Hi @JuanFMontesinos
Thanks for your help. I had introduced this conversion; it remove the error but I get another error, which is :

IndexError                                Traceback (most recent call last)
 in 
----> 1 for original_img, noisy_img in train_loader:
2         originalImage = original_img
3
~.conda\envs\pytorch2\lib\site-packages\torch\utils\data\dataloader.py in next(self)
352
353     def next(self):
–> 354         data = self._next_data()
355         self._num_yielded += 1
356         if self._dataset_kind == _DatasetKind.Iterable and \
~.conda\envs\pytorch2\lib\site-packages\torch\utils\data\dataloader.py in _next_data(self)
392     def _next_data(self):
393         index = self._next_index()  # may raise StopIteration
–> 394         data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
395         if self._pin_memory:
396             data = _utils.pin_memory.pin_memory(data)
~.conda\envs\pytorch2\lib\site-packages\torch\utils\data_utils\fetch.py in fetch(self, possibly_batched_index)
42     def fetch(self, possibly_batched_index):
43         if self.auto_collation:
—> 44             data = [self.dataset[idx] for idx in possibly_batched_index]
45         else:
46             data = self.dataset[possibly_batched_index]
~.conda\envs\pytorch2\lib\site-packages\torch\utils\data_utils\fetch.py in (.0)
42     def fetch(self, possibly_batched_index):
43         if self.auto_collation:
—> 44             data = [self.dataset[idx] for idx in possibly_batched_index]
45         else:
46             data = self.dataset[possibly_batched_index]
 in getitem(self, index)
24         #noisyIMG = Image.open(self.filenames_NI[index])
25
—> 26         originalIMG = imageio.imread(self.filenames_OI[index])
27         noisyIMG = imageio.imread(self.filenames_NI[index])
28
IndexError: list index out of range