Open hellock opened 4 years ago
i hope that MMPose can support 21 hand landmark detetion, thanks
i hope that MMPose can support 21 hand landmark detetion, thanks
Good suggestions! We will add this feature in our TODO list. Thank you.
TODO List (continuously updated... [last edit: 2023.1.14]) : Here is a collection of feature requests. Items that have already been implemented in MMPose will be removed from the list.
More popular backbones
Add more popular datasets:
More 2d human pose estimation method.
More 2d face alignment algorithms.
More 3d human pose algorithms.
Support 2d video pose estimation and tracking
Support Vehicle pose estimation
Add 3D Pose Consistency Benchmark #828
Mano based hand keypoints detection
Depth-based 3d hand pose estimation
Multi-view 3d pose estimation
Support memonger
Support Pytorch AMP training #339
Hyperparameter tuner Optuna
Support Unity plugin
print loss during evaluation. #333
Quantization Aware Training #359
Easier Usage (API)
Export to Torchscript #576
Would you mind add https://github.com/open-mmlab/mmpose/issues/31#issuecomment-663334223 to the TODO list.
Would you mind add #31 (comment) to the TODO list.
Sure.
Speed up inference https://github.com/open-mmlab/mmpose/issues/40
Support video pose estimation #67
Would be great to add support for whole body pose estimation dataset (body+face+hands) via COCO-WholeBody
Also add support for MPII in mmdetection.
It would be great to add support for pose tracking dataset i.e. posetrack2017/2018.
Support to convert pytorch model to onnx by the way.ThxοΌ
@OasisYang could you elaborate? is loading the data and processing on a frame basis is enough, or you want the tracking part also?
@flynnamy sounds like a request for a general tool. maybe we can provide such tools for the whole mm-series (just saying, not a confirmation).
@innerlee If possible, adding both data loading and tracking part would be great. However, the tracking part seems a little bit complicate and always comes with some extra modules. Maybe, the first step is basically to support the data loading and processing. Thanks
@OasisYang could you elaborate? is loading the data and processing on a frame basis is enough, or you want the tracking part also?
@flynnamy sounds like a request for a general tool. maybe we can provide such tools for the whole mm-series (just saying, not a confirmation).
Support ShuffleNet V2 & MobileNet V3 backbones. #94
Support for InterHand2.6
Add Yolov4 and OpenPose
Please make it possible to obtain estimated heatmaps from methods
@hamedcan could you explain more about the usage? do you want a visualizer of heatmaps during training, or a visualization tool for demo, or anything else?
Bottom up for MPII dataset?
@innerlee First, I really want to thank you for the MMPose. It really helped me. I want to compare different models' performance on hard poses. So I need to be able to observe generated heatmaps. I want a visualization tool for demo.
support memonger : https://github.com/Lyken17/pytorch-memonger
Support multi-head networks #219
Please support mpii_trb demo and mpi_inf_3dhp datasets!
Support 3d hand keypoint estimation!!!!!!
Support log info when dataset is tinty, #333
Support PyTorch AMP training, thanks. #339
Support GCN-based methods for refining top-down results. https://arxiv.org/pdf/2003.10506v3.pdf https://github.com/lingtengqiu/OPEC-Net https://arxiv.org/abs/2007.10599
Would be great to see the integration of a hyperparameter tuner like Optuna
A Unity plugin would be amazing to have, using json input data and/or real-time pose estimation with a webcam and seeing it reflected on a 3D model.
@MaxGodTier do you have experience in developing unity plugin? contributions are welcome :D
I don't, but a dirty implementation may be possible using an existing repo , it reads pose data from simple text files each representing a single frame , I see two solutions: (1) If pose_results from mmpose were translated into the same format expected from that repo, it will work out of the box without needing to change a single line of code or (2) edit the repo code (C#) to use mmpose rules instead of theirs.
Quantization Aware Training for models to get the int8 models ,int8 models will greatly improve inference speed #359,thanks
Support DetTrack and KeyTrack. http://arxiv.org/abs/2003.13743 & https://arxiv.org/abs/1912.02323
Albumentations augmetnations similar to mmclassification
i hope that MMPose can support 3D hand landmarks detetion, thanks
Does MMPose support Single Person Pose Estimation? Currently I found only multi-person versions are supported.
@rhiver single is a case of multi
@rhiver single is a case of multi
Sort of. But multi-person version has two stages, person detection and pose estimation, which have to infer on two models. So this method doesn't work for realtime pose estimation in mobile devices since it takes too long on the inference. MobileNetV2 is good enough for simple pose estimation. But for best FPS, it's better to let it do both single person detection and pose estimation.
I see it has supported heatmap method of face datasets now. Please support regression method of face dataset!
I see it has supported heatmap method of face datasets now. Please support regression method of face dataset!
Do you have any recommended papers/codes ?
I see it has supported heatmap method of face datasets now. Please support regression method of face dataset!
Do you have any recommended papers/codes ?
Yes,wingloss:https://arxiv.org/pdf/1711.06753.pdf, and GCN+softwing loss: https://arxiv.org/pdf/2006.11697.pdf
Support FashionAI https://tianchi.aliyun.com/competition/entrance/231648/introduction
I want to use mmpose with the pypi package much more easily than now; such as:
from mmpose import top_down
top_down("darkpose", "COCO_wholebody", video_path="hoge.mp4", output_json_title="hoge") # Analyze hoge.mp4 with COCO wholebody on darkpose and output the result as hoge/hoge000000000000.json, hoge/hoge000000000001.json, hoge/hoge000000000002.json, ....
MPII multi-person dataset for bottom-up methods is really needed!
hi ,can you add handlandmark filtering algorithm for eliminating handlandmark jittering in videos? thanks
Adding Vehicle pose estimation to the pipe line using CarFusion dataset. Similar to Occlusion-net, and Apollocar3D.
Export to Torchscript !
Lite-HRNet, its already built with mmpose, so including into the main repo should be super simple. Would be amazing if it could work with the pytorch2onnx tool for deployment
Please support Halpe data set: https://github.com/Fang-Haoshu/Halpe-FullBody
It has 3 useful points in addition to the COCO-WholeBody.
Hi everyone,
I intend to create my own keypoints dataset with 3 points of interest (two endpoints and one center point). Can anyone kindly help me on how I can create annotations to be loaded into mmpose? Because I believe that the repo is based on mmcv, how can I get my own dataloader? Any help in this regard will be highly appreciated. Thank you
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