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Release dev2 #141

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Release dev2 #141

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data-hound
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@data-hound data-hound commented Mar 3, 2023

New release for DANNCE

New Features

  • Mirror augmentation added
    • Mirror the images in half of the samples of the training set
    • If mirror augmentation is used, the right_keypoints indices and left_keypoints indices must be specified as well.
      For the skeleton, ['RHand, 'LHand', 'RFoot', 'LFoot'],
        set right_keypoints: [0, 2] and
        left_keypoints: [1, 3] in the config file
  • Options for layer and instance normalization added.
  • More Losses available: Huber, logcosh, gaussian cross entropy
  • n-rand-views configured to choose a subset of camera views for training/testing on weights trained for a lesser number of views.
    (Note: the number of views for which the weights have been trained should match the number of views specified with n-rand-views)
  • AVG+MAX training introduced where both the mean of heatmaps and the pmax of heatmaps are used for loss computation.
  • Saving prediction targets when running in MAX mode enabled

Codebase Improvements

  • Cluster scripts have now been remodelled to use yaml config files specific to each cluster instead of a set of shell scripts
    • Sbatch submissions for dannce and com training and prediction have been implemented.
  • Logging statements added throughout the code base with options to change the log level in the config (closes Logging code type error #117, closes dannce-predict loss very small, but result same like normal but shift #138)
  • DANNCE now supports mat73 format files for label3d and predictions
  • Python based scripts for plotting predictions on videos added
  • Newer tests using function name parsing
  • Uniform nomenclature for results_dir across codebase
  • Callbacks moved to a new module
  • Code refactored and reformatted across the codebase
  • Trimming dependencies in multiple modules
  • Saving pred targets moved to end of training

Bug Fixes and Minor Enhancements

  • Allow multiple read attempts when loading video
  • Added sigmoid normalization for pmax in dannce-predict
  • Introduced closing videos from prev experiments
  • Remove GPU placement during inference
  • Model summary printed during training to help debug mismatches
  • Save training data into npy volumes and cleanup unused
  • Remove hardcoded file names in multi-gpu

diegoaldarondo and others added 30 commits July 16, 2021 15:31
…d processing.py -adding backwards compatibility and defaulting to layer norm
updating jhw_dev with dev_fix_1.2 updates
This reverts commit 9058136.

TF 2.6 doesn't work with built in cuda/cudnn installations on the cluster that we've been using. Reverting to keep tf2.4 branch using tf2.4 requirements.
Anshuman Sabath and others added 24 commits May 12, 2022 17:42
…e_dev_savedata

Merge small changes to remote development into remote savedata branch
…in interface to save prediction targets only when the corresponding flag is set to true in config.
@data-hound data-hound marked this pull request as ready for review March 15, 2023 23:42
@spoonsso
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spoonsso commented May 3, 2023

@data-hound can you please test out the README install instructions in a fresh conda environment and then run all tests? thanks!

@data-hound
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Done. The install instructions work and all tests under /tests are passing

@data-hound can you please test out the README install instructions in a fresh conda environment and then run all tests? thanks!

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Logging code type error dannce-predict loss very small, but result same like normal but shift
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