From e9620fd62e72d11493c714e65291191a4e51054d Mon Sep 17 00:00:00 2001 From: Sean Sube Date: Sat, 14 Jan 2023 15:34:57 -0600 Subject: [PATCH] generate noise channel-wise --- api/onnx_web/image.py | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/api/onnx_web/image.py b/api/onnx_web/image.py index f46cb0fa..a45248ff 100644 --- a/api/onnx_web/image.py +++ b/api/onnx_web/image.py @@ -26,13 +26,9 @@ def blend_source_histogram(source_image: Image, dims: Tuple[int, int], sigma = 2 stats = ImageStat.Stat(source_image) sum_r, sum_g, sum_b = stats.sum - rng_r = random.choice(256, p=np.divide(np.copy(hist_r), sum_r)) - rng_g = random.choice(256, p=np.divide(np.copy(hist_g), sum_g)) - rng_b = random.choice(256, p=np.divide(np.copy(hist_b), sum_b)) - - noise_r = rng_r.integers(0, size=width * height) - noise_g = rng_g.integers(0, size=width * height) - noise_b = rng_b.integers(0, size=width * height) + noise_r = random.choice(256, p=np.divide(np.copy(hist_r), sum_r), size=width*height) + noise_g = random.choice(256, p=np.divide(np.copy(hist_g), sum_g), size=width*height) + noise_b = random.choice(256, p=np.divide(np.copy(hist_b), sum_b), size=width*height) noise = Image.fromarray(zip(noise_r, noise_g, noise_b))