mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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97 lines
3.7 KiB
Python
97 lines
3.7 KiB
Python
from PIL import Image, ImageFilter, ImageOps
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def get_crop_region_v2(mask, pad=0):
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"""
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Finds a rectangular region that contains all masked ares in a mask.
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Returns None if mask is completely black mask (all 0)
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Parameters:
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mask: PIL.Image.Image L mode or numpy 1d array
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pad: int number of pixels that the region will be extended on all sides
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Returns: (x1, y1, x2, y2) | None
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Introduced post 1.9.0
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"""
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mask = mask if isinstance(mask, Image.Image) else Image.fromarray(mask)
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if box := mask.getbbox():
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x1, y1, x2, y2 = box
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return (max(x1 - pad, 0), max(y1 - pad, 0), min(x2 + pad, mask.size[0]), min(y2 + pad, mask.size[1])) if pad else box
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def get_crop_region(mask, pad=0):
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"""
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Same function as get_crop_region_v2 but handles completely black mask (all 0) differently
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when mask all black still return coordinates but the coordinates may be invalid ie x2>x1 or y2>y1
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Notes: it is possible for the coordinates to be "valid" again if pad size is sufficiently large
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(mask_size.x-pad, mask_size.y-pad, pad, pad)
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Extension developer should use get_crop_region_v2 instead unless for compatibility considerations.
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"""
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mask = mask if isinstance(mask, Image.Image) else Image.fromarray(mask)
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if box := get_crop_region_v2(mask, pad):
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return box
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x1, y1 = mask.size
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x2 = y2 = 0
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return max(x1 - pad, 0), max(y1 - pad, 0), min(x2 + pad, mask.size[0]), min(y2 + pad, mask.size[1])
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def expand_crop_region(crop_region, processing_width, processing_height, image_width, image_height):
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"""expands crop region get_crop_region() to match the ratio of the image the region will processed in; returns expanded region
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for example, if user drew mask in a 128x32 region, and the dimensions for processing are 512x512, the region will be expanded to 128x128."""
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x1, y1, x2, y2 = crop_region
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ratio_crop_region = (x2 - x1) / (y2 - y1)
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ratio_processing = processing_width / processing_height
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if ratio_crop_region > ratio_processing:
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desired_height = (x2 - x1) / ratio_processing
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desired_height_diff = int(desired_height - (y2-y1))
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y1 -= desired_height_diff//2
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y2 += desired_height_diff - desired_height_diff//2
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if y2 >= image_height:
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diff = y2 - image_height
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y2 -= diff
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y1 -= diff
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if y1 < 0:
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y2 -= y1
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y1 -= y1
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if y2 >= image_height:
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y2 = image_height
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else:
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desired_width = (y2 - y1) * ratio_processing
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desired_width_diff = int(desired_width - (x2-x1))
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x1 -= desired_width_diff//2
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x2 += desired_width_diff - desired_width_diff//2
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if x2 >= image_width:
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diff = x2 - image_width
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x2 -= diff
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x1 -= diff
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if x1 < 0:
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x2 -= x1
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x1 -= x1
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if x2 >= image_width:
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x2 = image_width
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return x1, y1, x2, y2
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def fill(image, mask):
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"""fills masked regions with colors from image using blur. Not extremely effective."""
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image_mod = Image.new('RGBA', (image.width, image.height))
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image_masked = Image.new('RGBa', (image.width, image.height))
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image_masked.paste(image.convert("RGBA").convert("RGBa"), mask=ImageOps.invert(mask.convert('L')))
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image_masked = image_masked.convert('RGBa')
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for radius, repeats in [(256, 1), (64, 1), (16, 2), (4, 4), (2, 2), (0, 1)]:
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blurred = image_masked.filter(ImageFilter.GaussianBlur(radius)).convert('RGBA')
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for _ in range(repeats):
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image_mod.alpha_composite(blurred)
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return image_mod.convert("RGB")
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