"cv2.error: OpenCV(4.7.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\resize.cpp:4065: error: (-215:Assertion failed) inv_scale_x > 0 in function 'cv::resize'"

[Contestant0star]

This error shows up after starting train.py with the configuration that came with traiNNer. Fresh install with nothing modified (except the train_sr.yml"

23-05-31 19:09:48.945 - INFO: Random seed: 0
23-05-31 19:09:49.264 - INFO: Dataset [AlignedDataset - DIV2K] is created.
23-05-31 19:09:49.266 - INFO: Number of train images: 14,361, epoch iters: 1,795
23-05-31 19:09:49.266 - INFO: Total epochs needed: 279 for iters 500,000
23-05-31 19:09:49.266 - INFO: Dataset [AlignedDataset - val_set14_part] is created.
23-05-31 19:09:49.267 - INFO: Number of val images in [val_set14_part]: 1
23-05-31 19:09:49.624 - INFO: AMP library available
23-05-31 19:09:51.252 - INFO: Initialization method [kaiming]
23-05-31 19:09:51.547 - INFO: Initialization method [kaiming]
23-05-31 19:09:51.670 - INFO: Loading pretrained model for G [..\experiments\pretrained_models\RRDB_PSNR_x4.pth]
23-05-31 19:09:52.916 - INFO: GAN enabled
23-05-31 19:09:52.922 - INFO: AMP enabled
23-05-31 19:09:52.923 - INFO: norm gradient clip enabled. Clip value: 0.1.
23-05-31 19:09:52.935 - INFO: Network G structure: DataParallel - RRDBNet, with parameters: 16,697,987
23-05-31 19:09:52.936 - INFO: Network D structure: DataParallel - Discriminator_VGG, with parameters: 14,502,281
23-05-31 19:09:52.936 - INFO: Model [SRModel] created.
23-05-31 19:09:52.936 - INFO: Start training from epoch: 0, iter: 0
E:\nn\trainner\codes\models\base_model.py:921: FutureWarning: Non-finite norm encountered in torch.nn.utils.clip_grad_norm_; continuing anyway. Note that the default behavior will change in a future release to error out if a non-finite total norm is encountered. At that point, setting error_if_nonfinite=false will be required to retain the old behavior.
self.grad_clip(
C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\optim\lr_scheduler.py:129: UserWarning: Detected call of lr_scheduler.step() before optimizer.step(). In PyTorch 1.1.0 and later, you should call them in the opposite order: optimizer.step() before lr_scheduler.step(). Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
warnings.warn("Detected call of lr_scheduler.step() before optimizer.step(). "
Traceback (most recent call last):
File "E:\nn\trainner\codes\train.py", line 500, in
main()
File "E:\nn\trainner\codes\train.py", line 496, in main
fit(model, opt, dataloaders, steps_states, data_params, loggers)
File "E:\nn\trainner\codes\train.py", line 224, in fit
for n, train_data in enumerate(dataloaders['train'], start=1):
File "C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\utils\data\dataloader.py", line 521, in next
data = self._next_data()
File "C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\utils\data\dataloader.py", line 1203, in _next_data
return self._process_data(data)
File "C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\utils\data\dataloader.py", line 1229, in _process_data
data.reraise()
File "C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch_utils.py", line 425, in reraise
raise self.exc_type(msg)
cv2.error: Caught error in DataLoader worker process 0.
Original Traceback (most recent call last):
File "C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\utils\data_utils\worker.py", line 287, in _worker_loop
data = fetcher.fetch(index)
File "C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\utils\data_utils\fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "C:\Users\AppData\Local\Programs\Python\Python39\lib\site-packages\torch\utils\data_utils\fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "E:\nn\trainner\codes\data\aligned_dataset.py", line 117, in getitem
img_A, img_B = paired_imgs_check(
File "E:\nn\trainner\codes\dataops\augmentations.py", line 1388, in paired_imgs_check
img_A, img_B = shape_change_fn(
File "E:\nn\trainner\codes\dataops\augmentations.py", line 1141, in shape_change_fn
img_A = transforms.Resize((int(h/scale), int(w/scale)),
File "E:\nn\trainner\codes\dataops\augmennt\augmennt\transforms.py", line 192, in call
return F.resize(img, self.size, self.interpolation)
File "E:\nn\trainner\codes\dataops\augmennt\augmennt\common.py", line 211, in wrapped_function
result = func(img, *args, **kwargs)
File "E:\nn\trainner\codes\dataops\augmennt\augmennt\functional.py", line 187, in resize
output = cv2.resize(img, dsize=(size[1], size[0]), interpolation=_cv2_str2interpolation[interpolation])
cv2.error: OpenCV(4.7.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\resize.cpp:4065: error: (-215:Assertion failed) inv_scale_x > 0 in function 'cv::resize'

[victorca25]

I missed this issue before, did you find a solution?

I can take a look in the following days to see if I find where it's coming from.