Highlights
- Support LFB
New Features
- Support LFB #553
Improvements
- Add slowfast config/json/log/ckpt for training custom classes of AVA #678
Bug and Typo Fixes
ModelZoo
- Add LFB for AVA2.1 #553
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
andtest_cfg
inmodel
(#629) - Provide an alternative way to download older kinetics annotations (#597)
- Update FAQ for
- 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
ModelZoo
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
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)
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
inOpenCVInit
(#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)
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 inevaluate
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
asmmit_mean_average_precision
since it is only used on MMIT and is not themAP
we usually talk about. Addmean_average_precision
, which is the realmAP
(#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 inevaluate
(#286)
Bug Fixes
- Register
FrameSelector
inPIPELINES
(#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)
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)
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 eachval
workflow (#123) - Use
xxInit()
method to gettotal_frames
and maketotal_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)
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