unet TypeError: function takes exactly 1 argument (3 given)

[tobimichigan]

Hi, I tried running your code but it hangs around the line below with `"unet TypeError: function takes exactly 1 argument (3 given)". I have commented the section. Please kindly advise,

Training process

if TRAIN: unet_model.train() path = os.path.join('saved_models',MODEL_NAME) if SAVE_MODEL else None unet_train_history = unet_classifier.train(EPOCHS,trainloader,mini_batch=100,save_best=path) print(f'Training Finished after {EPOCHS} epoches')

Testing process on test data.

unet_model.eval() unet_score = unet_classifier.test(testloader) #unet TypeError: function takes exactly 1 argument (3 given) print(f'\n\nDice Score {unet_score}')

Dice Score 0.7446110107881675

`

[tobimichigan]

Here are further details:

`--------------------------------------------------------------------------- TypeError Traceback (most recent call last)

in () 7 # Testing process on test data. 8 unet_model.eval() ----> 9 unet_score = unet_classifier.test(testloader) #unet TypeError: function takes exactly 1 argument (3 given) 10 print(f'\n\nDice Score {unet_score}') 11 # Dice Score 0.7446110107881675 10 frames Brain-Tumor-Segmentation/bts/classifier.py in test(self, testloader, threshold) 160 while len(test_data_indexes) != 0: 161 # Getting a data sample. --> 162 data = testloader.next() 163 # Getting the data index 164 index = int(data['index']) /usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in __next__(self) 343 344 def __next__(self): --> 345 data = self._next_data() 346 self._num_yielded += 1 347 if self._dataset_kind == _DatasetKind.Iterable and \ /usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in _next_data(self) 383 def _next_data(self): 384 index = self._next_index() # may raise StopIteration --> 385 data = self._dataset_fetcher.fetch(index) # may raise StopIteration 386 if self._pin_memory: 387 data = _utils.pin_memory.pin_memory(data) /usr/local/lib/python3.6/dist-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] /usr/local/lib/python3.6/dist-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] /content/Brain-Tumor-Segmentation/bts/dataset.py in __getitem__(self, index) 60 # Custom transformations 61 if self.transform: ---> 62 image, mask = self._random_transform(image, mask) 63 64 image = TF.to_tensor(image) /content/Brain-Tumor-Segmentation/bts/dataset.py in _random_transform(self, image, mask) 85 if self.DEBUG: 86 print(f'\t\tRotation by: {rotation}') ---> 87 image = self.transform[choice_key](image, rotation) 88 mask = self.transform[choice_key](mask, rotation) 89 else: /usr/local/lib/python3.6/dist-packages/torchvision/transforms/functional.py in rotate(img, angle, resample, expand, center, fill) 727 fill = tuple([fill] * 3) 728 --> 729 return img.rotate(angle, resample, expand, center, fillcolor=fill) 730 731 /usr/local/lib/python3.6/dist-packages/PIL/Image.py in rotate(self, angle, resample, expand, center, translate, fillcolor) 2003 w, h = nw, nh 2004 -> 2005 return self.transform((w, h), AFFINE, matrix, resample, fillcolor=fillcolor) 2006 2007 def save(self, fp, format=None, **params): /usr/local/lib/python3.6/dist-packages/PIL/Image.py in transform(self, size, method, data, resample, fill, fillcolor) 2297 raise ValueError("missing method data") 2298 -> 2299 im = new(self.mode, size, fillcolor) 2300 if method == MESH: 2301 # list of quads /usr/local/lib/python3.6/dist-packages/PIL/Image.py in new(mode, size, color) 2503 im.palette = ImagePalette.ImagePalette() 2504 color = im.palette.getcolor(color) -> 2505 return im._new(core.fill(mode, size, color)) 2506 2507 TypeError: function takes exactly 1 argument (3 given)`

[muminoff]

The same error occurs on my side too. My initial dataset was in RGB and converted it using ImageMagick to greyscale PNG file.

[tobimichigan]

@muminoff , thanks for your response. I am using the same dataset suggested in the repo. Please could you elaborate further on the workaround this? I mean how to practically handle RGB issue in this case?

[muminoff]

@tobimichigan I am not maintainer of this repo. I am also issue-reporter like you. Let's wait what @sdsubhajitdas thinks about this.

[JordanMicahBennett]

@muminoff , thanks for your response. I am using the same dataset suggested in the repo. Please could you elaborate further on the workaround this? I mean how to practically handle RGB issue in this case?

It is possible that information is lost in the RGB downgrade to Grayscale.

A solution could be to retrain the model entirely, ensuring you payed attention to the shape of your new model, wrt rgb channels.

[Hamid-Naderi]

Did anyone solve this issue? I also get the same error! Seems there is something with Pillow library!? I tried with version 7.1 and 8.1 but again the same error!