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Nerfs the aggressive post-processing step of overlaying the original image.

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CodeHatchling 2023-11-28 16:13:42 -07:00
parent e715e46b6a
commit a6e5846453
1 changed files with 11 additions and 3 deletions
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14
modules/processing.py
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@ -1412,7 +1412,12 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
image_mask = Image.fromarray(np_mask)
if self.inpaint_full_res:
self.mask_for_overlay = image_mask
np_mask = np.array(image_mask).astype(np.float32)
np_mask /= 255
np_mask = 1-pow(1-np_mask, 100)
np_mask *= 255
np_mask = np.clip(np_mask, 0, 255).astype(np.uint8)
self.mask_for_overlay = Image.fromarray(np_mask)
mask = image_mask.convert('L')
crop_region = masking.get_crop_region(np.array(mask), self.inpaint_full_res_padding)
crop_region = masking.expand_crop_region(crop_region, self.width, self.height, mask.width, mask.height)
@ -1423,8 +1428,11 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.paste_to = (x1, y1, x2-x1, y2-y1)
else:
image_mask = images.resize_image(self.resize_mode, image_mask, self.width, self.height)
np_mask = np.array(image_mask)
np_mask = np.clip((np_mask.astype(np.float32)) * 2, 0, 255).astype(np.uint8)
np_mask = np.array(image_mask).astype(np.float32)
np_mask /= 255
np_mask = 1-pow(1-np_mask, 100)
np_mask *= 255
np_mask = np.clip(np_mask, 0, 255).astype(np.uint8)
self.mask_for_overlay = Image.fromarray(np_mask)
self.overlay_images = []