QUICK GUIDE to single Animal Training:

The main steps to take you from project creation to analyzed videos:

Open ipython in the terminal:

ipython
import deeplabcut

Create a new project:

deeplabcut.create_new_project(‘project_name’,‘experimenter’,[‘path of video 1’,‘path of video2’,..])

Set a config_path variable for ease of use + go edit this file!:

config_path = ‘yourdirectory/project_name/config.yaml’ 

Extract frames:

deeplabcut.extract_frames(config_path)

Label frames:

deeplabcut.label_frames(config_path)

Check labels [OPTIONAL]:

deeplabcut.check_labels(config_path)

Create training dataset:

deeplabcut.create_training_dataset(config_path)

Train the network:

deeplabcut.train_network(config_path)

Evaluate the trained network:

deeplabcut.evaluate_network(config_path)

Video analysis:

deeplabcut.analyze_videos(config_path, [‘path of video 1’,‘path of video2’, ...])

Filter predictions [OPTIONAL]:

deeplabcut.filterpredictions(config_path, [‘path of video 1’,‘path of video2’,..])

Plot results (trajectories):

deeplabcut.plot_trajectories(config_path, [‘path of video 1’,‘path of video2’,..], filtered=True)

Create a video:

deeplabcut.create_labeled_video(config_path, [‘path of video 1’,‘path of video2’,..]filtered=True)