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Can't download models about merged_depth HOT 7 CLOSED

p-ranav avatar p-ranav commented on August 18, 2024
Can't download models

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Comments (7)

p-ranav avatar p-ranav commented on August 18, 2024 1

Sorry y'all, I accidentally deleted the pretrained ZIP when cleaning up my Google Drive.

Can you check again? I've restored the file.

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mmurray avatar mmurray commented on August 18, 2024 1

Thanks for the quick reply. It looks like the code is already trying to load the models from torch.hub but the repository has moved. I submit a PR #11 with the updated repository, which fixes the 404 issue for me.

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canadacow avatar canadacow commented on August 18, 2024

Same. Was excited to try it out as it's the first depth model I've found on github that isn't completely abandoned/out of date.

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canadacow avatar canadacow commented on August 18, 2024

Thanks for updating the pretrained.zip. The python script doesn't work with the URL but downloading it manually (constructing the URL manually) works just fine.

Using cache found in C:\Users\Dean/.cache\torch\hub\rwightman_gen-efficientnet-pytorch_master
Loading base model ()...Done.
Removing last two layers (global_pool & classifier).
Building Encoder-Decoder model..Done.
Using cache found in C:\Users\Dean/.cache\torch\hub\rwightman_gen-efficientnet-pytorch_master
Loading base model ()...Done.
Removing last two layers (global_pool & classifier).
Building Encoder-Decoder model..Done.
Loading weights:  ./pretrained/MiDaS_f6b98070.pt
Downloading: "https://github.com/facebookresearch/WSL-Images/archive/master.zip" to

Unfortunately https://github.com/facebookresearch/WSL-Images/archive/master.zip is now a 404 file.

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eppppi avatar eppppi commented on August 18, 2024

Thank you for uploading the file!
Unfortunately I'm also experiencing the same problem as canadacow.

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mmurray avatar mmurray commented on August 18, 2024

I also see a 404 for the WSL-images zip. Were either of you able to resolve the issue?

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p-ranav avatar p-ranav commented on August 18, 2024

It seems the models are now available in torch.hub.

One would have to acquire them like so:

model = torch.hub.load('facebookresearch/WSL-Images', 'resnext101_32x16d_wsl')

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