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							- local w2nn = require 'w2nn'
 
- local reconstruct = require 'reconstruct'
 
- local image = require 'image'
 
- local iproc = require 'iproc'
 
- local gm = require 'graphicsmagick'
 
- alpha_util = {}
 
- function alpha_util.make_border(rgb, alpha, offset)
 
-    if not alpha then
 
-       return rgb
 
-    end
 
-    local sum2d = nn.SpatialConvolutionMM(1, 1, 3, 3, 1, 1, 1, 1):cuda()
 
-    sum2d.weight:fill(1)
 
-    sum2d.bias:zero()
 
-    local mask = alpha:clone()
 
-    mask[torch.gt(mask, 0.0)] = 1
 
-    mask[torch.eq(mask, 0.0)] = 0
 
-    local mask_nega = (mask - 1):abs():byte()
 
-    local eps = 1.0e-7
 
-    rgb = rgb:clone()
 
-    rgb[1][mask_nega] = 0
 
-    rgb[2][mask_nega] = 0
 
-    rgb[3][mask_nega] = 0
 
-    for i = 1, offset do
 
-       local mask_weight = sum2d:forward(mask:cuda()):float()
 
-       local border = rgb:clone()
 
-       for j = 1, 3 do
 
- 	 border[j]:copy(sum2d:forward(rgb[j]:reshape(1, rgb:size(2), rgb:size(3)):cuda()))
 
- 	 border[j]:cdiv((mask_weight + eps))
 
- 	 rgb[j][mask_nega] = border[j][mask_nega]
 
-       end
 
-       mask = mask_weight:clone()
 
-       mask[torch.gt(mask_weight, 0.0)] = 1
 
-       mask_nega = (mask - 1):abs():byte()
 
-       if border:size(2) * border:size(3) > 1024*1024 then
 
- 	 collectgarbage()
 
-       end
 
-    end
 
-    rgb[torch.gt(rgb, 1.0)] = 1.0
 
-    rgb[torch.lt(rgb, 0.0)] = 0.0
 
-    return rgb
 
- end
 
- function alpha_util.composite(rgb, alpha, model2x)
 
-    if not alpha then
 
-       return rgb
 
-    end
 
-    if not (alpha:size(2) == rgb:size(2) and  alpha:size(3) == rgb:size(3)) then
 
-       if model2x then
 
- 	 alpha = reconstruct.scale(model2x, 2.0, alpha)
 
-       else
 
- 	 alpha = gm.Image(alpha, "I", "DHW"):size(rgb:size(3), rgb:size(2), "Sinc"):toTensor("float", "I", "DHW")
 
-       end
 
-    end
 
-    local out = torch.Tensor(4, rgb:size(2), rgb:size(3))
 
-    out[1]:copy(rgb[1])
 
-    out[2]:copy(rgb[2])
 
-    out[3]:copy(rgb[3])
 
-    out[4]:copy(alpha)
 
-    return out
 
- end
 
- local function test()
 
-    require 'sys'
 
-    require 'trepl'
 
-    torch.setdefaulttensortype("torch.FloatTensor")
 
-    local image_loader = require 'image_loader'
 
-    local rgb, alpha = image_loader.load_float("alpha.png")
 
-    local t = sys.clock()
 
-    rgb = alpha_util.make_border(rgb, alpha, 7)
 
-    print(sys.clock() - t)
 
-    print(rgb:min(), rgb:max())
 
-    image.display({image = rgb, min = 0, max = 1})
 
-    image.save("out.png", rgb)
 
- end
 
- --test()
 
- return alpha_util
 
 
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