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

[BMaser]

Describe the bug

I tried to get a score for a gray-scale image, but I got the following error,

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

Desktop (please complete the following information):

• OS: [Ubuntu]
• Version [20.04]

Additional context

import imquality.brisque as brisque
import PIL.Image
path = '/home/image.png'
img = PIL.Image.open(path)
brisque.score(img)




ValueError                                Traceback (most recent call last)
Input In [11], in <cell line: 6>()
      4 path = '/home/maser/Projects/Wood_Project/Dataset/Heidelberg_Spectrometer/UV_VIS/Scan0_r0_l0_163,57516.png'
      5 img = PIL.Image.open(path)
----> 6 brisque.score(img)

File ~/anaconda3/envs/quality/lib/python3.9/site-packages/imquality/brisque.py:160, in score(image, kernel_size, sigma)
    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)

File ~/anaconda3/envs/quality/lib/python3.9/site-packages/imquality/brisque.py:130, in calculate_features(image, kernel_size, sigma)
    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.
    133     #    Fix this warning error in version of scikit-image 0.16.0.
    134     with warnings.catch_warnings():

File ~/anaconda3/envs/quality/lib/python3.9/site-packages/imquality/brisque.py:45, in Brisque.__init__(self, image, kernel_size, sigma)
     38 def __init__(
     39     self,
     40     image: typing.Union[PIL.Image.Image, numpy.ndarray],
     41     kernel_size: int = 7,
     42     sigma: float = 7 / 6,
     43 ):
     44     self.image = pil2ndarray(image)
---> 45     self.image = skimage.color.rgb2gray(self.image)
     46     self.kernel_size = kernel_size
     47     self.sigma = sigma

File ~/anaconda3/envs/quality/lib/python3.9/site-packages/skimage/_shared/utils.py:394, in channel_as_last_axis.__call__.<locals>.fixed_func(*args, **kwargs)
    391 channel_axis = kwargs.get('channel_axis', None)
    393 if channel_axis is None:
--> 394     return func(*args, **kwargs)
    396 # TODO: convert scalars to a tuple in anticipation of eventually
    397 #       supporting a tuple of channel axes. Right now, only an
    398 #       integer or a single-element tuple is supported, though.
    399 if np.isscalar(channel_axis):

File ~/anaconda3/envs/quality/lib/python3.9/site-packages/skimage/color/colorconv.py:875, in rgb2gray(rgb, channel_axis)
    834 @channel_as_last_axis(multichannel_output=False)
    835 def rgb2gray(rgb, *, channel_axis=-1):
    836     """Compute luminance of an RGB image.
    837 
    838     Parameters
   (...)
    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

File ~/anaconda3/envs/quality/lib/python3.9/site-packages/skimage/color/colorconv.py:140, in _prepare_colorarray(arr, force_copy, channel_axis)
    137 if arr.shape[channel_axis] != 3:
    138     msg = (f'the input array must have size 3 along `channel_axis`, '
    139            f'got {arr.shape}')
--> 140     raise ValueError(msg)
    142 float_dtype = _supported_float_type(arr.dtype)
    143 if float_dtype == np.float32:

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

[mohammadSHP]

did this problem solved?
someone help me with same problem

[masterofobzene]

did this problem solved? someone help me with same problem

No and the owner deletes problems.
Easy way uh?

[NetRxn]

Same issue here.

[pockerman]

The suggestion here: #41 seems to fix that but I don't know how much it may affect the results

[hosford42]

The issue is fixed here, but not in the version stored on PyPI.

#41 (comment)