Comments (3)
DagnyT
commented on May 20, 2024
1
labels = torch.cat([labels, datasets[i][1]+torch.max(labels)+1]
It is written in such way to shift label indices, in every dataset you expect to have labels: [0, n1], so in concat function labels from new dataset have to start from (n1+1).
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yunyundong
commented on May 20, 2024
How can I point to the newest version? what's the address? Thank you very much.
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DagnyT
commented on May 20, 2024
Thank you, yes, it was a bug in TotalDataLoader. Please, check the update.
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Related Issues (20)
- hardnet training files HOT 2
- About the measurement metric HOT 1
- HardNet+ with --augmentation or --fliprot HOT 11
- Code of Oxford5k experiments HOT 2
- Training epochs HOT 2
- Verification task on HPatches
- what is the version of pytorch HOT 2
- Key Error occurred when running bash run_me.sh HOT 1
- HPatches result with matlab and python HOT 2
- The link to HardNet++ is broken HOT 1
- Test on yosemite dataset HOT 1
- Is this loss the same with Batch Hard Loss ? HOT 3
- invalid index of a 0-dim tensor. Use tensor.item() to convert a 0-dim tensor to a Python number HOT 1
- report a bug maybe
- Training Set Label Formatting HOT 2
- Loss function
- FileNotFoundError: [Errno 2] No such file or directory: 'data/sets/liberty.zip' HOT 1
- local variable 'out_a' referenced before assignment HOT 1
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- indoor dataset
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