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prevent neural network resizing when it is not necessary #1109

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AUTOMATIC 2022-09-30 14:23:41 +03:00
parent 98cc6c6e74
commit 980cd1697a
1 changed files with 10 additions and 8 deletions
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12
modules/images.py
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@ -213,17 +213,19 @@ def resize_image(resize_mode, im, width, height):
if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None" or im.mode == 'L': if opts.upscaler_for_img2img is None or opts.upscaler_for_img2img == "None" or im.mode == 'L':
return im.resize((w, h), resample=LANCZOS) return im.resize((w, h), resample=LANCZOS)
scale = max(w / im.width, h / im.height)
if scale > 1.0:
upscalers = [x for x in shared.sd_upscalers if x.name == opts.upscaler_for_img2img] upscalers = [x for x in shared.sd_upscalers if x.name == opts.upscaler_for_img2img]
assert len(upscalers) > 0, f"could not find upscaler named {opts.upscaler_for_img2img}" assert len(upscalers) > 0, f"could not find upscaler named {opts.upscaler_for_img2img}"
upscaler = upscalers[0] upscaler = upscalers[0]
scale = max(w / im.width, h / im.height) im = upscaler.scaler.upscale(im, scale, upscaler.data_path)
upscaled = upscaler.scaler.upscale(im, scale, upscaler.data_path)
if upscaled.width != w or upscaled.height != h: if im.width != w or im.height != h:
upscaled = im.resize((w, h), resample=LANCZOS) im = im.resize((w, h), resample=LANCZOS)
return upscaled return im
if resize_mode == 0: if resize_mode == 0:
res = resize(im, width, height) res = resize(im, width, height)