deploy: b9bb300

develop/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: a7b7f9800faa1bcc2746e1b3ba7ad6cf
+config: ea14d6c449de46604b07382202b24124
 tags: 645f666f9bcd5a90fca523b33c5a78b7

develop/CODE_OF_CONDUCT.html

@@ -9,7 +9,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
 
-    <title>Contributor Covenant Code of Conduct &#8212; SLEAP (v1.4.1a2)</title>
+    <title>Contributor Covenant Code of Conduct &#8212; SLEAP (v1.3.4)</title>
 
 
 

develop/CONTRIBUTING.html

@@ -9,7 +9,7 @@
     <meta charset="utf-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
 
-    <title>Contributing to SLEAP &#8212; SLEAP (v1.4.1a2)</title>
+    <title>Contributing to SLEAP &#8212; SLEAP (v1.3.4)</title>
 
 
 

develop/_sources/api.rst

@@ -19,38 +19,6 @@ Developer API
    sleap.message
    sleap.skeleton
    sleap.util
-   sleap.info.align
-   sleap.info.feature_suggestions
-   sleap.info.labels
-   sleap.info.metrics
-   sleap.info.summary
-   sleap.info.trackcleaner
-   sleap.info.write_tracking_h5
-   sleap.io.asyncvideo
-   sleap.io.convert
-   sleap.io.dataset
-   sleap.io.legacy
-   sleap.io.pathutils
-   sleap.io.video
-   sleap.io.videowriter
-   sleap.io.visuals
-   sleap.io.format.adaptor
-   sleap.io.format.alphatracker
-   sleap.io.format.coco
-   sleap.io.format.csv
-   sleap.io.format.deeplabcut
-   sleap.io.format.deepposekit
-   sleap.io.format.dispatch
-   sleap.io.format.filehandle
-   sleap.io.format.genericjson
-   sleap.io.format.hdf5
-   sleap.io.format.labels_json
-   sleap.io.format.leap_matlab
-   sleap.io.format.main
-   sleap.io.format.ndx_pose
-   sleap.io.format.nix
-   sleap.io.format.sleap_analysis
-   sleap.io.format.text
    sleap.nn.callbacks
    sleap.nn.evals
    sleap.nn.heads
@@ -65,12 +33,6 @@ Developer API
    sleap.nn.training
    sleap.nn.utils
    sleap.nn.viz
-   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
@@ -99,3 +61,41 @@ Developer API
    sleap.nn.data.resizing
    sleap.nn.data.training
    sleap.nn.data.utils
+   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.info.align
+   sleap.info.feature_suggestions
+   sleap.info.labels
+   sleap.info.metrics
+   sleap.info.summary
+   sleap.info.trackcleaner
+   sleap.info.write_tracking_h5
+   sleap.io.asyncvideo
+   sleap.io.convert
+   sleap.io.dataset
+   sleap.io.legacy
+   sleap.io.pathutils
+   sleap.io.video
+   sleap.io.videowriter
+   sleap.io.visuals
+   sleap.io.format.adaptor
+   sleap.io.format.alphatracker
+   sleap.io.format.coco
+   sleap.io.format.csv
+   sleap.io.format.deeplabcut
+   sleap.io.format.deepposekit
+   sleap.io.format.dispatch
+   sleap.io.format.filehandle
+   sleap.io.format.genericjson
+   sleap.io.format.hdf5
+   sleap.io.format.labels_json
+   sleap.io.format.leap_matlab
+   sleap.io.format.main
+   sleap.io.format.ndx_pose
+   sleap.io.format.nix
+   sleap.io.format.sleap_analysis
+   sleap.io.format.text

develop/_sources/guides/cli.md

@@ -36,8 +36,8 @@ optional arguments:
 
 ```none
 usage: sleap-train [-h] [--video-paths VIDEO_PATHS] [--val_labels VAL_LABELS]
-                   [--test_labels TEST_LABELS] [--tensorboard] [--save_viz] 
-                   [--keep_viz] [--zmq] [--run_name RUN_NAME] [--prefix PREFIX]
+                   [--test_labels TEST_LABELS] [--tensorboard] [--save_viz]
+                   [--zmq] [--run_name RUN_NAME] [--prefix PREFIX]
                    [--suffix SUFFIX]
                    training_job_path [labels_path]
 
@@ -68,8 +68,6 @@ optional arguments:
   --save_viz            Enable saving of prediction visualizations to the run
                         folder if not already specified in the training job
                         config.
-  --keep_viz            Keep prediction visualization images in the run
-                        folder after training if --save_viz is enabled.
   --zmq                 Enable ZMQ logging (for GUI) if not already specified
                         in the training job config.
   --run_name RUN_NAME   Run name to use when saving file, overrides other run
@@ -101,9 +99,9 @@ optional arguments:
   -e [EXPORT_PATH], --export_path [EXPORT_PATH]
                         Path to output directory where the frozen model will be exported to.
                         Defaults to a folder named 'exported_model'.
-  -r, --ragged RAGGED
-                        Keep tensors ragged if present. If ommited, convert
-                        ragged tensors into regular tensors with NaN padding.
+  -u, --unrag UNRAG
+                        Convert ragged tensors into regular tensors with NaN padding.
+                        Defaults to True.
   -n, --max_instances MAX_INSTANCES
                         Limit maximum number of instances in multi-instance models.
                         Not available for ID models. Defaults to None.
@@ -138,10 +136,7 @@ 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 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
+  data_path             Path to data to predict on. This can be a labels (.slp) file or any supported video format.
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -156,7 +151,7 @@ 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 or directory path to use for the predicted data. If not provided, defaults to '[data_path].predictions.slp'.
+                        The output filename 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
@@ -327,8 +322,7 @@ optional arguments:
                               analysis file for the latter video is given a default name.
   --format FORMAT       Output format. Default ('slp') is SLEAP dataset;
                         'analysis' results in analysis.h5 file; 'analysis.nix' results
-                        in an analysis nix file; 'analysis.csv' results
-                        in an analysis csv file; 'h5' or 'json' results in SLEAP dataset
+                        in an analysis nix file; 'h5' or 'json' results in SLEAP dataset
                         with specified file format.
   --video VIDEO         Path to video (if needed for conversion).
 ```
@@ -395,9 +389,6 @@ optional arguments:
   --distinctly_color DISTINCTLY_COLOR
                         Specify how to color instances. Options include: "instances",
                         "edges", and "nodes" (default: "instances")
-  --background BACKGROUND
-                        Specify the type of background to be used to save the videos.
-                        Options: original, black, white and grey. (default: "original")
 ```
 
 ## Debugging

develop/_sources/guides/gui.md

@@ -60,7 +60,7 @@ Note that many of the menu command have keyboard shortcuts which can be configur
 
 "**Edge Style**" controls whether edges are drawn as thin lines or as wedges which indicate the {ref}`orientation` of the instance (as well as the direction of the part affinity field which would be used to predict the connection between nodes when using a "bottom-up" approach).
 
-"**Trail Length**" allows you to show a trail of where each instance was located in prior frames (the length of the trail is the number of prior frames). This can be useful when proofreading predictions since it can help you detect swaps in the identities of animals across frames. By default, you can only select trail lengths of up to 250 frames. You can use a custom trail length by modifying the default length in the `preferences.yaml` file. However, using trail lengths longer than about 500 frames can result in significant lag.
+"**Trail Length**" allows you to show a trail of where each instance was located in prior frames (the length of the trail is the number of prior frames). This can be useful when proofreading predictions since it can help you detect swaps in the identities of animals across frames.
 
 "**Fit Instances to View**" allows you to toggle whether the view is auto-zoomed to the instances in each frame. This can be useful when proofreading predictions.
 

develop/_sources/installation.md

@@ -137,13 +137,13 @@ SLEAP can be installed three different ways: via {ref}`conda package<condapackag
 **Windows** and **Linux**
 
 ```bash
-mamba create -y -n sleap -c conda-forge -c nvidia -c sleap -c anaconda sleap=1.4.1a2
+mamba create -y -n sleap -c conda-forge -c nvidia -c sleap -c anaconda sleap=1.3.4
 ```
 
 **Mac OS X** and **Apple Silicon**
 
 ```bash
-mamba create -y -n sleap -c conda-forge -c anaconda -c sleap sleap=1.4.1a2
+mamba create -y -n sleap -c conda-forge -c anaconda -c sleap sleap=1.3.4
 ```
 
 **This is the recommended installation method**.
@@ -232,7 +232,7 @@ Although you do not need Mambaforge installed to perform a `pip install`, we rec
 3. Finally, we can perform the `pip install`:
 
    ```bash
-   pip install sleap[pypi]==1.4.1a2
+   pip install sleap[pypi]==1.3.4
    ```
 
    This works on **any OS except Apple silicon** and on **Google Colab**.

develop/_sources/notebooks/Data_structures.ipynb

@@ -56,7 +56,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.4\"\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",
         "# conda create -n sleap -c sleap -c conda-forge -c nvidia sleap"

develop/_sources/notebooks/Interactive_and_realtime_inference.ipynb

@@ -60,7 +60,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.4\"\n",
         "\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",

develop/_sources/notebooks/Interactive_and_resumable_training.ipynb

@@ -62,7 +62,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.4\"\n",
         "\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",

develop/_sources/notebooks/Model_evaluation.ipynb

@@ -40,7 +40,7 @@
       ],
       "source": [
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.4\"\n",
         "!apt -qq install tree\n",
         "!wget -q https://storage.googleapis.com/sleap-data/reference/flies13/td_fast.210505_012601.centered_instance.n%3D1800.zip\n",
         "!unzip -qq -o -d \"td_fast.210505_012601.centered_instance.n=1800\" \"td_fast.210505_012601.centered_instance.n=1800.zip\""

develop/_sources/notebooks/Post_inference_tracking.ipynb

@@ -61,7 +61,7 @@
       "source": [
         "# This should take care of all the dependencies on colab:\n",
         "!pip uninstall -qqq -y opencv-python opencv-contrib-python\n",
-        "!pip install -qqq \"sleap[pypi]>=1.3.3\"\n",
+        "!pip install -qqq \"sleap[pypi]>=1.3.4\"\n",
         "\n",
         "# But to do it locally, we'd recommend the conda package (available on Windows + Linux):\n",
         "# conda create -n sleap -c sleap -c conda-forge -c nvidia sleap"