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Changelog

Master

0.16.0 (01/07/2021)

Highlights

  • Support using backbone from pytorch-image-models(timm)
  • Support PIMS Decoder
  • Demo for skeleton-based action recognition
  • Support Timesformer

New Features

  • Support using backbones from pytorch-image-models(timm) for TSN (#880)
  • Support torchvision transformations in preprocessing pipelines (#972)
  • Demo for skeleton-based action recognition (#972)
  • Support Timesformer (#839)

Improvements

  • Add a tool to find invalid videos (#907, #950)
  • Add an option to specify spectrogram_type (#909)
  • Add json output to video demo (#906)
  • Add MIM related docs (#918)
  • Rename lr to scheduler (#916)
  • Support --cfg-options for demos (#911)
  • Support number counting for flow-wise filename template (#922)
  • Add Chinese tutorial (#941)
  • Change ResNet3D default values (#939)
  • Adjust script structure (#935)
  • Add font color to args in long_video_demo (#947)
  • Polish code style with Pylint (#908)
  • Support PIMS Decoder (#946)
  • Improve Metafiles (#956, #979, #966)
  • Add links to download Kinetics400 validation (#920)
  • Audit the usage of shutil.rmtree (#943)
  • Polish localizer related codes(#913)

Bug and Typo Fixes

  • Fix spatiotemporal detection demo (#899)
  • Fix docstring for 3D inflate (#925)
  • Fix bug of writing text to video with TextClip (#952)
  • Fix mmcv install in CI (#977)

ModelZoo

  • Add TSN with Swin Transformer backbone as an example for using pytorch-image-models(timm) backbones (#880)
  • Port CSN checkpoints from VMZ (#945)
  • Release various checkpoints for UCF101, HMDB51 and Sthv1 (#938)
  • Support Timesformer (#839)
  • Update TSM modelzoo (#981)

0.15.0 (31/05/2021)

Highlights

  • Support PoseC3D
  • Support ACRN
  • Support MIM

New Features

  • Support PoseC3D (#786, #890)
  • Support MIM (#870)
  • Support ACRN and Focal Loss (#891)
  • Support Jester dataset (#864)

Improvements

  • Add metric_options for evaluation to docs (#873)
  • Support creating a new label map based on custom classes for demos about spatio temporal demo (#879)
  • Improve document about AVA dataset preparation (#878)
  • Provide a script to extract clip-level feature (#856)

Bug and Typo Fixes

  • Fix issues about resume (#877, #878)
  • Correct the key name of eval_results dictionary for metric 'mmit_mean_average_precision' (#885)

ModelZoo

  • Support Jester dataset (#864)
  • Support ACRN and Focal Loss (#891)

0.14.0 (30/04/2021)

Highlights

  • Support TRN
  • Support Diving48

New Features

  • Support TRN (#755)
  • Support Diving48 (#835)
  • Support Webcam Demo for Spatio-temporal Action Detection Models (#795)

Improvements

  • Add softmax option for pytorch2onnx tool (#781)
  • Support TRN (#755)
  • Test with onnx models and TensorRT engines (#758)
  • Speed up AVA Testing (#784)
  • Add self.with_neck attribute (#796)
  • Update installation document (#798)
  • Use a random master port (#809)
  • Update AVA processing data document (#801)
  • Refactor spatio-temporal augmentation (#782)
  • Add QR code in CN README (#812)
  • Add Alternative way to download Kinetics (#817, #822)
  • Refactor Sampler (#790)
  • Use EvalHook in MMCV with backward compatibility (#793)
  • Use MMCV Model Registry (#843)

Bug and Typo Fixes

  • Fix a bug in pytorch2onnx.py when num_classes <= 4 (#800, #824)
  • Fix demo_spatiotemporal_det.py error (#803, #805)
  • Fix loading config bugs when resume (#820)
  • Make HMDB51 annotation generation more robust (#811)

ModelZoo

  • Update checkpoint for 256 height in something-V2 (#789)
  • Support Diving48 (#835)

0.13.0 (31/03/2021)

Highlights

  • Support LFB
  • Support using backbone from MMCls/TorchVision
  • Add Chinese documentation

New Features

Improvements

  • Add slowfast config/json/log/ckpt for training custom classes of AVA (#678)
  • Set RandAugment as Imgaug default transforms (#585)
  • Add --test-last & --test-best for tools/train.py to test checkpoints after training (#608)
  • Add fcn_testing in TPN (#684)
  • Remove redundant recall functions (#741)
  • Recursively remove pretrained step for testing (#695)
  • Improve demo by limiting inference fps (#668)

Bug and Typo Fixes

  • Fix a bug about multi-class in VideoDataset (#723)
  • Reverse key-value in anet filelist generation (#686)
  • Fix flow norm cfg typo (#693)

ModelZoo

  • Add LFB for AVA2.1 (#553)
  • Add TSN with ResNeXt-101-32x4d backbone as an example for using MMCls backbones (#679)
  • Add TSN with Densenet161 backbone as an example for using TorchVision backbones (#720)
  • Add slowonly_nl_embedded_gaussian_r50_4x16x1_150e_kinetics400_rgb (#690)
  • Add slowonly_nl_embedded_gaussian_r50_8x8x1_150e_kinetics400_rgb (#704)
  • Add slowonly_nl_kinetics_pretrained_r50_4x16x1(8x8x1)_20e_ava_rgb (#730)

0.12.0 (28/02/2021)

Highlights

  • Support TSM-MobileNetV2
  • Support TANet
  • Support GPU Normalize

New Features

  • Support TSM-MobileNetV2 (#415)
  • Support flip with label mapping (#591)
  • Add seed option for sampler (#642)
  • Support GPU Normalize (#586)
  • Support TANet (#595)

Improvements

  • Training custom classes of ava dataset (#555)
  • Add CN README in homepage (#592, #594)
  • Support soft label for CrossEntropyLoss (#625)
  • Refactor config: Specify train_cfg and test_cfg in model (#629)
  • Provide an alternative way to download older kinetics annotations (#597)
  • Update FAQ for
    • 1). data pipeline about video and frames (#598)
    • 2). how to show results (#598)
    • 3). batch size setting for batchnorm (#657)
    • 4). how to fix stages of backbone when finetuning models (#658)
  • Modify default value of save_best (#600)
  • Use BibTex rather than latex in markdown (#607)
  • Add warnings of uninstalling mmdet and supplementary documents (#624)
  • Support soft label for CrossEntropyLoss (#625)

Bug and Typo Fixes

  • Fix value of pem_low_temporal_iou_threshold in BSN (#556)
  • Fix ActivityNet download script (#601)

ModelZoo

  • Add TSM-MobileNetV2 for Kinetics400 (#415)
  • Add deeper SlowFast models (#605)

0.11.0 (31/01/2021)

Highlights

  • Support imgaug
  • Support spatial temporal demo
  • Refactor EvalHook, config structure, unittest structure

New Features

  • Support imgaug for augmentations in the data pipeline (#492)
  • Support setting max_testing_views for extremely large models to save GPU memory used (#511)
  • Add spatial temporal demo (#547, #566)

Improvements

  • Refactor EvalHook (#395)
  • Refactor AVA hook (#567)
  • Add repo citation (#545)
  • Add dataset size of Kinetics400 (#503)
  • Add lazy operation docs (#504)
  • Add class_weight for CrossEntropyLoss and BCELossWithLogits (#509)
  • add some explanation about the resampling in slowfast (#502)
  • Modify paper title in README.md (#512)
  • Add alternative ways to download Kinetics (#521)
  • Add OpenMMLab projects link in README (#530)
  • Change default preprocessing to shortedge to 256 (#538)
  • Add config tag in dataset README (#540)
  • Add solution for markdownlint installation issue (#497)
  • Add dataset overview in readthedocs (#548)
  • Modify the trigger mode of the warnings of missing mmdet (#583)
  • Refactor config structure (#488, #572)
  • Refactor unittest structure (#433)

Bug and Typo Fixes

  • Fix a bug about ava dataset validation (#527)
  • Fix a bug about ResNet pretrain weight initialization (#582)
  • Fix a bug in CI due to MMCV index (#495)
  • Remove invalid links of MiT and MMiT (#516)
  • Fix frame rate bug for AVA preparation (#576)

ModelZoo

0.10.0 (31/12/2020)

Highlights

  • Support Spatio-Temporal Action Detection (AVA)
  • Support precise BN

New Features

  • Support precise BN (#501)
  • Support Spatio-Temporal Action Detection (AVA) (#351)
  • Support to return feature maps in inference_recognizer (#458)

Improvements

  • Add arg stride to long_video_demo.py, to make inference faster (#468)
  • Support training and testing for Spatio-Temporal Action Detection (#351)
  • Fix CI due to pip upgrade (#454)
  • Add markdown lint in pre-commit hook (#255)
  • Speed up confusion matrix calculation (#465)
  • Use title case in modelzoo statistics (#456)
  • Add FAQ documents for easy troubleshooting. (#413, #420, #439)
  • Support Spatio-Temporal Action Detection with context (#471)
  • Add class weight for CrossEntropyLoss and BCELossWithLogits (#509)
  • Add Lazy OPs docs (#504)

Bug and Typo Fixes

  • Fix typo in default argument of BaseHead (#446)
  • Fix potential bug about output_config overwrite (#463)

ModelZoo

  • Add SlowOnly, SlowFast for AVA2.1 (#351)

0.9.0 (30/11/2020)

Highlights

  • Support GradCAM utils for recognizers
  • Support ResNet Audio model

New Features

  • Automatically add modelzoo statistics to readthedocs (#327)
  • Support GYM99 (#331, #336)
  • Add AudioOnly Pathway from AVSlowFast. (#355)
  • Add GradCAM utils for recognizer (#324)
  • Add print config script (#345)
  • Add online motion vector decoder (#291)

Improvements

  • Support PyTorch 1.7 in CI (#312)
  • Support to predict different labels in a long video (#274)
  • Update docs bout test crops (#359)
  • Polish code format using pylint manually (#338)
  • Update unittest coverage (#358, #322, #325)
  • Add random seed for building filelists (#323)
  • Update colab tutorial (#367)
  • set default batch_size of evaluation and testing to 1 (#250)
  • Rename the preparation docs to README.md (#388)
  • Move docs about demo to demo/README.md (#329)
  • Remove redundant code in tools/test.py (#310)
  • Automatically calculate number of test clips for Recognizer2D (#359)

Bug and Typo Fixes

  • Fix rename Kinetics classnames bug (#384)
  • Fix a bug in BaseDataset when data_prefix is None (#314)
  • Fix a bug about tmp_folder in OpenCVInit (#357)
  • Fix get_thread_id when not using disk as backend (#354, #357)
  • Fix the bug of HVU object num_classes from 1679 to 1678 (#307)
  • Fix typo in export_model.md (#399)
  • Fix OmniSource training configs (#321)
  • Fix Issue #306: Bug of SampleAVAFrames (#317)

ModelZoo

  • Add SlowOnly model for GYM99, both RGB and Flow (#336)
  • Add auto modelzoo statistics in readthedocs (#327)
  • Add TSN for HMDB51 pretrained on Kinetics400, Moments in Time and ImageNet. (#372)

v0.8.0 (31/10/2020)

Highlights

  • Support OmniSource
  • Support C3D
  • Support video recognition with audio modality
  • Support HVU
  • Support X3D

New Features

  • Support AVA dataset preparation (#266)
  • Support the training of video recognition dataset with multiple tag categories (#235)
  • Support joint training with multiple training datasets of multiple formats, including images, untrimmed videos, etc. (#242)
  • Support to specify a start epoch to conduct evaluation (#216)
  • Implement X3D models, support testing with model weights converted from SlowFast (#288)
  • Support specify a start epoch to conduct evaluation (#216)

Improvements

  • Set default values of 'average_clips' in each config file so that there is no need to set it explicitly during testing in most cases (#232)
  • Extend HVU datatools to generate individual file list for each tag category (#258)
  • Support data preparation for Kinetics-600 and Kinetics-700 (#254)
  • Use metric_dict to replace hardcoded arguments in evaluate function (#286)
  • Add cfg-options in arguments to override some settings in the used config for convenience (#212)
  • Rename the old evaluating protocol mean_average_precision as mmit_mean_average_precision since it is only used on MMIT and is not the mAP we usually talk about. Add mean_average_precision, which is the real mAP (#235)
  • Add accurate setting (Three crop * 2 clip) and report corresponding performance for TSM model (#241)
  • Add citations in each preparing_dataset.md in tools/data/dataset (#289)
  • Update the performance of audio-visual fusion on Kinetics-400 (#281)
  • Support data preparation of OmniSource web datasets, including GoogleImage, InsImage, InsVideo and KineticsRawVideo (#294)
  • Use metric_options dict to provide metric args in evaluate (#286)

Bug Fixes

  • Register FrameSelector in PIPELINES (#268)
  • Fix the potential bug for default value in dataset_setting (#245)
  • Fix multi-node dist test (#292)
  • Fix the data preparation bug for something-something dataset (#278)
  • Fix the invalid config url in slowonly README data benchmark (#249)
  • Validate that the performance of models trained with videos have no significant difference comparing to the performance of models trained with rawframes (#256)
  • Correct the img_norm_cfg used by TSN-3seg-R50 UCF-101 model, improve the Top-1 accuracy by 3% (#273)

ModelZoo

  • Add Baselines for Kinetics-600 and Kinetics-700, including TSN-R50-8seg and SlowOnly-R50-8x8 (#259)
  • Add OmniSource benchmark on MiniKineitcs (#296)
  • Add Baselines for HVU, including TSN-R18-8seg on 6 tag categories of HVU (#287)
  • Add X3D models ported from SlowFast (#288)

v0.7.0 (30/9/2020)

Highlights

  • Support TPN
  • Support JHMDB, UCF101-24, HVU dataset preparation
  • support onnx model conversion

New Features

  • Support the data pre-processing pipeline for the HVU Dataset (#277)
  • Support real-time action recognition from web camera (#171)
  • Support onnx (#160)
  • Support UCF101-24 preparation (#219)
  • Support evaluating mAP for ActivityNet with CUHK17_activitynet_pred (#176)
  • Add the data pipeline for ActivityNet, including downloading videos, extracting RGB and Flow frames, finetuning TSN and extracting feature (#190)
  • Support JHMDB preparation (#220)

ModelZoo

  • Add finetuning setting for SlowOnly (#173)
  • Add TSN and SlowOnly models trained with OmniSource, which achieve 75.7% Top-1 with TSN-R50-3seg and 80.4% Top-1 with SlowOnly-R101-8x8 (#215)

Improvements

  • Support demo with video url (#165)
  • Support multi-batch when testing (#184)
  • Add tutorial for adding a new learning rate updater (#181)
  • Add config name in meta info (#183)
  • Remove git hash in __version__ (#189)
  • Check mmcv version (#189)
  • Update url with 'https://download.openmmlab.com' (#208)
  • Update Docker file to support PyTorch 1.6 and update install.md (#209)
  • Polish readsthedocs display (#217, #229)

Bug Fixes

  • Fix the bug when using OpenCV to extract only RGB frames with original shape (#184)
  • Fix the bug of sthv2 num_classes from 339 to 174 (#174, #207)

v0.6.0 (2/9/2020)

Highlights

  • Support TIN, CSN, SSN, NonLocal
  • Support FP16 training

New Features

  • Support NonLocal module and provide ckpt in TSM and I3D (#41)
  • Support SSN (#33, #37, #52, #55)
  • Support CSN (#87)
  • Support TIN (#53)
  • Support HMDB51 dataset preparation (#60)
  • Support encoding videos from frames (#84)
  • Support FP16 training (#25)
  • Enhance demo by supporting rawframe inference (#59), output video/gif (#72)

ModelZoo

  • Update Slowfast modelzoo (#51)
  • Update TSN, TSM video checkpoints (#50)
  • Add data benchmark for TSN (#57)
  • Add data benchmark for SlowOnly (#77)
  • Add BSN/BMN performance results with feature extracted by our codebase (#99)

Improvements

  • Polish data preparation codes (#70)
  • Improve data preparation scripts (#58)
  • Improve unittest coverage and minor fix (#62)
  • Support PyTorch 1.6 in CI (#117)
  • Support with_offset for rawframe dataset (#48)
  • Support json annotation files (#119)
  • Support multi-class in TSMHead (#104)
  • Support using val_step() to validate data for each val workflow (#123)
  • Use xxInit() method to get total_frames and make total_frames a required key (#90)
  • Add paper introduction in model readme (#140)
  • Adjust the directory structure of tools/ and rename some scripts files (#142)

Bug Fixes

  • Fix configs for localization test (#67)
  • Fix configs of SlowOnly by fixing lr to 8 gpus (#136)
  • Fix the bug in analyze_log (#54)
  • Fix the bug of generating HMDB51 class index file (#69)
  • Fix the bug of using load_checkpoint() in ResNet (#93)
  • Fix the bug of --work-dir when using slurm training script (#110)
  • Correct the sthv1/sthv2 rawframes filelist generate command (#71)
  • CosineAnnealing typo (#47)

v0.5.0 (9/7/2020)

Highlights

  • MMAction2 is released

New Features

  • Support various datasets: UCF101, Kinetics-400, Something-Something V1&V2, Moments in Time, Multi-Moments in Time, THUMOS14
  • Support various action recognition methods: TSN, TSM, R(2+1)D, I3D, SlowOnly, SlowFast, Non-local
  • Support various action localization methods: BSN, BMN
  • Colab demo for action recognition