Problem in data transformations

[rabiaali95]

In dataloader.py when preparing rotated images
rotated_imgs = [

                self.transform(img0),
                self.transform(rotate_img(img0,  90)),
                self.transform(rotate_img(img0, 180)),
                self.transform(rotate_img(img0, 270))
            ]

the following error arises.
ValueError: some of the strides of a given numpy array are negative. This is currently not supported, but will be added in future releases.

How to solve this error?

[rxqy]

Hi, a simple solution would be to add a .copy() to all of the output of rotate_img

From

FeatureLearningRotNet/dataloader.py

Lines 216 to 226 in 817342b

	def rotate_img(img, rot):
	if rot == 0: # 0 degrees rotation
	return img
	elif rot == 90: # 90 degrees rotation
	return np.flipud(np.transpose(img, (1,0,2)))
	elif rot == 180: # 90 degrees rotation
	return np.fliplr(np.flipud(img))
	elif rot == 270: # 270 degrees rotation / or -90
	return np.transpose(np.flipud(img), (1,0,2))
	else:
	raise ValueError('rotation should be 0, 90, 180, or 270 degrees')

To
return np.flipud(...),copy()
return np.fliplr(...).copy()
return np.transpose(...).copy()

For more details of this problem, you can check this thread from the pytorch form