cyclegan

cyclegan/util/VGG_preprocess.lua

@@ -0,0 +1,27 @@
+-- define nn module for VGG postprocessing
+local VGG_postprocess, parent = torch.class('nn.VGG_postprocess', 'nn.Module')
+
+function VGG_postprocess:__init()
+	parent.__init(self)
+end
+
+function VGG_postprocess:updateOutput(input)
+  self.output = input:add(1):mul(127.5)
+	-- print(self.output:max(), self.output:min())
+	if self.output:max() > 255 or self.output:min() < 0 then
+		print(self.output:min(), self.output:max())
+	end
+	-- assert(self.output:min()>=0,"badly scaled inputs")
+  -- assert(self.output:max()<=255,"badly scaled inputs")
+
+	local mean_pixel = torch.FloatTensor({103.939, 116.779, 123.68})
+	mean_pixel = mean_pixel:reshape(1,3,1,1)
+	mean_pixel = mean_pixel:repeatTensor(input:size(1), 1, input:size(3), input:size(4)):cuda()
+	self.output:add(-1, mean_pixel)
+	return self.output
+end
+
+function VGG_postprocess:updateGradInput(input, gradOutput)
+	self.gradInput = gradOutput:div(127.5)
+	return self.gradInput
+end