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MMPose v1.1.0 Release Note
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@Tau-J Tau-J released this 04 Jul 13:35
· 80 commits to main since this release
v1.1.0
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Learn about vigilant mode.

New Datasets

We are glad to support 3 new datasets:

(CVPR 2023) Human-Art

Human-Art is a large-scale dataset that targets multi-scenario human-centric tasks to bridge the gap between natural and artificial scenes.

image

Contents of Human-Art:

  • 50,000 images including human figures in 20 scenarios (5 natural scenarios, 3 2D artificial scenarios, and 12 2D artificial scenarios)
  • Human-centric annotations include human bounding box, 21 2D human keypoints, human self-contact keypoints, and description text
  • baseline human detector and human pose estimator trained on the joint of MSCOCO and Human-Art

Models trained on Human-Art:

Thanks @juxuan27 for helping with the integration of Human-Art!

(CVPR 2022) Animal Kingdom

Animal Kingdom provides multiple annotated tasks to enable a more thorough understanding of natural animal behaviors.

image

Results comparison:

Arch Input Size PCK(0.05) Ours Official Repo Paper
P1_hrnet_w32 256x256 0.6323 0.6342 0.6606
P2_hrnet_w32 256x256 0.3741 0.3726 0.393
P3_mammals_hrnet_w32 256x256 0.571 0.5719 0.6159
P3_amphibians_hrnet_w32 256x256 0.5358 0.5432 0.5674
P3_reptiles_hrnet_w32 256x256 0.51 0.5 0.5606
P3_birds_hrnet_w32 256x256 0.7671 0.7636 0.7735
P3_fishes_hrnet_w32 256x256 0.6406 0.636 0.6825

For more details, see this page

Thanks @Dominic23331 for helping with the integration of Animal Kingdom!

(AAAI 2020) LaPa

Landmark guided face Parsing dataset (LaPa) consists of more than 22,000 facial images with abundant variations in expression, pose and occlusion, and each image of LaPa is provided with an 11-category pixel-level label map and 106-point landmarks.

image

Supported by @Tau-J

New Config Type

MMEngine introduced the pure Python style configuration file:

  • Support navigating to base configuration file in IDE
  • Support navigating to base variable in IDE
  • Support navigating to source code of class in IDE
  • Support inheriting two configuration files containing the same field
  • Load the configuration file without other third-party requirements

Refer to the tutorial for more detailed usages.

image

We provided some examples here. Also, new config type of YOLOX-Pose is supported here.
Feel free to try this new feature and give us your feedback!

Improved RTMPose

We combined public datasets and released more powerful RTMPose models:

  • 17-kpt and 26-kpt body models
  • 21-kpt hand models
  • 106-kpt face models

List of examples to deploy RTMPose:

  • RTMPose-Deploy @HW140701 @Dominic23331
    • RTMPose-Deploy is a C++ code example for RTMPose localized deployment.
  • RTMPose inference with ONNXRuntime (Python) @IRONICBo
    • This example shows how to run RTMPose inference with ONNXRuntime in Python.
  • PoseTracker Android Demo
    • PoseTracker Android Demo Prototype based on mmdeploy.

Check out this page to know more.

Supported by @Tau-J

3D Pose Lifter Refactory

We have migrated SimpleBaseline3D and VideoPose3D into MMPose v1.1.0. Users can easily use Inferencer and body3d demo to conduct inference.

Below is an example of how to use Inferencer to predict 3d pose:

python demo/inferencer_demo.py tests/data/coco/000000000785.jpg \
    --pose3d human3d --vis-out-dir vis_results/human3d \
    --rebase-keypoint-height

image

Video result:

img_v2_45ba54f3-adae-49c7-bf45-07e84d49d21g

Supported by @LareinaM

Inference Speed-up & Webcam Inference

We have made a lot of improvements to our demo scripts:

  • Much higher inference speed
  • OpenCV-backend visualizer
  • All demos support inference with webcam

Take topdown_demo_with_mmdet.py as example, you can conduct inference with webcam by specifying --input webcam:

# inference with webcam
python demo/topdown_demo_with_mmdet.py \
    projects/rtmpose/rtmdet/person/rtmdet_nano_320-8xb32_coco-person.py \
    https://download.openmmlab.com/mmpose/v1/projects/rtmpose/rtmdet_nano_8xb32-100e_coco-obj365-person-05d8511e.pth \
    projects/rtmpose/rtmpose/body_2d_keypoint/rtmpose-m_8xb256-420e_coco-256x192.py \
    https://download.openmmlab.com/mmpose/v1/projects/rtmposev1/rtmpose-m_simcc-aic-coco_pt-aic-coco_420e-256x192-63eb25f7_20230126.pth \
    --input webcam \
    --show

Supported by @Ben-Louis and @LareinaM

New Contributors

Full Changelog: v1.0.0...v1.1.0

Contributors

shuheilocale, xin-li-67, and 17 other contributors
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