deploy: d3ad226

develop/_sources/api.rst

@@ -65,14 +65,23 @@ Developer API
    sleap.nn.training
    sleap.nn.utils
    sleap.nn.viz
-   sleap.nn.tracker.components
-   sleap.nn.tracker.kalman
    sleap.nn.config.data
    sleap.nn.config.model
    sleap.nn.config.optimization
    sleap.nn.config.outputs
    sleap.nn.config.training_job
    sleap.nn.config.utils
+   sleap.nn.architectures.common
+   sleap.nn.architectures.encoder_decoder
+   sleap.nn.architectures.hourglass
+   sleap.nn.architectures.hrnet
+   sleap.nn.architectures.leap
+   sleap.nn.architectures.pretrained_encoders
+   sleap.nn.architectures.resnet
+   sleap.nn.architectures.unet
+   sleap.nn.architectures.upsampling
+   sleap.nn.tracker.components
+   sleap.nn.tracker.kalman
    sleap.nn.data.augmentation
    sleap.nn.data.confidence_maps
    sleap.nn.data.dataset_ops
@@ -90,12 +99,3 @@ Developer API
    sleap.nn.data.resizing
    sleap.nn.data.training
    sleap.nn.data.utils
-   sleap.nn.architectures.common
-   sleap.nn.architectures.encoder_decoder
-   sleap.nn.architectures.hourglass
-   sleap.nn.architectures.hrnet
-   sleap.nn.architectures.leap
-   sleap.nn.architectures.pretrained_encoders
-   sleap.nn.architectures.resnet
-   sleap.nn.architectures.unet
-   sleap.nn.architectures.upsampling

develop/_sources/guides/cli.md

@@ -138,7 +138,10 @@ usage: sleap-track [-h] [-m MODELS] [--frames FRAMES] [--only-labeled-frames] [-
                    [data_path]
 
 positional arguments:
-  data_path             Path to data to predict on. This can be a labels (.slp) file or any supported video format.
+  data_path             Path to data to predict on. This can be one of the following: A .slp file containing labeled data; A folder containing multiple
+                        video files in supported formats; An individual video file in a supported format; A CSV file with a column of video file paths. 
+                        If more than one column is provided in the CSV file, the first will be used for the input data paths and the next column will be
+                        used as the output paths; A text file with a path to a video file on each line
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -153,7 +156,7 @@ optional arguments:
                         Only run inference on unlabeled suggested frames when running on labels dataset. This is useful for generating predictions for
                         initialization during labeling.
   -o OUTPUT, --output OUTPUT
-                        The output filename to use for the predicted data. If not provided, defaults to '[data_path].predictions.slp'.
+                        The output filename or directory path to use for the predicted data. If not provided, defaults to '[data_path].predictions.slp'.
   --no-empty-frames     Clear any empty frames that did not have any detected instances before saving to output.
   --verbosity {none,rich,json}
                         Verbosity of inference progress reporting. 'none' does not output anything during inference, 'rich' displays an updating

develop/genindex.html

@@ -1481,6 +1481,8 @@ <h2 id="E">E</h2>
 <h2 id="F">F</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="api/sleap.nn.tracker.components.html#sleap.nn.tracker.components.factory_object_keypoint_similarity">factory_object_keypoint_similarity() (in module sleap.nn.tracker.components)</a>
+</li>
       <li><a href="api/sleap.nn.architectures.resnet.html#sleap.nn.architectures.resnet.ResNet101.features_output_stride">features_output_stride (sleap.nn.architectures.resnet.ResNet101 attribute)</a>
 
       <ul>

develop/guides/cli.html

@@ -482,7 +482,10 @@ <h2>Inference and Tracking<a class="headerlink" href="#inference-and-tracking" t
                    [data_path]
 
 positional arguments:
-  data_path             Path to data to predict on. This can be a labels (.slp) file or any supported video format.
+  data_path             Path to data to predict on. This can be one of the following: A .slp file containing labeled data; A folder containing multiple
+                        video files in supported formats; An individual video file in a supported format; A CSV file with a column of video file paths. 
+                        If more than one column is provided in the CSV file, the first will be used for the input data paths and the next column will be
+                        used as the output paths; A text file with a path to a video file on each line
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -497,7 +500,7 @@ <h2>Inference and Tracking<a class="headerlink" href="#inference-and-tracking" t
                         Only run inference on unlabeled suggested frames when running on labels dataset. This is useful for generating predictions for
                         initialization during labeling.
   -o OUTPUT, --output OUTPUT
-                        The output filename to use for the predicted data. If not provided, defaults to &#39;[data_path].predictions.slp&#39;.
+                        The output filename or directory path to use for the predicted data. If not provided, defaults to &#39;[data_path].predictions.slp&#39;.
   --no-empty-frames     Clear any empty frames that did not have any detected instances before saving to output.
   --verbosity {none,rich,json}
                         Verbosity of inference progress reporting. &#39;none&#39; does not output anything during inference, &#39;rich&#39; displays an updating