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

-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.