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@@ -50,18 +50,18 @@ function pairwise_transform_utils.active_cropping(x, y, lowres_y, size, scale, p
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t = "byte"
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t = "byte"
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end
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end
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if p < r then
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if p < r then
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- local xi = torch.random(0, x:size(3) - (size + 1))
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- local yi = torch.random(0, x:size(2) - (size + 1))
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- local yc = iproc.crop(y, xi * scale, yi * scale, xi * scale + size, yi * scale + size)
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- local xc = iproc.crop(x, xi, yi, xi + size / scale, yi + size / scale)
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+ local xi = torch.random(1, x:size(3) - (size + 1)) * scale
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+ local yi = torch.random(1, x:size(2) - (size + 1)) * scale
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+ local yc = iproc.crop(y, xi, yi, xi + size, yi + size)
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+ local xc = iproc.crop(x, xi / scale, yi / scale, xi / scale + size / scale, yi / scale + size / scale)
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return xc, yc
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return xc, yc
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else
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else
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local best_se = 0.0
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local best_se = 0.0
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local best_xi, best_yi
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local best_xi, best_yi
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local m = torch.FloatTensor(y:size(1), size, size)
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local m = torch.FloatTensor(y:size(1), size, size)
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for i = 1, tries do
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for i = 1, tries do
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- local xi = torch.random(0, x:size(3) - (size + 1)) * scale
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- local yi = torch.random(0, x:size(2) - (size + 1)) * scale
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+ local xi = torch.random(1, x:size(3) - (size + 1)) * scale
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+ local yi = torch.random(1, x:size(2) - (size + 1)) * scale
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local xc = iproc.crop(y, xi, yi, xi + size, yi + size)
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local xc = iproc.crop(y, xi, yi, xi + size, yi + size)
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local lc = iproc.crop(lowres_y, xi, yi, xi + size, yi + size)
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local lc = iproc.crop(lowres_y, xi, yi, xi + size, yi + size)
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local xcf = iproc.byte2float(xc)
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local xcf = iproc.byte2float(xc)
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