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Make tiled_scale work for downscaling.
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9db2e97b47
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@ -18,26 +18,26 @@ def common_upscale(samples, width, height, upscale_method, crop):
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return torch.nn.functional.interpolate(s, size=(height, width), mode=upscale_method)
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@torch.inference_mode()
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def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, upscale_amount = 4):
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output = torch.empty((samples.shape[0], 3, samples.shape[2] * upscale_amount, samples.shape[3] * upscale_amount), device="cpu")
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def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, upscale_amount = 4, out_channels = 3):
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output = torch.empty((samples.shape[0], out_channels, round(samples.shape[2] * upscale_amount), round(samples.shape[3] * upscale_amount)), device="cpu")
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for b in range(samples.shape[0]):
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s = samples[b:b+1]
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out = torch.zeros((s.shape[0], 3, s.shape[2] * upscale_amount, s.shape[3] * upscale_amount), device="cpu")
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out_div = torch.zeros((s.shape[0], 3, s.shape[2] * upscale_amount, s.shape[3] * upscale_amount), device="cpu")
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out = torch.zeros((s.shape[0], out_channels, round(s.shape[2] * upscale_amount), round(s.shape[3] * upscale_amount)), device="cpu")
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out_div = torch.zeros((s.shape[0], out_channels, round(s.shape[2] * upscale_amount), round(s.shape[3] * upscale_amount)), device="cpu")
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for y in range(0, s.shape[2], tile_y - overlap):
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for x in range(0, s.shape[3], tile_x - overlap):
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s_in = s[:,:,y:y+tile_y,x:x+tile_x]
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ps = function(s_in).cpu()
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mask = torch.ones_like(ps)
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feather = overlap * upscale_amount
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feather = round(overlap * upscale_amount)
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for t in range(feather):
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mask[:,:,t:1+t,:] *= ((1.0/feather) * (t + 1))
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mask[:,:,mask.shape[2] -1 -t: mask.shape[2]-t,:] *= ((1.0/feather) * (t + 1))
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mask[:,:,:,t:1+t] *= ((1.0/feather) * (t + 1))
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mask[:,:,:,mask.shape[3]- 1 - t: mask.shape[3]- t] *= ((1.0/feather) * (t + 1))
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out[:,:,y*upscale_amount:(y+tile_y)*upscale_amount,x*upscale_amount:(x+tile_x)*upscale_amount] += ps * mask
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out_div[:,:,y*upscale_amount:(y+tile_y)*upscale_amount,x*upscale_amount:(x+tile_x)*upscale_amount] += mask
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out[:,:,round(y*upscale_amount):round((y+tile_y)*upscale_amount),round(x*upscale_amount):round((x+tile_x)*upscale_amount)] += ps * mask
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out_div[:,:,round(y*upscale_amount):round((y+tile_y)*upscale_amount),round(x*upscale_amount):round((x+tile_x)*upscale_amount)] += mask
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output[b:b+1] = out/out_div
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return output
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