tips.md

Tips

This file has assorted tips related to NCams and DeepLabCut.

Moving DLC network to a different project

1. Change filenames in config.yaml
2. Change filenames in pose_cfg.yaml (two of them)
3. Change directory name dlc-models/iteration-0/<PROJECT NAME>-trainset95shuffle1

Continuing teaching a NN on new videos

Instead of using deeplabcut.add_new_videos to add new videos to the project and sample training data from them, one can do the following steps:

1. Edit your config.yaml by replacing the video list with the new videos, save the text referencing the old videos. You may want to change the numframes2pick variable in config, too.
2. Extract frames: deeplabcut.extract_frames(config_path, mode='automatic', algo='uniform', crop=False, userfeedback=False)
3. Label frames: deeplabcut.label_frames(config_path)
4. Put back the old videos paths (do not remove the new ones) into the config.yaml.
5. Merge datasets: deeplabcut.merge_datasets(config_path)
6. Create training dataset. deeplabcut.create_training_dataset(config_path)
7. Go to train and test pose_cfg.yaml of the new interation (e.g. in '<DLC_PROJECT>/dlc-models/iteration-1/CMGPretrainedNetworkDec3-trainset95shuffle1/train/pose_cfg.yaml' and '<DLC_PROJECT>/dlc-models/iteration-1/CMGPretrainedNetworkDec3-trainset95shuffle1/test/pose_cfg.yaml') and change the init_weights variable to point to the snapshot from previous network or iteration (for example, '<DLC_PROJECT>\dlc-models\iteration-0\CMGPretrainedNetworkDec3-trainset95shuffle1\train\snapshot-250000' without file extension). Note: put <DLC_PROJECT> as a full path from root directory or disk.
8. Start training.