jyunlee / interhandgen Goto Github PK

Thanks for your work, I'm getting the following error with Network Inference.

Dear authors, thank you for releasing the code.

Could you elaborate on which checkpoint corresponds to the released model?
I've tried all four released files, however none of them seems to be compatible with the model.
python interhandgen.py --model_path Im2Hands/ref_occ.pt
python interhandgen.py --model_path Im2Hands/init_occ.pt
python interhandgen.py --model_path Im2Hands/intaghand_baseline.pth
python interhandgen.py --model_path Im2Hands/halo_baseline.pt

Thanks for your code, when I run interhand.py I get a dimension mismatch, theoretically, there shouldn't be this error, how to fix it please, thanks!

ERROR - interhandgen.py - 2024-04-02 00:09:05,236 - Traceback (most recent call last):
File "/mnt/e/Lwork/two-hand/Code/InterHandGen/interhandgen.py", line 147, in main
runner.train()
File "/mnt/e/Lwork/two-hand/Code/InterHandGen/runners/diffhand.py", line 367, in train
data, gt_anchor_verts, gt_add_verts, gt_anchor_joints, gt_add_joints, anc_valid, add_valid = self.mano_forward_gt(data)
File "/mnt/e/Lwork/two-hand/Code/InterHandGen/runners/diffhand.py", line 272, in mano_forward_gt
add_handV = add_handV - add_handJ[:, 9, :].unsqueeze(1) + rel_trans.unsqueeze(1)
RuntimeError: The size of tensor a (778) must match the size of tensor b (3) at non-singleton dimension 1

What is the version of Python you used? I got a dependency error for Python 3.10, 3.9. 3.8.

Thank you for sharing the great work! I have a question regarding the training setup:
What GPUs did you use for training the model? How much GPU memory is required to train the model?
Thank you for your time! Best regards.

It seems that there is an error in the calculation of the penetration volume metric. When directly inferring with the official pre-trained model you provided, the penetration volume metric yields 0. Could you please offer some guidance or suggestions on this matter?

Hi, @jyunlee! Thank you for sharing your code. I'm trying to use the ARCTIC dataset for your code, and have some questions.

• How can you get the object point cloud? (I mean, how can you generate the object point cloud?)
• Do you have any plans to release the code regarding Object-conditional generation?

Hi, @jyunlee! Thank you for sharing your code. I'm trying to use the ARCTIC dataset to visualize hand-object interactions through the differentiable manolayer (https://github.com/hassony2/manopth/blob/master/manopth/manolayer.py), but now I'm encountering some issues. I've noticed that you also use Manolayer, so I'd like to ask for your advice.

I am using the data from arctic_data/data/raw_seqs(https://github.com/zc-alexfan/arctic/blob/master/docs/data/README.md) and extracting hand and object parameters to visualize through manopth, but the hand is always displayed abnormally, and at the same time, the hand and object are intermingling.

I have been troubled by this question for a long time. I would like to know how you use manolayer to visualize data from ARCTIC ( and which part of the dataset) .or Is it feasible to directly use the manolayer you have written(https://github.com/jyunlee/InterHandGen/blob/main/utils/manolayer.py)?