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()