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19 lines
755 B
19 lines
755 B
2 years ago
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import torch
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def common_upscale(samples, width, height, upscale_method, crop):
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if crop == "center":
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old_width = samples.shape[3]
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old_height = samples.shape[2]
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old_aspect = old_width / old_height
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new_aspect = width / height
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x = 0
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y = 0
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if old_aspect > new_aspect:
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x = round((old_width - old_width * (new_aspect / old_aspect)) / 2)
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elif old_aspect < new_aspect:
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y = round((old_height - old_height * (old_aspect / new_aspect)) / 2)
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s = samples[:,:,y:old_height-y,x:old_width-x]
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else:
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s = samples
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return torch.nn.functional.interpolate(s, size=(height, width), mode=upscale_method)
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