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Visualize about interhand2.6m HOT 7 OPEN

facebookresearch avatar facebookresearch commented on September 28, 2024
Visualize

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Comments (7)

mks0601 avatar mks0601 commented on September 28, 2024
  1. Read https://github.com/facebookresearch/InterHand2.6M#test
  2. Set vis=True in here and here.
  3. Run test.

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liwenssss avatar liwenssss commented on September 28, 2024

When I use your visualize demo to show the 3d joints, I find the position of the right hand and left hand is opposite, how to set it to show the position in the right position?

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mks0601 avatar mks0601 commented on September 28, 2024

Hmm could you give me some examples of the opposite results?

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liwenssss avatar liwenssss commented on September 28, 2024

Hmm could you give me some examples of the opposite results?

the rgb image is like this:
image

but the corresponding visualized 3d joint is like this:
image

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mks0601 avatar mks0601 commented on September 28, 2024

This is because I subtract the root joint position at here for the evaluation.

The code makes the two hand 3D coordinates have the same (0,0,0) root joint (wrist) position.
For the visualization, you may want to visualize the 3D hand pose before subtracting the root joint position.

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chenyanyin avatar chenyanyin commented on September 28, 2024

Hmm could you give me some examples of the opposite results?

the rgb image is like this:
image

but the corresponding visualized 3d joint is like this:
image

have you got bbox and abs_depth by rootnet? in other words, i have to inference rootNet and InterNet for get hand-3D results when i test one image not STB/RHD/InterHand2.6M datasets, the image just got for my cam. @liwenssss @mks0601 Thanks!

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mks0601 avatar mks0601 commented on September 28, 2024

I used GT bbox for the training and testing, as described in the paper.
For the RootNet, actually, you can just visualize pred_joint_coord_img right after here without adding the results of RootNet (abs_depth).
x and y coordinates of pred_joint_coord_img are in image space, and z coordinate is in the voxelized heatmap space, not mm. However, it will look very similar, so you can just use it.

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