I’m following the network refinement workflow. I have manually selected outlier frames and adjusted tracker errors using the GUI, and I seem to have successfully merged these datasets with my original frame selection. According to the workflow (described here: https://github.com/DeepLabCut/DeepLabCut/blob/4e7306baefe7a4f1b107251dae07e138ce02215c/docs/functionDetails.md#g-train-the-network), the new training set should be stored in a new iteration folder. However, my new training set, as well as new .csv, .h5, .mat, and .pickle files, are stored in the iteration-0 folders of their respective subdirectories (see screenshot; I specified this to be shuffle2 in the GUI “create training dataset” panel).
Why this is relevant: when I started retraining (with shuffle=2 selected in the train function), all new snapshots are being stored in the shuffle1 folder. I am concerned that the newly augmented training set (shuffle2) is not being used in retraining.
Am I correct in assuming that shuffle2 is not being used for retraining? If so, what is the root of this problem? Does the confusion stem from failure to create a new iteration folder? Or have I just goofed on making another adjustment that would tell DLC to use shuffle2 instead of shuffle1?
One more note: I just realized that I forgot to adjust the initial weight in the train pose_cfg.yaml file to the last snapshot of my first training session using shuffle1, but I don’t see how this could cause the issue described above.
I and the Bettas thank you v much for any help you can give!