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Changelog

v0.29.0 (14/10/2022)

Highlights

  • Support DEKR, CVPR’2021 (#1693) @JinluZhang1126, @jin-s13, @Ben-Louis

  • Support CID, CVPR’2022 (#1604) @kennethwdk, @jin-s13, @Ben-Louis

Improvements

  • Improve 3D pose estimation demo with viewpoint & height controlling and enriched input formats (#1481, #1490) @pallgeuer, @liqikai9

  • Improve smoothing of 3D video pose estimation (#1479) @darcula1993

  • Improve dependency management for smoother installation (#1491) @danielbraun89

  • Improve documentation quality (#1680, #1525, #1516, #1513, #1511, #1507, #1506, #1525) @Ben-Louis, @Yulv-git, @jin-s13

Bug Fixes

  • Update dependency versions of pre-commit-hooks (#1706, #1678) @Ben-Louis, @liqikai9

  • Fix missing data transforms in RLE configs (#1632) @Ben-Louis

  • Fix a bug in fliplr_joints that causes error when keypoint visibility has float values (#1589) @walsvid

  • Fix hsigmoid default parameters (#1575) @Ben-Louis

  • Fix a bug in UDP decoding (#1565) @liqikai9

  • Fix a bug in pose tracking demo with non-COCO dataset (#1504) @daixinghome

  • Fix typos and unused contents in configs (#1499, #1496) @liqikai9

  • Fix a bug in the mesh demo (#1482) @zengwang430521

v0.28.1 (28/07/2022)

This release is meant to fix the compatibility with the latest mmcv v1.6.1

v0.28.0 (06/07/2022)

Highlights

  • Support TCFormer backbone, CVPR’2022 (#1447, #1452) @zengwang430521

  • Add RLE models on COCO dataset (#1424) @Indigo6, @Ben-Louis, @ly015

  • Update swin models with better performance (#1467) @jin-s13

New Features

  • Support TCFormer backbone, CVPR’2022 (#1447, #1452) @zengwang430521

  • Add RLE models on COCO dataset (#1424) @Indigo6, @Ben-Louis, @ly015

  • Support layer decay optimizer conctructor and learning rate decay optimizer constructor (#1423) @jin-s13

Improvements

  • Improve documentation quality (#1416, #1421, #1423, #1426, #1458, #1463) @ly015, @liqikai9

  • Support installation by mim (#1425) @liqikai9

  • Support PAVI logger (#1434) @EvelynWang-0423

  • Add progress bar for some demos (#1454) @liqikai9

  • Webcam API supports quick device setting in terminal commands (#1466) @ly015

  • Update swin models with better performance (#1467) @jin-s13

Bug Fixes

  • Rename custom_hooks_config to custom_hooks in configs to align with the documentation (#1427) @ly015

  • Fix deadlock issue in Webcam API (#1430) @ly015

  • Fix smoother configs in video 3D demo (#1457) @ly015

v0.27.0 (07/06/2022)

Highlights

New Features

  • Support gesture recognition algorithm MTUT CVPR’2019 and dataset NVGesture CVPR’2016 (#1380) @Ben-Louis

Improvements

  • Upgrade Webcam API and related documents (#1393, #1404, #1413) @ly015

  • Support exporting COCO inference result without the annotation file (#1368) @liqikai9

  • Replace markdownlint with mdformat in CI to avoid the dependence on ruby #1382 @ly015

  • Improve documentation quality (#1385, #1394, #1395, #1408) @chubei-oppen, @ly015, @liqikai9

Bug Fixes

  • Fix xywh->xyxy bbox conversion in dataset sanity check (#1367) @jin-s13

  • Fix a bug in two-stage 3D keypoint demo (#1373) @ly015

  • Fix out-dated settings in PVT configs (#1376) @ly015

  • Fix myst settings for document compiling (#1381) @ly015

  • Fix a bug in bbox transform (#1384) @ly015

  • Fix inaccurate description of min_keypoints in tracking apis (#1398) @pallgeuer

  • Fix warning with torch.meshgrid (#1402) @pallgeuer

  • Remove redundant transformer modules from mmpose.datasets.backbones.utils (#1405) @ly015

v0.26.0 (05/05/2022)

Highlights

New Features

Improvements

  • Speed up inference and reduce CPU usage by optimizing the pre-processing pipeline (#1320) @chenxinfeng4, @liqikai9

  • Video demo supports models that requires multi-frame inputs (#1300) @liqikai9, @jin-s13

  • Update benchmark regression list (#1328) @ly015, @liqikai9

  • Remove unnecessary warnings in TopDownPoseTrack18VideoDataset (#1335) @liqikai9

  • Improve documentation quality (#1313, #1305) @Ben-Louis, @ly015

  • Update deprecating settings in configs (#1317) @ly015

Bug Fixes

  • Fix a bug in human skeleton grouping that may skip the matching process unexpectedly when ignore_to_much is True (#1341) @daixinghome

  • Fix a GPG key error that leads to CI failure (#1354) @ly015

  • Fix bugs in distributed training script (#1338, #1298) @ly015

  • Fix an upstream bug in xtoccotools that causes incorrect AP(M) results (#1308) @jin-s13, @ly015

  • Fix indentiation errors in the colab tutorial (#1298) @YuanZi1501040205

  • Fix incompatible model weight initialization with other OpenMMLab codebases (#1329) @274869388

  • Fix HRNet FP16 checkpoints download URL (#1309) @YinAoXiong

  • Fix typos in body3d_two_stage_video_demo.py (#1295) @mucozcan

Breaking Changes

  • Refactor bbox processing in datasets and pipelines (#1311) @ly015, @Ben-Louis The bbox format conversion (xywh to center-scale) and random translation are moved from the dataset to the pipeline. The comparison between new and old version is as below:

v0.26.0 v0.25.0
Dataset
(e.g. TopDownCOCODataset) 
...
# Data sample only contains bbox
rec.append({
    'bbox': obj['clean_bbox][:4],
    ...
})

...
# Convert bbox from xywh to center-scale
center, scale = self._xywh2cs(*obj['clean_bbox'][:4])
# Data sample contains center and scale
rec.append({
    'bbox': obj['clean_bbox][:4],
    'center': center,
    'scale': scale,
    ...
})
Pipeline Config
(e.g. HRNet+COCO)		 
...
train_pipeline = [
    dict(type='LoadImageFromFile'),
    # Convert bbox from xywh to center-scale
    dict(type='TopDownGetBboxCenterScale', padding=1.25),
    # Randomly shift bbox center
    dict(type='TopDownRandomShiftBboxCenter', shift_factor=0.16, prob=0.3),
    ...
]

...
train_pipeline = [
    dict(type='LoadImageFromFile'),
    ...
]
Advantage
  • Simpler data sample content
  • Flexible bbox format conversion and augmentation
  • Apply bbox random translation every epoch (instead of only applying once at the annotation loading)
    		• -
    BC Breaking The method _xywh2cs of dataset base classes (e.g. Kpt2dSviewRgbImgTopDownDataset) will be deprecated in the future. Custom datasets will need modifications to move the bbox format conversion to pipelines. -

    v0.25.0 (02/04/2022)

    Highlights

    New Features

    Improvements

    • Update HRFormer configs and checkpoints with relative position bias (#1245) @zengwang430521

    • Support using different random seed for each distributed node (#1257, #1229) @ly015

    • Improve documentation quality (#1275, #1255, #1258, #1249, #1247, #1240, #1235) @ly015, @jin-s13, @YoniChechik

    Bug Fixes

    • Fix keypoint index in RHD dataset meta information (#1265) @liqikai9

    • Fix pre-commit hook unexpected behavior on Windows (#1282) @liqikai9

    • Remove python-dev installation in CI (#1276) @ly015

    • Unify hyphens in argument names in tools and demos (#1271) @ly015

    • Fix ambiguous channel size in channel_shuffle that may cause exporting failure (#1242) @PINTO0309

    • Fix a bug in Webcam API that causes single-class detectors fail (#1239) @674106399

    • Fix the issue that custom_hook can not be set in configs (#1236) @bladrome

    • Fix incompatible MMCV version in DockerFile (#raykindle)

    • Skip invisible joints in visualization (#1228) @womeier

    v0.24.0 (07/03/2022)

    Highlights

    New Features

    Improvements

    • Refactor multi-view 3D pose estimation framework towards better modularization and expansibility (#1196) @wusize

    • Add WebcamAPI documents and tutorials (#1187) @ly015

    • Refactor dataset evaluation interface to align with other OpenMMLab codebases (#1209) @ly015

    • Add deprecation message for deploy tools since MMDeploy has supported MMPose (#1207) @QwQ2000

    • Improve documentation quality (#1206, #1161) @ly015

    • Switch to OpenMMLab official pre-commit-hook for copyright check (#1214) @ly015

    Bug Fixes

    • Fix hard-coded data collating and scattering in inference (#1175) @ly015

    • Fix model configs on JHMDB dataset (#1188) @jin-s13

    • Fix area calculation in pose tracking inference (#1197) @pallgeuer

    • Fix registry scope conflict of module wrapper (#1204) @ly015

    • Update MMCV installation in CI and documents (#1205)

    • Fix incorrect color channel order in visualization functions (#1212) @ly015

    v0.23.0 (11/02/2022)

    Highlights

    New Features

    • Add MMPose Webcam API: A simple yet powerful tools to develop interactive webcam applications with MMPose functions. (#1178, #1173, #1173, #1143, #1094, #1133, #1098, #1160) @ly015, @jin-s13, @liqikai9, @wusize, @luminxu, @zengwang430521 @mzr1996

    • Support ConcatDataset (#1139) @Canwang-sjtu

    • Support CPU training and testing (#1157) @ly015

    Improvements

    • Add multi-processing configurations to speed up distributed training and testing (#1146) @ly015

    • Add default runtime config (#1145)

    • Upgrade isort in pre-commit hook (#1179) @liqikai9

    • Update README and documents (#1171, #1167, #1153, #1149, #1148, #1147, #1140) @jin-s13, @wusize, @TommyZihao, @ly015

    Bug Fixes

    • Fix undeterministic behavior in pre-commit hooks (#1136) @jin-s13

    • Deprecate the support for “python setup.py test” (#1179) @ly015

    • Fix incompatible settings with MMCV on HSigmoid default parameters (#1132) @ly015

    • Fix albumentation installation (#1184) @BIGWangYuDong

    v0.22.0 (04/01/2022)

    Highlights

    New Features

    Improvements

    Bug Fixes

    • Fix a bug in Dark UDP postprocessing that causes error when the channel number is large. (#1079, #1116) @X00123, @jin-s13

    • Fix hard-coded sigmas in bottom-up image demo (#1107, #1101) @chenxinfeng4, @liqikai9

    • Fix unstable checks in unit tests (#1112) @ly015

    • Do not destroy NULL windows if args.show==False in demo scripts (#1104) @bladrome

    v0.21.0 (06/12/2021)

    Highlights

    New Features

    Improvements

    Bug Fixes

    • Update pose tracking demo to be compatible with latest mmtracking (#1014) @jin-s13

    • Fix symlink creation failure when installed in Windows environments (#1039) @QwQ2000

    • Fix AP-10K dataset sigmas (#1040) @jin-s13

    v0.20.0 (01/11/2021)

    Highlights

    • Add AP-10K dataset for animal pose estimation (#987) @Annbless, @AlexTheBad, @jin-s13, @ly015

    • Support TorchServe (#979) @ly015

    New Features

    • Add AP-10K dataset for animal pose estimation (#987) @Annbless, @AlexTheBad, @jin-s13, @ly015

    • Add HRNetv2 checkpoints on 300W and COFW datasets (#980) @jin-s13

    • Support TorchServe (#979) @ly015

    Bug Fixes

    • Fix some deprecated or risky settings in configs (#963, #976, #992) @jin-s13, @wusize

    • Fix issues of default arguments of training and testing scripts (#970, #985) @liqikai9, @wusize

    • Fix heatmap and tag size mismatch in bottom-up with UDP (#994) @wusize

    • Fix python3.9 installation in CI (#983) @ly015

    • Fix model zoo document integrity issue (#990) @jin-s13

    Improvements

    • Support non-square input shape for bottom-up (#991) @wusize

    • Add image and video resources for demo (#971) @liqikai9

    • Use CUDA docker images to accelerate CI (#973) @ly015

    • Add codespell hook and fix detected typos (#977) @ly015

    v0.19.0 (08/10/2021)

    Highlights

    • Add models for Associative Embedding with Hourglass network backbone (#906, #955) @jin-s13, @luminxu

    • Support COCO-Wholebody-Face and COCO-Wholebody-Hand datasets (#813) @jin-s13, @innerlee, @luminxu

    • Upgrade dataset interface (#901, #924) @jin-s13, @innerlee, @ly015, @liqikai9

    • New style of documentation (#945) @ly015

    New Features

    • Add models for Associative Embedding with Hourglass network backbone (#906, #955) @jin-s13, @luminxu

    • Support COCO-Wholebody-Face and COCO-Wholebody-Hand datasets (#813) @jin-s13, @innerlee, @luminxu

    • Add pseudo-labeling tool to generate COCO style keypoint annotations with given bounding boxes (#928) @soltkreig

    • New style of documentation (#945) @ly015

    Bug Fixes

    • Fix segmentation parsing in Macaque dataset preprocessing (#948) @jin-s13

    • Fix dependencies that may lead to CI failure in downstream projects (#936, #953) @RangiLyu, @ly015

    • Fix keypoint order in Human3.6M dataset (#940) @ttxskk

    • Fix unstable image loading for Interhand2.6M (#913) @zengwang430521

    Improvements

    • Upgrade dataset interface (#901, #924) @jin-s13, @innerlee, @ly015, @liqikai9

    • Improve demo usability and stability (#908, #934) @ly015

    • Standardize model metafile format (#941) @ly015

    • Support persistent_worker and several other arguments in configs (#946) @jin-s13

    • Use MMCV root model registry to enable cross-project module building (#935) @RangiLyu

    • Improve the document quality (#916, #909, #942, #913, #956) @jin-s13, @ly015, @bit-scientist, @zengwang430521

    • Improve pull request template (#952, #954) @ly015

    Breaking Changes

    • Upgrade dataset interface (#901) @jin-s13, @innerlee, @ly015

    v0.18.0 (01/09/2021)

    Bug Fixes

    • Fix redundant model weight loading in pytorch-to-onnx conversion (#850) @ly015

    • Fix a bug in update_model_index.py that may cause pre-commit hook failure(#866) @ly015

    • Fix a bug in interhand_3d_head (#890) @zengwang430521

    • Fix pose tracking demo failure caused by out-of-date configs (#891)

    Improvements

    • Add automatic benchmark regression tools (#849, #880, #885) @liqikai9, @ly015

    • Add copyright information and checking hook (#872)

    • Add PR template (#875) @ly015

    • Add citation information (#876) @ly015

    • Add python3.9 in CI (#877, #883) @ly015

    • Improve the quality of the documents (#845, #845, #848, #867, #870, #873, #896) @jin-s13, @ly015, @zhiqwang

    v0.17.0 (06/08/2021)

    Highlights

    1. Support “Lite-HRNet: A Lightweight High-Resolution Network” CVPR’2021 (#733,#800) @jin-s13

    2. Add 3d body mesh demo (#771) @zengwang430521

    3. Add Chinese documentation (#787, #798, #799, #802, #804, #805, #815, #816, #817, #819, #839) @ly015, @luminxu, @jin-s13, @liqikai9, @zengwang430521

    4. Add Colab Tutorial (#834) @ly015

    New Features

    Bug Fixes

    • Fix mpii pckh@0.1 index (#773) @jin-s13

    • Fix multi-node distributed test (#818) @ly015

    • Fix docstring and init_weights error of ShuffleNetV1 (#814) @Junjun2016

    • Fix imshow_bbox error when input bboxes is empty (#796) @ly015

    • Fix model zoo doc generation (#778) @ly015

    • Fix typo (#767), (#780, #782) @ly015, @jin-s13

    Breaking Changes

    • Use MMCV EvalHook (#686) @ly015

    Improvements

    • Add pytest.ini and fix docstring (#812) @jin-s13

    • Update MSELoss (#829) @Ezra-Yu

    • Move process_mmdet_results into inference.py (#831) @ly015

    • Update resource limit (#783) @jin-s13

    • Use COCO 2D pose model in 3D demo examples (#785) @ly015

    • Change model zoo titles in the doc from center-aligned to left-aligned (#792, #797) @ly015

    • Support MIM (#706, #794) @ly015

    • Update out-of-date configs (#827) @jin-s13

    • Remove opencv-python-headless dependency by albumentations (#833) @ly015

    • Update QQ QR code in README_CN.md (#832) @ly015

    v0.16.0 (02/07/2021)

    Highlights

    1. Support “ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search” CVPR’2021 (#742,#755).

    2. Support MPI-INF-3DHP dataset (#683,#746,#751).

    3. Add webcam demo tool (#729)

    4. Add 3d body and hand pose estimation demo (#704, #727).

    New Features

    Bug Fixes

    Breaking Changes

    • Switch to MMCV MODEL_REGISTRY (#669)

    Improvements

    • Refactor MeshMixDataset (#752)

    • Rename ‘GaussianHeatMap’ to ‘GaussianHeatmap’ (#745)

    • Update out-of-date configs (#734)

    • Improve compatibility for breaking changes (#731)

    • Enable to control radius and thickness in visualization (#722)

    • Add regex dependency (#720)

    v0.15.0 (02/06/2021)

    Highlights

    1. Support 3d video pose estimation (VideoPose3D).

    2. Support 3d hand pose estimation (InterNet).

    3. Improve presentation of modelzoo.

    New Features

    • Support “InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Image” (ECCV‘20) (#624)

    • Support “3D human pose estimation in video with temporal convolutions and semi-supervised training” (CVPR’19) (#602, #681)

    • Support 3d pose estimation demo (#653, #670)

    • Support bottom-up whole-body pose estimation (#689)

    • Support mmcli (#634)

    Bug Fixes

    Breaking Changes

    • Reorganize configs by tasks, algorithms, datasets, and techniques (#647)

    • Rename heads and detectors (#667)

    Improvements

    • Add radius and thickness parameters in visualization (#638)

    • Add trans_prob parameter in TopDownRandomTranslation (#650)

    • Switch to MMCV MODEL_REGISTRY (#669)

    • Update dependencies (#674, #676)

    v0.14.0 (06/05/2021)

    Highlights

    1. Support animal pose estimation with 7 popular datasets.

    2. Support “A simple yet effective baseline for 3d human pose estimation” (ICCV’17).

    New Features

    • Support “A simple yet effective baseline for 3d human pose estimation” (ICCV’17) (#554,#558,#566,#570,#589)

    • Support animal pose estimation (#559,#561,#563,#571,#603,#605)

    • Support Horse-10 dataset (#561), MacaquePose dataset (#561), Vinegar Fly dataset (#561), Desert Locust dataset (#561), Grevy’s Zebra dataset (#561), ATRW dataset (#571), and Animal-Pose dataset (#603)

    • Support bottom-up pose tracking demo (#574)

    • Support FP16 training (#584,#616,#626)

    • Support NMS for bottom-up (#609)

    Bug Fixes

    • Fix bugs in the top-down demo, when there are no people in the images (#569).

    • Fix the links in the doc (#612)

    Improvements

    v0.13.0 (31/03/2021)

    Highlights

    1. Support Wingloss.

    2. Support RHD hand dataset.

    New Features

    • Support Wingloss (#482)

    • Support RHD hand dataset (#523, #551)

    • Support Human3.6m dataset for 3d keypoint detection (#518, #527)

    • Support TCN model for 3d keypoint detection (#521, #522)

    • Support Interhand3D model for 3d hand detection (#536)

    • Support Multi-task detector (#480)

    Bug Fixes

    • Fix PCKh@0.1 calculation (#516)

    • Fix unittest (#529)

    • Fix circular importing (#542)

    • Fix bugs in bottom-up keypoint score (#548)

    Improvements

    v0.12.0 (28/02/2021)

    Highlights

    1. Support DeepPose algorithm.

    New Features

    • Support DeepPose algorithm (#446, #461)

    • Support interhand3d dataset (#468)

    • Support Albumentation pipeline (#469)

    • Support PhotometricDistortion pipeline (#485)

    • Set seed option for training (#493)

    • Add demos for face keypoint detection (#502)

    Bug Fixes

    • Change channel order according to configs (#504)

    • Fix num_factors in UDP encoding (#495)

    • Fix configs (#456)

    Breaking Changes

    • Refactor configs for wholebody pose estimation (#487, #491)

    • Rename decode function for heads (#481)

    Improvements

    v0.11.0 (31/01/2021)

    Highlights

    1. Support fashion landmark detection.

    2. Support face keypoint detection.

    3. Support pose tracking with MMTracking.

    New Features

    • Support fashion landmark detection (DeepFashion) (#413)

    • Support face keypoint detection (300W, AFLW, COFW, WFLW) (#367)

    • Support pose tracking demo with MMTracking (#427)

    • Support face demo (#443)

    • Support AIC dataset for bottom-up methods (#438, #449)

    Bug Fixes

    • Fix multi-batch training (#434)

    • Fix sigmas in AIC dataset (#441)

    • Fix config file (#420)

    Breaking Changes

    • Refactor Heads (#382)

    Improvements

    v0.10.0 (31/12/2020)

    Highlights

    1. Support more human pose estimation methods.

    2. Support pose tracking.

    3. Support multi-batch inference.

    4. Add some useful tools, including analyze_logs, get_flops, print_config.

    5. Support more backbone networks.

    New Features

    • Support UDP (#353, #371, #402)

    • Support multi-batch inference (#390)

    • Support MHP dataset (#386)

    • Support pose tracking demo (#380)

    • Support mpii-trb demo (#372)

    • Support mobilenet for hand pose estimation (#377)

    • Support ResNest backbone (#370)

    • Support VGG backbone (#370)

    • Add some useful tools, including analyze_logs, get_flops, print_config (#324)

    Bug Fixes

    • Fix bugs in pck evaluation (#328)

    • Fix model download links in README (#396, #397)

    • Fix CrowdPose annotations and update benchmarks (#384)

    • Fix modelzoo stat (#354, #360, #362)

    • Fix config files for aic datasets (#340)

    Breaking Changes

    • Rename image_thr to det_bbox_thr for top-down methods.

    Improvements

    • Organize the readme files (#398, #399, #400)

    • Check linting for markdown (#379)

    • Add faq.md (#350)

    • Remove PyTorch 1.4 in CI (#338)

    • Add pypi badge in readme (#329)

    v0.9.0 (30/11/2020)

    Highlights

    1. Support more human pose estimation methods.

    2. Support video pose estimation datasets.

    3. Support Onnx model conversion.

    New Features

    • Support MSPN (#278)

    • Support RSN (#221, #318)

    • Support new post-processing method for MSPN & RSN (#288)

    • Support sub-JHMDB dataset (#292)

    • Support urls for pre-trained models in config files (#232)

    • Support Onnx (#305)

    Bug Fixes

    • Fix model download links in README (#255, #315)

    Breaking Changes

    • post_process=True|False and unbiased_decoding=True|False are deprecated, use post_process=None|default|unbiased etc. instead (#288)

    Improvements

    v0.8.0 (31/10/2020)

    Highlights

    1. Support more human pose estimation datasets.

    2. Support more 2D hand keypoint estimation datasets.

    3. Support adversarial training for 3D human shape recovery.

    4. Support multi-stage losses.

    5. Support mpii demo.

    New Features

    Bug Fixes

    • Fix config files (#190)

    Improvements

    • Add mpii demo (#216)

    • Improve README (#181, #183, #208)

    • Support return heatmaps and backbone features (#196, #212)

    • Support different return formats of mmdetection models (#217)

    v0.7.0 (30/9/2020)

    Highlights

    1. Support HMR for 3D human shape recovery.

    2. Support WholeBody human pose estimation.

    3. Support more 2D hand keypoint estimation datasets.

    4. Add more popular backbones & enrich the modelzoo

      • ShuffleNetv2

    5. Support hand demo and whole-body demo.

    New Features

    Bug Fixes

    • Fix typos in docs (#121)

    • Fix assertion (#142)

    Improvements

    • Add tools to transform .mat format to .json format (#126)

    • Add hand demo (#115)

    • Add whole-body demo (#163)

    • Reuse mmcv utility function and update version files (#135, #137)

    • Enrich the modelzoo (#147, #169)

    • Improve docs (#174, #175, #178)

    • Improve README (#176)

    • Improve version.py (#173)

    v0.6.0 (31/8/2020)

    Highlights

    1. Add more popular backbones & enrich the modelzoo

      • ResNext

      • SEResNet

      • ResNetV1D

      • MobileNetv2

      • ShuffleNetv1

      • CPM (Convolutional Pose Machine)

    2. Add more popular datasets:

    3. Support 2d hand keypoint estimation.

    4. Support bottom-up inference.

    New Features

    Bug Fixes

    • Fix configs for MPII & MPII-TRB datasets (#93)

    • Fix the bug of missing test_pipeline in configs (#14)

    • Fix typos (#27, #28, #50, #53, #63)

    Improvements

    • Update benchmark (#93)

    • Add Dockerfile (#44)

    • Improve unittest coverage and minor fix (#18)

    • Support CPUs for train/val/demo (#34)

    • Support bottom-up demo (#69)

    • Add tools to publish model (#62)

    • Enrich the modelzoo (#64, #68, #82)

    v0.5.0 (21/7/2020)

    Highlights

    • MMPose is released.

    Main Features

    • Support both top-down and bottom-up pose estimation approaches.

    • Achieve higher training efficiency and higher accuracy than other popular codebases (e.g. AlphaPose, HRNet)

    • Support various backbone models: ResNet, HRNet, SCNet, Houglass and HigherHRNet.

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