "Training and Inference": [[117, "training-and-inference"]], "Training Options": [[117, "training-options"]], "Start Training": [[117, "start-training"]], "Creating a project": [[118, "creating-a-project"]], "Starting SLEAP": [[118, "starting-sleap"]], "Opening a video": [[118, "opening-a-video"]], "Creating a Skeleton": [[118, "creating-a-skeleton"]], "Tracking instances across frames": [[119, "tracking-instances-across-frames"]], "Track proofreading": [[119, "track-proofreading"]], "Tutorial": [[120, "tutorial"]]}, "indexentries": {"align_instance_points() (in module sleap.info.align)": [[3, "sleap.info.align.align_instance_points"]], "align_instances() (in module sleap.info.align)": [[3, "sleap.info.align.align_instances"]], "align_instances_on_most_stable() (in module 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"sleap.skeleton": [[84, "module-sleap.skeleton"]], "sleap.util": [[85, "module-sleap.util"]], "Datasets": [[86, "datasets"]], "fly32": [[86, "fly32"]], "flies13": [[86, "flies13"]], "mice_of": [[86, "mice-of"]], "mice_hc": [[86, "mice-hc"]], "bees": [[86, "bees"]], "gerbils": [[86, "gerbils"]], "Using Bonsai with SLEAP": [[87, "using-bonsai-with-sleap"]], "Exporting a SLEAP trained model": [[87, "exporting-a-sleap-trained-model"]], "Installing Bonsai and necessary packages": [[87, "installing-bonsai-and-necessary-packages"]], "Using Bonsai SLEAP modules": [[87, "using-bonsai-sleap-modules"]], "Top-down model": [[87, "top-down-model"]], "Top-Down-ID model": [[87, "top-down-id-model"]], "Single instance model": [[87, "single-instance-model"]], "Connecting the modules": [[87, "connecting-the-modules"]], "Configuring models": [[88, "configuring-models"]], "Model type": [[88, "model-type"]], "Hyperparameters": [[88, "hyperparameters"]], "Command line interfaces": [[89, "command-line-interfaces"]], "GUI": [[89, "gui"], [92, "gui"]], "sleap-label": [[89, "sleap-label"]], "Training": [[89, "training"]], "sleap-train": [[89, "sleap-train"]], "sleap-export": [[89, "sleap-export"]], "Inference and Tracking": [[89, "inference-and-tracking"]], "sleap-track": [[89, "sleap-track"]], "Examples:": [[89, "examples"]], "Dataset files": [[89, "dataset-files"]], "sleap-convert": [[89, "sleap-convert"]], "sleap-inspect": [[89, "sleap-inspect"]], "Rendering": [[89, "rendering"]], "sleap-render": [[89, "sleap-render"]], "Debugging": [[89, "debugging"]], "sleap-diagnostic": [[89, "sleap-diagnostic"]], "Run training and inference on Colab": [[90, "run-training-and-inference-on-colab"]], "About Colab": [[90, "about-colab"]], "Moving Data to/from Colab": [[90, "moving-data-to-from-colab"]], "Creating a custom training profile": [[91, "creating-a-custom-training-profile"]], "Menus": [[92, "menus"]], "File": [[92, "file"]], "Go": [[92, "go"]], "View": [[92, "view"]], "Labels": [[92, "labels"]], "Predict": [[92, "predict"]], "Help": [[92, "help"], [100, "help"]], "Application GUI": [[92, "application-gui"]], "Mouse": [[92, "mouse"]], "Navigation Keys": [[92, "navigation-keys"]], "Selection Keys": [[92, "selection-keys"]], "Seekbar": [[92, "seekbar"]], "Labeling Suggestions": [[92, "labeling-suggestions"]], "Guides": [[93, "guides"]], "General": [[93, "general"]], "Getting better results": [[93, "getting-better-results"]], "Running remotely": [[93, "running-remotely"]], "SLEAP with Bonsai": [[93, "sleap-with-bonsai"]], "Importing predictions for labeling": [[94, "importing-predictions-for-labeling"]], "Tracking and proofreading": [[95, "tracking-and-proofreading"]], "Tracking methods": [[95, "tracking-methods"]], "More training data?": [[95, "more-training-data"]], "The \u201ctrack cleaning\u201d script": [[95, "the-track-cleaning-script"]], "Color palettes": [[95, "color-palettes"]], "Proofreading": [[95, "id1"]], "Orientation": [[95, "orientation"]], "Running SLEAP remotely": [[96, "running-sleap-remotely"]], "Remote training": [[96, "remote-training"]], "Remote inference": [[96, "remote-inference"]], "Skeleton design": [[97, "skeleton-design"]], "Tips": [[97, "tips"]], "Training with GUI": [[98, "training-with-gui"]], "Troubleshooting workflows": [[99, "troubleshooting-workflows"]], "Installation": [[100, "installation"], [102, "installation"]], "I can\u2019t get SLEAP to install!": [[100, "i-cant-get-sleap-to-install"]], "Can I install it on a computer without a GPU?": [[100, "can-i-install-it-on-a-computer-without-a-gpu"]], "What if I already have CUDA set up on my system?": [[100, "what-if-i-already-have-cuda-set-up-on-my-system"]], "Usage": [[100, "usage"]], "How do I use SLEAP?": [[100, "how-do-i-use-sleap"]], "Does my data need to be in a particular format?": [[100, "does-my-data-need-to-be-in-a-particular-format"]], "I get strange results where the poses appear to be correct but shifted relative to the image.": [[100, "i-get-strange-results-where-the-poses-appear-to-be-correct-but-shifted-relative-to-the-image"]], "How do I get predictions out?": [[100, "how-do-i-get-predictions-out"]], "What do I do with the output of SLEAP?": [[100, "what-do-i-do-with-the-output-of-sleap"]], "Getting more help": [[100, "getting-more-help"]], "I\u2019ve found a bug or have another problem!": [[100, "ive-found-a-bug-or-have-another-problem"]], "Can I just talk to someone?": [[100, "can-i-just-talk-to-someone"]], "Improving SLEAP": [[100, "improving-sleap"]], "How can I help improve SLEAP?": [[100, "how-can-i-help-improve-sleap"]], "What is usage data?": [[100, "what-is-usage-data"]], "Social LEAP Estimates Animal Poses (SLEAP)": [[101, "social-leap-estimates-animal-poses-sleap"]], "Features": [[101, "features"]], "Get some SLEAP": [[101, "get-some-sleap"]], "Quick install": [[101, "quick-install"]], "Learn to SLEAP": [[101, "learn-to-sleap"]], "References": [[101, "references"]], "Contact": [[101, "contact"]], "Contributors": [[101, "contributors"]], "License": [[101, "license"]], "SLEAP Documentation": [[101, "sleap-documentation"]], "Contents": [[102, "contents"]], "Package Manager": [[102, "package-manager"]], "Miniforge (recommended)": [[102, "miniforge-recommended"]], "Miniconda": [[102, "miniconda"]], "Installation methods": [[102, "installation-methods"]], "Testing that things are working": [[102, "testing-that-things-are-working"]], "GUI support": [[102, "gui-support"]], "Importing": [[102, "importing"]], "GPU support": [[102, "gpu-support"]], "Upgrading and uninstalling": [[102, "upgrading-and-uninstalling"]], "Getting help": [[102, "getting-help"]], "Analysis examples": [[103, "analysis-examples"], [112, "id4"]], "Example analysis data": [[103, "example-analysis-data"]], "Loading the data": [[103, "loading-the-data"]], "Fill missing values": [[103, "fill-missing-values"]], "Visualize thorax movement across video": [[103, "visualize-thorax-movement-across-video"]], "More advanced visualizations": [[103, "more-advanced-visualizations"]], "Visualizing thorax x-y dynamics and velocity for fly 0": [[103, "visualizing-thorax-x-y-dynamics-and-velocity-for-fly-0"]], "Visualize thorax colored by magnitude of fly speed": [[103, "visualize-thorax-colored-by-magnitude-of-fly-speed"]], "Find covariance in thorax velocities between fly-0 and fly-1": [[103, "find-covariance-in-thorax-velocities-between-fly-0-and-fly-1"]], "Clustering": [[103, "clustering"]], "Data structures": [[104, "data-structures"], [112, "id5"]], "1. Setup SLEAP and data": [[104, "setup-sleap-and-data"]], "2. Data structures and inference": [[104, "data-structures-and-inference"]], "Interactive and realtime inference": [[105, "interactive-and-realtime-inference"], [112, "id8"]], "1. Setup SLEAP": [[105, "setup-sleap"], [106, "setup-sleap"], [108, "setup-sleap"]], "2. Setup data": [[105, "setup-data"], [108, "setup-data"]], "3. Interactive inference": [[105, "interactive-inference"]], "4. Realtime performance": [[105, "realtime-performance"]], "Interactive and resumable training": [[106, "interactive-and-resumable-training"], [112, "id7"]], "2. Setup training data": [[106, "setup-training-data"]], "3. Setup training job": [[106, "setup-training-job"]], "4. Training": [[106, "training"]], "5. Continuing training": [[106, "continuing-training"]], "Model evaluation": [[107, "model-evaluation"], [112, "id9"]], "Post-inference tracking": [[108, "post-inference-tracking"], [112, "id6"]], "Install": [[108, "install"]], "Test": [[108, "test"]], "3. Track": [[108, "track"]], "4. Inspect and save": [[108, "inspect-and-save"]], "Training and inference on an example dataset": [[109, "training-and-inference-on-an-example-dataset"], [112, "id2"]], "Install SLEAP": [[109, "install-sleap"], [110, "install-sleap"]], "Download sample training data into Colab": [[109, "download-sample-training-data-into-colab"]], "Train models": [[109, "train-models"]], "Inference": [[109, "inference"], [117, "inference"]], "Training and inference on your own data using Google Drive": [[110, "training-and-inference-on-your-own-data-using-google-drive"], [112, "id3"]], "Import training data into Colab with Google Drive": [[110, "import-training-data-into-colab-with-google-drive"]], "Create and export the training job package": [[110, "create-and-export-the-training-job-package"]], "Upload training job package to Google Drive": [[110, "upload-training-job-package-to-google-drive"]], "Mount your Google Drive": [[110, "mount-your-google-drive"]], "Train a model": [[110, "train-a-model"]], "Note on training profiles": [[110, "note-on-training-profiles"]], "Note on training process": [[110, "note-on-training-process"]], "Run inference to predict instances": [[110, "run-inference-to-predict-instances"]], "Predicting instances in suggested frames": [[110, "predicting-instances-in-suggested-frames"]], "Predicting and tracking instances in uploaded video": [[110, "predicting-and-tracking-instances-in-uploaded-video"]], "Inference with top-down models": [[110, "inference-with-top-down-models"]], "Notebooks": [[112, "notebooks"]], "Basic usage": [[112, "basic-usage"]], "Advanced SLEAPing": [[112, "advanced-sleaping"]], "Overview": [[113, "overview"]], "Export Data For Analysis": [[114, "export-data-for-analysis"]], "MATLAB": [[114, "matlab"]], "Python": [[114, "python"]], "Prediction-assisted labeling": [[115, "prediction-assisted-labeling"]], "Reviewing and fixing predictions": [[115, "reviewing-and-fixing-predictions"]], "Initial Labeling": [[116, "initial-labeling"]], 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\ No newline at end of file