diplomat deeplabcut analyze_videos

Summary

Run DIPLOMAT tracking on videos using a DEEPLABCUT project and trained network.

Usage

diplomat deeplabcut analyze_videos [-h] --config FILE --videos
                                          [FILE, ...]|FILE [--video_type STR]
                                          [--shuffle INT]
                                          [--training_set_index INT]
                                          [--gpu_index INT]
                                          [--save_as_csv BOOL]
                                          [--destination_folder STR]
                                          [--batch_size INT]
                                          [--cropping [INT, INT, INT, INT]]
                                          [--model_prefix STR]
                                          [--num_outputs INT]
                                          [--multi_output_format 'default'|'separate']
                                          [--predictor STR]
                                          [--predictor_settings {STR: VAL, ...}]

Options

usage: diplomat deeplabcut analyze_videos [-h] --config FILE --videos
                                          [FILE, ...]|FILE [--video_type STR]
                                          [--shuffle INT]
                                          [--training_set_index INT]
                                          [--gpu_index INT]
                                          [--save_as_csv BOOL]
                                          [--destination_folder STR]
                                          [--batch_size INT]
                                          [--cropping [INT, INT, INT, INT]]
                                          [--model_prefix STR]
                                          [--num_outputs INT]
                                          [--multi_output_format 'default'|'separate']
                                          [--predictor STR]
                                          [--predictor_settings {STR: VAL, ...}]

Run DIPLOMAT tracking on videos using a DEEPLABCUT project and trained
network.

optional arguments:
  -h, --help            show this help message and exit
  --config FILE, -c FILE
                        The path to the DLC config for the DEEPLABCUT project.
  --videos [FILE, ...]|FILE, -v [FILE, ...]|FILE
                        A single path or list of paths, to the location of
                        video files to run analysis on. Can also be a
                        directory.
  --video_type STR, -vt STR
                        Optional string, the video extension to search for if
                        the 'videos' argument is a directory to search inside
                        ('.avi', '.mp4', ...).
  --shuffle INT, -s INT
                        int, optional. Integer specifying which
                        TrainingsetFraction to use. By default, the first
                        (note that TrainingFraction is a list in config.yaml).
  --training_set_index INT, -tsi INT
                        int, optional. Integer specifying which
                        TrainingsetFraction to use. By default the first (note
                        that TrainingFraction is a list in config.yaml).
  --gpu_index INT, -gi INT
                        Integer index of the GPU to use for inference (in
                        tensorflow) defaults to 0, or selecting the first
                        detected GPU if available.
  --save_as_csv BOOL, -sac BOOL
                        Boolean, if true save the results to both a HDF5 file
                        (".h5") and also a CSV file, otherwise only save
                        results to a HDF5.
  --destination_folder STR, -df STR
                        The destination folder to save the resulting HDF5
                        track files to. Defaults to None, meaning save the
                        HDF5 in the same folder as the video file it was
                        generated from.
  --batch_size INT, -bs INT
                        The batch size to use while processing. Defaults to
                        None, which uses the default batch size for the
                        project.
  --cropping [INT, INT, INT, INT]
                        A tuple of 4 integers in the format (x1, x2, y1, y2),
                        specifying the boundaries of the cropping box analyze
                        in the video. Defaults to None, which uses the
                        cropping settings in the DLC config file.
  --model_prefix STR, -mp STR
                        The string prefix of the DEEPLABCUT model to use
                        defaults to no prefix (the default model).
  --num_outputs INT, -no INT
                        The number of outputs, or bodies to track in the
                        video. Defaults to the value specified in the DLC
                        config, or None if one is not specified.
  --multi_output_format 'default'|'separate', -mof 'default'|'separate'
                        The format to use when tracking multiple body parts of
                        the same type (multiple bodies, or num_outputs > 1).
                        Defaults to "default", which uses DLC's original
                        multi-output format. Passing "separate" saves
                        additional bodies by tacking on an index onto to body
                        part name (Nose, Nose2, Nose3, ...) instead of storing
                        tracks for the same body part type together.
  --predictor STR, -p STR
                        A String, the name of the predictor plugin to be used
                        to make predictions. If not specified, defaults to the
                        segmented frame pass engine
                        ("SegmentedFramePassEngine").
  --predictor_settings {STR: VAL, ...}, -ps {STR: VAL, ...}
                        Optional dictionary of strings to any. This will
                        specify what settings a predictor should use,
                        completely ignoring any settings specified in the
                        config.yaml. Default value is None, which tells this
                        method to use the settings specified in the
                        config.yaml.