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* ci(pre-commit): Add pep8-naming to `pre-commit` hooks (#7038) * refactor: Fix naming conventions (#7038) * Update arithmetic_analysis/lu_decomposition.py Co-authored-by: Christian Clauss <cclauss@me.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * refactor(lu_decomposition): Replace `NDArray` with `ArrayLike` (#7038) * chore: Fix naming conventions in doctests (#7038) * fix: Temporarily disable project euler problem 104 (#7069) * chore: Fix naming conventions in doctests (#7038) Co-authored-by: Christian Clauss <cclauss@me.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
"""
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Peak signal-to-noise ratio - PSNR
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https://en.wikipedia.org/wiki/Peak_signal-to-noise_ratio
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Source:
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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: float, contrast: float) -> float:
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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 # noqa: N806
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PSNR = 20 * math.log10(PIXEL_MAX / math.sqrt(mse)) # noqa: N806
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return PSNR
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def main() -> None:
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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, "image_data/original_image.png"))
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contrast = cv2.imread(os.path.join(dir_path, "image_data/compressed_image.png"), 1)
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original2 = cv2.imread(os.path.join(dir_path, "image_data/PSNR-example-base.png"))
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contrast2 = cv2.imread(
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os.path.join(dir_path, "image_data/PSNR-example-comp-10.jpg"), 1
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)
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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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