Utilize numpy functions to do the color correction #8
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mahmoudnafifi
approved these changes
Feb 16, 2021
| I[:, 1] * I[:, 2], I[:, 0] * I[:, 0], I[:, 1] * I[:, 1], | ||
| I[:, 2] * I[:, 2], I[:, 0] * I[:, 1] * I[:, 2], | ||
| np.repeat(1, np.shape(I)[0])))) | ||
| rgb = I |
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We may need to change kernelP(I) to kernelP(rgb)
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Maybe we can apply the change in other commits so that the PR won't introduced backward incompatible changes. The users might call the public function kernelP with keyword argument KernelP(I=some_rgb_image).
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The PR utilizes broadcasting mechanism and numpy functions to speed up the color correction.
On a machine with 8-core 3.1 Ghz CPU, the original
correctImagetakes ~1.88 second to process example_images/figure3.jpg. With the PR, it takes ~0.14 second to process the same image.See also #5 and #6.