Hello everyone,
I am using a SAR image (16-bit) and trying to implement GLCM algorithm
using sciki-learn. When trying to calculate the GLCM using greycomatrix i
get the following error:
assert image.max() < levels. It says that the maximum value of the image
intensity must be less than the number of grey levels.
Because the SAR image is really big, i want to reduce the calculation time by
reducing the levels to 8.
Even if i remove the parameter 'level=8' when using greycomatrix, still gives
me the same error
My code is the following:
from skimage.feature import greycomatrix, greycoprops
import numpy as np
from skimage import data
import rasterio
path = 'C:\Users\GLCM_implementation\glasgow.tif'
with rasterio.open(path, 'r') as src:
import_file = src.read()
img = import_file[0,:,:] #i need only the two dimentions (height, width)
print img.shape
#calculate the GLCM specifying the distance, direction(4 directions) and number
of grey levels
GLCM = greycomatrix(img, [1], [0, np.pi/4, np.pi/2, 3*np.pi/4],levels=8,
symmetric=False, normed=True)
#list(GLCM[:,:,0,2])
#Calculate texture statistics
contrast = greycoprops(GLCM, 'contrast')
dissimilarity = greycoprops(GLCM, 'dissimilarity')
homogeneity = greycoprops(GLCM, 'homogeneity')
energy = greycoprops(GLCM, 'energy')
correlation = greycoprops(GLCM, 'correlation')
ASM = greycoprops(GLCM, 'ASM')
Error message:
101 image = np.ascontiguousarray(image) 102 assert image.min() >=
0--> 103 assert image.max() < levels 104 image =
image.astype(np.uint8) 105 distances = np.ascontiguousarray(distances,
dtype=np.float64)
AssertionError:
I would appreciate any help.
Thank you in advance
Ioannis
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