2.2rc2! is up

2.2rc2 is up, and has some great new additions!

To upgrade simply run pip install ‘deeplabcut[gui]’==2.2rc2 (this is fully backwards compatible with your 2.2rc1 projects, and we 1000% recommend upgrading). Read the release note here (which has links to detailed code): https://github.com/DeepLabCut/DeepLabCut/releases/tag/2.2rc2

New features:

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  • DLCRNet new default net when you use maDLC (also select it easily in the Project GUI)! 🔥

  • smarter inclusion of identity (ID) information & and new way to track using ID only:

    • Automatically stitch with identity when possible!

    • Allow tracking with identity only (optimal ID assignment based on soft voting of body part identity predictions)

    • to use: deeplabcut.convert_detections2tracklets(..., identity_only=True)

    • read more here + TL’DR: if you trained with identity=True you can leverage this in tracking (it was already leveraged in assembly). This is ideal when you animal is occluded or disappears, as in this example (awesome data from co-author William Menegas!). Read more about predicting animal identity from images in our preprint here.

  • user can define frame rate of camera for make labeled videos!

  • dynamically allocate memory on GPU in tensorflow for video analysis deeplabcut.analyze_videos(config_path, [new_video_path], allow_growth=True)

  • API update to create video with all detections (easier to use!): deeplabcut.create_video_with_all_detections(config_path, ['/fullpath/project/videos/testVideo.mp4']) —> now you can make a video right after pose estimation step quickly (to check quality on a video before doing tracking).

  • you can fund us in 1 click 🙏 🤩 💖

  • Check for the addition of new animals to the config while labeling (namely, if you find you have MORE animals that you thought in your maDLC project, just add a new name to the config.yaml, and then re-open labeling GUI and go!)

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Upgrades:

  • select DLCRNet from main project manager GUI!

  • installation docs updated!

  • tracklet docs upgraded!

  • docstring upgrade (thanks @Joilence)

  • Roadmap updated!

  • user-defined skeleton possible (but not advised per se)

  • much faster dataset creation!

  • if symlink fails, move videos during project creation

Bug Fixes:

  • single animal mode supported in new tracklet stitcher

  • return 0 mAP when no reasonable assemblies are found (vs just indexingError); i.e., more informative error now

  • force data frame to start at 0 (i.e., even if not animal visible)

  • image panel error fixed

  • path clean up (thanks @sin-mike)

  • use the user-input individual names

  • config integrity on re-crop fix

  • slicing error (thanks @backyardbiomech!)

Lastly, if you have not, please consider giving us a star on Github! ⭐️

mackenzie