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HuangJunJie2017 avatar HuangJunJie2017 commented on August 17, 2024

where did you down load the model~ we provide the models trained with udp here
image

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azuryl avatar azuryl commented on August 17, 2024

I had download your model and updated the w32_256x192_adam_lr1e-3.yaml from Hrnet
but there is error
python inference.py --cfg ../experiments/coco/hrnet/w32_256x192_adam_lr1e-3.yaml --videoFile ../../../Alexander\ Zverev\ vs\ Dominic\ Thiem\ -\ US\ Open\ 2020\ Final.mp4 --writeBoxFrames --outputDir output TEST.MODEL_FILE UDP-hrnet_w32_256x192.pth
=> loading model from UDP-hrnet_w32_256x192.pth
Traceback (most recent call last):
File "inference.py", line 341, in
main()
File "inference.py", line 226, in main
pose_model.load_state_dict(torch.load(cfg.TEST.MODEL_FILE), strict=False)
File "/home/azuryl/anaconda3/envs/udppose/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1044, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for PoseHighResolutionNet:
size mismatch for final_layer.weight: copying a param with shape torch.Size([51, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([17, 128, 1, 1]).
size mismatch for final_layer.bias: copying a param with shape torch.Size([51]) from checkpoint, the shape in current model is torch.Size([17]).

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HuangJunJie2017 avatar HuangJunJie2017 commented on August 17, 2024

can you run the origin hrnet repo with the pretrained models provided by the origin hrnet repo?

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HuangJunJie2017 avatar HuangJunJie2017 commented on August 17, 2024

If you can't, you should question on the origin hrnet repo for support.
If you can, you won't have problem in using this repo with the pretrained models provided in this repo.

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HuangJunJie2017 avatar HuangJunJie2017 commented on August 17, 2024

try not to use the origin hrnet repo alone with the pretrained models in this repo, so do the inverse

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azuryl avatar azuryl commented on August 17, 2024

orgin
I had run in orgin repo

your repo should use https://github.com/leoxiaobin/deep-high-resolution-net.pytorch/blob/master/experiments/coco/hrnet/w32_256x192_adam_lr1e-3.yaml
should not use w32_256x192_adam_lr1e-3_offset_ofm.yaml
https://github.com/HuangJunJie2017/UDP-Pose/tree/master/deep-high-resolution-net.pytorch/experiments/coco/hrnet

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HuangJunJie2017 avatar HuangJunJie2017 commented on August 17, 2024

emmm, but the others have no problem about using this.

make sure that you use this config: experiments/coco/hrnet/w32_256x192_adam_lr1e-3_offset_ofm.yaml
make sure that you use this checkpoint: UDP-hrnet_w32_256x192.pth which should be downloaded from here: https://pan.baidu.com/s/1mPuVj8piYzgWjoRgyd0Cwg (dsa9)

run this under https://github.com/HuangJunJie2017/UDP-Pose/tree/master/deep-high-resolution-net.pytorch ?

python tools/test.py --cfg experiments/coco/hrnet/w32_256x192_adam_lr1e-3_offset_ofm.yaml TEST.MODEL_FILE models/pytorch/pose_coco/UDP-hrnet_w32_256x192.pth TEST.USE_GT_BBOX False

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azuryl avatar azuryl commented on August 17, 2024

thank you

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azuryl avatar azuryl commented on August 17, 2024

since your hrnet fold's name is same as orginal repo but in fact your hrnet's fold just can run your model but orginal model .I had run youe model success
udphrnet

"emmm, but the others have no problem about using this."

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