there is no w32_256x256_adam_lr1e-3.yaml

[azuryl]

I run python tools/test.py \ --cfg experiments/coco/hrnet/w32_256x192_adam_lr1e-3.yaml \ TEST.MODEL_FILE models/pytorch/pose_coco/pose_hrnet_w32_256x192.pth \ TEST.USE_GT_BBOX Fals from https://github.com/HuangJunJie2017/UDP-Pose/tree/master/deep-high-resolution-net.pytorch

but in experiments/coco/hrnet/ just have w32_256x192_adam_lr1e-3_offset_ofm.yaml and does not match pose_hrnet_w32_256x192.pth https://github.com/HuangJunJie2017/UDP-Pose/tree/master/deep-high-resolution-net.pytorch/experiments/coco/hrnet

and how to run your UDP-hrnet_w32_256x192

[HuangJunJie2017]

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

[azuryl]

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]).

[HuangJunJie2017]

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

[HuangJunJie2017]

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.

[HuangJunJie2017]

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

[azuryl]

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

[HuangJunJie2017]

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

[azuryl]

thank you

[azuryl]

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

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