Dear All,
I was trying to use the above code segment for performing Contrast Limited
Adaptive Histogram Equalization (CLAHE).
def clahe_equalized(imgs):
imgs_equalized = np.empty(imgs.shape)
for i in range(imgs.shape[0]):
print('imgs[i,0] ',imgs[i,0].dtype)
print('imgs[i,0] ',imgs[i,0].max())
print('imgs[i,0] ',imgs[i,0].min())
imgs_equalized[i,0] =
exposure.equalize_adapthist(imgs[i,0],clip_limit=0.03)
return imgs_equalized
The dtype is float64, maximum value is 255.0 and minimum value is 0.0
Running the program generates the following error message ( I only keep the
related ones)
imgs_equalized[i,0] = exposure.equalize_adapthist(imgs[i,0],clip_limit=0.03)
raise ValueError("Images of type float must be between -1 and 1.")
ValueError: Images of type float must be between -1 and 1.
In accordance with the above error message and image characteristics, what
are the best way to handle this scenario.
I have been thinking of two approaches
1. add imgs[i,0] = imgs[i,0]/255. which scale it to 0 and 1
2. convert imgs[i,0] from float64 to unit8
but imgs[i,0] = imgs[i,0].astype(np.unit8) gives the error message such as
imgs[i,0]=imgs[i,0].astype(np.unit8)
AttributeError: 'module' object has no attribute 'unit8'
Would you like to give any advice on this problem? Thank you very much!
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