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!