ValueError: the input array must have size 3 along `channel_axis`, got (80, 512)

[chinmaysahu]

~\Envs\Iris\lib\site-packages\imquality\brisque.py in score(image, kernel_size, sigma)
158
159 def score(image: PIL.Image.Image, kernel_size=7, sigma=7 / 6) -> float:
--> 160 scaled_features = calculate_features(image, kernel_size, sigma)
161 return predict(scaled_features)

~\Envs\Iris\lib\site-packages\imquality\brisque.py in calculate_features(image, kernel_size, sigma)
128
129 def calculate_features(image: PIL.Image, kernel_size, sigma) -> numpy.ndarray:
--> 130 brisque = Brisque(image, kernel_size=kernel_size, sigma=sigma)
131 # WARNING: The algorithm is very sensitive to rescale
132 # FIXME: this is empirically the best configuration; however, scikit-image warns about bi-quadratic implementation.

~\Envs\Iris\lib\site-packages\imquality\brisque.py in init(self, image, kernel_size, sigma)
43 ):
44 self.image = pil2ndarray(image)
---> 45 self.image = skimage.color.rgb2gray(self.image)
46 self.kernel_size = kernel_size
47 self.sigma = sigma

~\Envs\Iris\lib\site-packages\skimage_shared\utils.py in fixed_func(*args, **kwargs)
336
337 if channel_axis is None:
--> 338 return func(*args, **kwargs)
339
340 # TODO: convert scalars to a tuple in anticipation of eventually

~\Envs\Iris\lib\site-packages\skimage\color\colorconv.py in rgb2gray(rgb, channel_axis)
873 >>> img_gray = rgb2gray(img)
874 """
--> 875 rgb = _prepare_colorarray(rgb)
876 coeffs = np.array([0.2125, 0.7154, 0.0721], dtype=rgb.dtype)
877 return rgb @ coeffs

~\Envs\Iris\lib\site-packages\skimage\color\colorconv.py in _prepare_colorarray(arr, force_copy, channel_axis)
138 msg = (f'the input array must have size 3 along channel_axis, '
139 f'got {arr.shape}')
--> 140 raise ValueError(msg)
141
142 float_dtype = _supported_float_type(arr.dtype)

ValueError: the input array must have size 3 along channel_axis, got (80, 512)

[0x8e5afe]

I encountered the same problem...

[Jackok99]

I had same problem for a long time.

[Jackok99]

ValueError: the input array must have size 3 along channel_axis, got (256, 384)

[soheilnavvabi]

anyone got any solution for this issue?

[njay225]

I found a solution to this issue. The problem is that in the calculate_features function in brisque.py, two Brisque objects get created.

Within the constructor of the Brique class, the function skimage.color.rgb2gray() gets called.

Back to the calculate_features method, the first Brique object that gets called, the input image is RGB; however, the second Brique object that gets called is already in grayscale. The skimage.color.rgb2gray() function throws an error that the input is already in grayscale as it expects 3 channels.

The solution was to add a condition around the call to skimage.color.rgb2gray() within the Brisque class.

Replace line 45 of `imquality/brisque.py' with:

# Only convert image to grayscale if RGB
if self.image.shape[-1] == 3:
    self.image = skimage.color.rgb2gray(self.image)

[nospotfer]

@ocampor please just merge this already when you have few minutes

[xerohackcom]

Merge it asap please! Serious issue.

[BMaser]

@njay225 ,

The error has not been resolved!

ValueError: the input array must have size 3 along channel_axis, got (336, 164)

[HodeiG]

@BMaser did you install the dependency directly from github master or did you use pip? I believe the latter won't work because a new package hasn't been rebuilt since Feb 2021: https://pypi.org/project/image-quality/#files

[BMaser]

@HodeiG : Thanks for the answer. I think as it is mentioned in the document, I simply installed it using Pypi. But I will try to install directly from github.

[HodeiG]

@ocampor I believe a new pypi package is needed that includes the fix #43. Otherwise the fix won't be generally available...

[BMaser]

@HodeiG and @ocampor , I installed the the package from the github master, but still I got the same error "the input array must have size 3 along channel_axis"