adjust weights by channel sum
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@ -23,9 +23,13 @@ def blend_source_histogram(source_image: Image, dims: Tuple[int, int], sigma = 2
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hist_g = g.histogram()
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hist_b = b.histogram()
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rng_r = random.choice(256, p=hist_r)
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rng_g = random.choice(256, p=hist_g)
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rng_b = random.choice(256, p=hist_b)
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stat_r = ImageStat(hist_r)
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stat_g = ImageStat(hist_g)
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stat_b = ImageStat(hist_b)
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rng_r = random.choice(256, p=np.divide(np.copy(hist_r), stat_r.sum))
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rng_g = random.choice(256, p=np.divide(np.copy(hist_g), stat_g.sum))
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rng_b = random.choice(256, p=np.divide(np.copy(hist_b), stat_b.sum))
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noise_r = rng_r.integers(0, size=width * height)
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noise_g = rng_g.integers(0, size=width * height)
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