Deeplabcut

Latest version: v2.3.9

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2.1.5

Happy new year! This version has a few minor updates. A big release is around the corner...

- Accelerate training set creation (by at least 2x, up to 10x under multiple train size/split conditions);
- Possibility to pass lists of train–test indices for user-defined splits in create_training_dataset()
- Selecting bodyparts for plotting; fixed https://github.com/AlexEMG/DeepLabCut/issues/504
- plot_trajectories now allows for selection of bodyparts (also in the Project GUI)
- create_labeled_videos now allows selection of bodyparts in Project GUI
- fix for 3D plotting if videos of different views have different length https://github.com/AlexEMG/DeepLabCut/commit/de35651835f8e3e59d09b2533fa6f88ab64ff449
- reading num_outputs from configfile (if it exists): https://github.com/AlexEMG/DeepLabCut/commit/2fe0fccd904b95ead21cfb2bfa0591e4ef26f996
- Better message when no videos are found during analysis: https://github.com/AlexEMG/DeepLabCut/commit/d275c3cf91d16a5d122814894b8aec711ec47af9

This release includes contributions from the new DLC-ChanZuckerbergInitiative fellows JessyLauer jeylau, alexEMG and MMathislab

2.1.4

- new command to start the GUI: python -m deeplabcut
https://github.com/AlexEMG/DeepLabCut/pull/484
- updated docs with regard to types of augmentation available and other aspects
- cleaned up loaders (now will throw out corrupt images; training more stable) https://github.com/AlexEMG/DeepLabCut/issues/463
- fix for negative coordinates https://github.com/AlexEMG/DeepLabCut/pull/501

2.1.1

Bug fixes and minor edits:
- fix docstring in tensorpack and calculation of processratio https://github.com/AlexEMG/DeepLabCut/pull/455
- multi peak extraction had an error (in 2.1 but not before): https://forum.image.sc/t/issue-with-analyzing-multiple-body-parts/30453/6
- one can pick more parameters in the GUI

2.1

**New Features, major updates and upgrades:**
- new **Project Manager GUI** (see docs/PROJECT_GUI.md)
- **dynamic auto-cropping** is available (issue 198): use during analyze_videos: deeplabcut.analyze_videos(path_config_file,[video], dynamic=(True,.1,30)). This dramatically improves the inference speed for typical applications in neuroscience such as open field behaviors where the animal is much smaller than the frame and no prior tracking is necessary.
- Integrated **MobileNetV2s** (described in Pretraining boosts out-of-domain robustness for pose estimation by Alexander Mathis, Mert Yüksekgönül, Byron Rogers, Matthias Bethge, Mackenzie W. Mathis https://arxiv.org/abs/1909.11229)
- integrated **TF based inference** code (based on https://arxiv.org/abs/1909.11229).
- Added in new data augmentation options with imgaug see Box 2 in docs (https://github.com/aleju/imgaug)
- New function, create_training_model_comparison that allows the user to create identical shuffles for multiple network and/or data augmentation testing.
- Updated evaluation metric: one can now evaluate the model at different scales (by passing rescale=True one can evaluate the model at the 'global_scale' variable (as set in the test/pose_config.yaml file for a particular project). I.e. every image will be resized according to that scale and prediction will be compared to the resized ground truth. The error will be reported in pixels at rescaled to the *original* size. I.e. For a [200,200] pixel image evaluated at global_scale=.5, the predictions are calculated on [100,100] pixel images, compared to 1/2*ground truth and this error is then multiplied by 2. The evaluation images are also shown for the original size!
- Retraining now also loads deconvolution weights by default
- dlc scorer name changed, and backwards compatibility maintained. E.g. data for videos like abc.mp4 will be saved as abcDLC_resnet50_xyz.h5 or abcDLC_mobnet35_xyz.h5 (depending on the network)

**Bug fixes and minor edits:**
- Changed imresize and imread from scipy.misc (deprecated functions); now uses openCV
- Colors changed when manually extracting outliers https://forum.image.sc/t/extract-outlier-frames-saves-images-with-different-color/29868/2
- Minor edits to ShortenVideo function, now returns path to shortened video
- By default .csv exported when analyzing a video when initializing a human pre-trained network (https://github.com/AlexEMG/DeepLabCut/pull/427)
- Changes to default values in augmentation with TensorPack; See results here: https://github.com/AlexEMG/DeepLabCut/pull/426 > Thanks katierupp! and the from #429 thanks ppwwyyxx!
- Updated link to human DEMO on COLAB
- updated setup.py dependencies (addresses 434, 433, 441, 440)
- edited and expanded test functions
- expanded docs, updated wiki

Contributors: alexEMG, meet10may, MMathisLab, mertyg & tbiasi

2.0.9

- Tensorpack integration for more choices of data augmentation.
PR: https://github.com/AlexEMG/DeepLabCut/pull/409 Thanks to Katie Rupp!
- Option to output multiple predictions per bodypart https://github.com/AlexEMG/DeepLabCut/pull/321 Thanks to Pierre Karashchuk!
- Fixed error in deeplabcut.analyze_time_lapse_frames() -- was not updated when changing TF code). Thanks to Ambareesh Jayakumari!
- added utilityfunctions: adddatasetstovideolistandviceversa, dropannotationfileentriesduetodeletedimages, dropduplicatesinannotatinfiles (among others)
- new functions to crop and downsample videos deeplabcut.ShortenVideo and deeplabcut.DownSampleVideo
- documentation of extra helper functions (see docs)
- option to check number of frames not from metadata of video
https://github.com/AlexEMG/DeepLabCut/issues/422

2.0.8

**New features:**
- new human project demo: extract human pose from video with pretrained network (deeplabcut.create_pretrained_human_project). The weights are from the DeeperCut paper.
- new COLAB demo on human project
- new skeleton analyzer (and docs) see 349
- multi peak extraction see 321

**Function updates:**
- documentation updates
- updated COLAB notebooks
- updated testscripts
- tensorflow code clean up (warning messages for TF 1.13 and 1.14)

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