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* Add compression_analysis removing analysis/compression_analysis to just compression_analysis * Delete PSNR-example-base.png * Delete PSNR-example-comp-10.jpg * Delete compressed_image.png * Delete example_image.jpg * Delete example_wikipedia_image.jpg * Delete original_image.png * Delete psnr.py
41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
"""
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Peak signal-to-noise ratio - PSNR - https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio
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Soruce: https://tutorials.techonical.com/how-to-calculate-psnr-value-of-two-images-using-python/
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"""
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import math
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import os
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import cv2
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import numpy as np
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def psnr(original, contrast):
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mse = np.mean((original - contrast) ** 2)
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if mse == 0:
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return 100
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PIXEL_MAX = 255.0
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PSNR = 20 * math.log10(PIXEL_MAX / math.sqrt(mse))
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return PSNR
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def main():
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dir_path = os.path.dirname(os.path.realpath(__file__))
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# Loading images (original image and compressed image)
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original = cv2.imread(os.path.join(dir_path, 'original_image.png'))
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contrast = cv2.imread(os.path.join(dir_path, 'compressed_image.png'), 1)
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original2 = cv2.imread(os.path.join(dir_path, 'PSNR-example-base.png'))
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contrast2 = cv2.imread(os.path.join(dir_path, 'PSNR-example-comp-10.jpg'), 1)
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# Value expected: 29.73dB
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print("-- First Test --")
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print(f"PSNR value is {psnr(original, contrast)} dB")
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# # Value expected: 31.53dB (Wikipedia Example)
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print("\n-- Second Test --")
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print(f"PSNR value is {psnr(original2, contrast2)} dB")
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if __name__ == '__main__':
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main()
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