diplomat deeplabcut analyze_frames

Summary

Takes a DIPLOMAT Frame Store file (.dlfs) and makes predictions for the stored frames, using whatever predictor plugin is selected. This allows for the video to be run through the Deep Neural Network once, and then run through several prediction algorithms as many times as desired, saving time. It also allows for frames to be processed on one computer to be transferred to another computer for post-processing and predictions.

Usage

diplomat deeplabcut analyze_frames [-h] --config FILE --frame_stores
                                          [FILE, ...]|FILE [--predictor STR]
                                          [--save_as_csv BOOL]
                                          [--multi_output_format 'default'|'separate-bodyparts']
                                          [--video_folders [FILE, ...]|FILE]
                                          [--num_outputs INT] [--shuffle INT]
                                          [--training_set_index INT]
                                          [--predictor_settings {STR: VAL, ...}]

Options

usage: diplomat deeplabcut analyze_frames [-h] --config FILE --frame_stores
                                          [FILE, ...]|FILE [--predictor STR]
                                          [--save_as_csv BOOL]
                                          [--multi_output_format 'default'|'separate-bodyparts']
                                          [--video_folders [FILE, ...]|FILE]
                                          [--num_outputs INT] [--shuffle INT]
                                          [--training_set_index INT]
                                          [--predictor_settings {STR: VAL, ...}]

Takes a DIPLOMAT Frame Store file (.dlfs) and makes predictions for the stored
frames, using whatever predictor plugin is selected. This allows for the video
to be run through the Deep Neural Network once, and then run through several
prediction algorithms as many times as desired, saving time. It also allows
for frames to be processed on one computer to be transferred to another
computer for post-processing and predictions.

optional arguments:
  -h, --help            show this help message and exit
  --config FILE, -c FILE
                        The path to the DLC config to use to interpret this
                        data. The .DLFS will inherit the neural network of
                        this project, allowing for frame labeling using this
                        project.
  --frame_stores [FILE, ...]|FILE, -fs [FILE, ...]|FILE
                        The paths to the frame stores (.dlfs files), string or
                        list of strings.
  --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").
  --save_as_csv BOOL, -sac BOOL
                        A Boolean, True to save the results to the human
                        readable .csv format, otherwise false.
  --multi_output_format 'default'|'separate-bodyparts', -mof 'default'|'separate-bodyparts'
                        A string. Determines the multi output format used.
                        "default" uses the default format, while "separate-
                        bodyparts" separates the multi output predictions such
                        that each is its own body part.
  --video_folders [FILE, ...]|FILE, -vf [FILE, ...]|FILE
                        None, a string, or a list of strings, folders to
                        search through to find videos which correlate to the
                        .dlfs files. If set to None, this method will search
                        for the corresponding videos in the directory each
                        .dlfs file is contained in.
  --num_outputs INT, -no INT
                        int, default
  --shuffle INT, -s INT
                        int, optional. An integer specifying the shuffle index
                        of the training dataset used for training the network.
                        The default is 1.
  --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).
  --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.