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Hi, in train.md you mentioned that we need to download the ImageNet-pretrained HRNet backbone model from the original authors' OneDrive. After downloading the file, I assumed the path to this weight should be specified as "weight" in config yaml file to be used as the initial weight? However the model keys don't seem to match, so I'm confused where should I use the pertained HRNET model.
Looking forward to your response
The text was updated successfully, but these errors were encountered:
Thanks for getting back to me so quickly!
Yes I'm running train.py, and using mseg_semantic/config/train/1080_release/mseg-relabeled-1m.yaml. Just wondering where should the ImageNet-pretrained HRNet backbone model be stored after download it, and where to specify the path to this file in config.
I tried putting path to pertained weight in args.weight but got "KeyError: 'state_dict' "
Also tried changing model.load_state_dict(checkpoint['state_dict']) to model.load_state_dict(checkpoint) but got a bunch of missing keys. Please let me know what I'm doing wrong. Thanks!
Hi, in train.md you mentioned that we need to download the ImageNet-pretrained HRNet backbone model from the original authors' OneDrive. After downloading the file, I assumed the path to this weight should be specified as "weight" in config yaml file to be used as the initial weight? However the model keys don't seem to match, so I'm confused where should I use the pertained HRNET model.
Looking forward to your response
The text was updated successfully, but these errors were encountered: