try:
clahe = cv2.createCLAHE(clipLimit=self.options['clip'],
tileGridSize=self.options['grid'])
# clahe = cv2.createCLAHE(clipLimit=2000.0, tileGridSize=(8,8))
except Exception:
return None
""" Apply to the image """
return clahe.apply(self.input_image)
if __name__ == '__main__':
import structure.Base
sample_image = structure.Base.sample_dir + 'sample.png'
img = cv2.imread(sample_image, 0)
op = ContrastLimitedAHE(img, options={'clip': 12.45, 'grid': (12, 8)})
import functions
result = op.execute()
# display resulting histogram
functions.createHistogram(result)
cv2.imshow('Output of CLAHE', result)
cv2.waitKey(0)
cv2.destroyAllWindows()
# clahe = cv2.createCLAHE(clipLimit=2000.0, tileGridSize=(8,8))
except Exception:
return None
""" Apply to the image """
return clahe.apply(self.input_image)
if __name__ == '__main__':
import structure.Base
sample_image = structure.Base.sample_dir + 'sample.png'
img = cv2.imread(sample_image, 0)
op = ContrastLimitedAHE(img, options={'clip':12.45, 'grid':(12, 8)})
import functions
result = op.execute()
# display resulting histogram
functions.createHistogram(result)
cv2.imshow('Output of CLAHE', result)
cv2.waitKey(0)
cv2.destroyAllWindows()
def execute(self):
"""
Execute the Algorithm
Overrides Operation.execute
Returns:
ndarray output_image - final output of the operation
"""
output_image = cv2.equalizeHist(self.input_image)
return output_image
if __name__ == '__main__':
import functions
import structure.Base
image_file = structure.Base.sample_dir + 'sample.png'
img = cv2.imread(image_file, 0)
op = AdaptiveHistogram(img)
final = op.execute()
functions.createHistogram(final)
cv2.imshow('Initial Image', img)
cv2.imshow('Result Image', final)
cv2.waitKey(0)
cv2.destroyAllWindows()
"""
Execute the Algorithm
Overrides Operation.execute
Returns:
ndarray output_image - final output of the operation
"""
output_image = cv2.equalizeHist(self.input_image)
return output_image
if __name__ == '__main__':
import functions
import structure.Base
image_file = structure.Base.sample_dir + 'sample.png'
img = cv2.imread(image_file, 0)
op = AdaptiveHistogram(img)
final = op.execute()
functions.createHistogram(final)
cv2.imshow('Initial Image', img)
cv2.imshow('Result Image', final)
cv2.waitKey(0)
cv2.destroyAllWindows()
