Comments (4)
You can refer to this: https://github.com/mks0601/3DMPPE_POSENET_RELEASE#quick-demo
Yes. you should extract all frames.
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Thanks for your reply. Actually I tried the quick-demo you mentioned, but when I changed the input image you supplied to my own image, the output 3d keypoints were wrong. The skeleton and the person did not overlap at all.
Is this because the corresponding bbox and root depth are required to input each picture?Does that mean if I want to inference a video, I have to get the bbox and root depth of all frames?
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As described in that link, you should set bbox and root depth for each image.
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Well, I got it! Thanks a lot!
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Related Issues (20)
- Keypoints probability HOT 3
- 2.6Mdatasets
- Human3.6M
- Run environment and video tests.
- Run my own img on demo.py HOT 4
- something about bbox_list HOT 2
- something about dataset HOT 2
- Some extended problems
- about h36m parsing. HOT 1
- Problems with Reproduced Papers HOT 12
- Problem when visualize on MuPoTS using bbox_root provided by RootNet
- Change resnet type HOT 5
- Question regarding bbox and rootNet HOT 2
- Extracting human36 parsed images HOT 12
- PoseNet HOT 9
- about human36 data File name format HOT 6
- other public datasets,overfitting issue HOT 6
- about datasets Human3.6m HOT 3
- Question about pretrained model used in demo. HOT 2
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