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ChanglongJiangGit / A2J-Transformer

[CVPR 2023] Code for paper 'A2J-Transformer: Anchor-to-Joint Transformer Network for 3D Interacting Hand Pose Estimation from a Single RGB Image'
Apache License 2.0
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Tested on a subset of InterHand2.6M (38959 images), but I got MPJPE=118.32 #18

Closed Mayo001 closed 11 months ago

Mayo001 commented 11 months ago

Hi! Thanks for your code.

Due to my limited GPU resources, I tested on a subset of the InterHand 2.6M dataset (part aa).
but I got the result of MPJPE=118.32, I guess there are some mistakes in my operation. Could you please direct me what should I change in the code. By the way, I noticed that you are Chinese, if it's convenient, we can communicate in Chinese!

Thank you again!

self.datalist = self.datalist_sh + self.datalist_ih
valid_datalist = []    
for data in tqdm(self.datalist):     
    img_path = data['img_path']
    if osp.exists(img_path):       # Only 'InterHand2.6M.images.5.fps.v1.0.tar.partaa'.
        valid_datalist.append(data)
self.datalist = valid_datalist[:]         
print('Number of annotations in single hand sequences: ' + str(len(self.datalist_sh)))
print('Number of annotations in interacting hand sequences: ' + str(len(self.datalist_ih)))

3091696912136_ pic