Description
Bug description
I've modified the reference (PyTorch) training code to use SVHN dataset.
That did not work (see traceback).
By looking at what DetectionDataset class is doing and some trial and error, I managed to get it working (or at least running) by restructuring the targets from the dataset as follows:
targets = [{"words": t} for t in targets]Don't know if this is "valid" fix, though.
Code snippet to reproduce the bug
See https://gist.github.com/KenjiTakahashi/9bb22093d584bb2b203eb003a2bbb414.
Like mentioned, this is mostly the same code as
https://github.com/mindee/doctr/blob/e6bf82d6a74a52cedac17108e596b9265c4e43c5/references/detection/train_pytorch.py
with slight modifications to work with SVHN class instead of DetectionDataset.
Error traceback
Traceback (most recent call last): | 0/16701 [00:00<?, ?it/s]
File "<string>", line 1, in <module>
File "ocr/src/ocr/main2.py", line 499, in main
_main(args)
File "ocr/src/ocr/main2.py", line 405, in _main
fit_one_epoch(model, train_loader, batch_transforms, optimizer, scheduler, amp=args.amp)
File "ocr/src/ocr/main2.py", line 126, in fit_one_epoch
train_loss = model(images, targets)["loss"]
^^^^^^^^^^^^^^^^^^^^^^
File "ocr/.venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "ocr/.venv/lib/python3.12/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "ocr/.venv/lib/python3.12/site-packages/doctr/models/detection/fast/pytorch.py", line 208, in forward
loss = self.compute_loss(logits, target)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "ocr/.venv/lib/python3.12/site-packages/doctr/models/detection/fast/pytorch.py", line 231, in compute_loss
targets = self.build_target(target, out_map.shape[1:], False) # type: ignore[arg-type]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "ocr/.venv/lib/python3.12/site-packages/doctr/models/detection/fast/base.py", line 177, in build_target
if any(t.dtype != np.float32 for tgt in target for t in tgt.values()):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "ocr/.venv/lib/python3.12/site-packages/doctr/models/detection/fast/base.py", line 177, in <genexpr>
if any(t.dtype != np.float32 for tgt in target for t in tgt.values()):
^^^^^^^^^^
AttributeError: 'numpy.ndarray' object has no attribute 'values'
Environment
This script does not seem to work well on (my) MacOS, it mostly returns N/A's. Anyway, I run it currently on MacOS 14 with latest doctr (tried both 0.10 release and master at e6bf82d) and PyTorch.
Deep Learning backend
I'm using PyTorch, but same problem happens on TF as well.