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Simplifying ControlNet SAM preprocessor segmentation color mapping.

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user1 2023-06-25 12:54:48 -07:00
parent de4064bdac
commit b872e7a5e0
1 changed files with 1 additions and 7 deletions
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8
invokeai/app/invocations/controlnet_image_processors.py
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@ -485,18 +485,12 @@ class SamDetectorReproducibleColors(SamDetector):
sorted_anns = sorted(anns, key=(lambda x: x['area']), reverse=True)
h, w = anns[0]['segmentation'].shape
final_img = Image.fromarray(np.zeros((h, w, 3), dtype=np.uint8), mode="RGB")
print("number of annotations: ", len(sorted_anns))
print("type of annotations: ", type(sorted_anns))
palette = ade_palette()
for i, ann in enumerate(sorted_anns):
m = ann['segmentation']
img = np.empty((m.shape[0], m.shape[1], 3), dtype=np.uint8)
# doing modulo just in case number of annotated regions exceeds number of colors in palette
ann_color = palette[i % len(palette)]
print(ann_color)
img[:, :, 0] = ann_color[0]
img[:, :, 1] = ann_color[1]
img[:, :, 2] = ann_color[2]
img[:, :] = ann_color
final_img.paste(Image.fromarray(img, mode="RGB"), (0, 0), Image.fromarray(np.uint8(m * 255)))
return np.array(final_img, dtype=np.uint8)