Remove -gamma_correction option

lib/pairwise_transform_jpeg_scale.lua

@@ -63,22 +63,12 @@ function pairwise_transform.jpeg_scale(src, scale, style, noise_level, size, off
    assert(y:size(2) % 4 == 0 and y:size(3) % 4 == 0)
    local down_scale = 1.0 / scale
    local x
-   if options.gamma_correction then
-      local small = iproc.scale_with_gamma22(y, y:size(3) * down_scale,
-					     y:size(2) * down_scale, downsampling_filter, blur)
-      if options.x_upsampling then
-	 x = iproc.scale(small, y:size(3), y:size(2), "Box")
-      else
-	 x = small
-      end
+   local small = iproc.scale(y, y:size(3) * down_scale,
+			     y:size(2) * down_scale, downsampling_filter, blur)
+   if options.x_upsampling then
+      x = iproc.scale(small, y:size(3), y:size(2), "Box")
    else
-      local small = iproc.scale(y, y:size(3) * down_scale,
-				  y:size(2) * down_scale, downsampling_filter, blur)
-      if options.x_upsampling then
-	 x = iproc.scale(small, y:size(3), y:size(2), "Box")
-      else
-	 x = small
-      end
+      x = small
    end
    local scale_inner = scale
    if options.x_upsampling then

lib/pairwise_transform_scale.lua

@@ -15,22 +15,12 @@ function pairwise_transform.scale(src, scale, size, offset, n, options)
    assert(y:size(2) % 4 == 0 and y:size(3) % 4 == 0)
    local down_scale = 1.0 / scale
    local x
-   if options.gamma_correction then
-      local small = iproc.scale_with_gamma22(y, y:size(3) * down_scale,
-					     y:size(2) * down_scale, downsampling_filter, blur)
-      if options.x_upsampling then
-	 x = iproc.scale(small, y:size(3), y:size(2), "Box")
-      else
-	 x = small
-      end
-   else
-      local small = iproc.scale(y, y:size(3) * down_scale,
+   local small = iproc.scale(y, y:size(3) * down_scale,
 				  y:size(2) * down_scale, downsampling_filter, blur)
-      if options.x_upsampling then
-	 x = iproc.scale(small, y:size(3), y:size(2), "Box")
-      else
-	 x = small
-      end
+   if options.x_upsampling then
+      x = iproc.scale(small, y:size(3), y:size(2), "Box")
+   else
+      x = small
    end
    local scale_inner = scale
    if options.x_upsampling then

lib/settings.lua

@@ -50,7 +50,6 @@ cmd:option("-nr_rate", 0.75, 'trade-off between reducing noise and erasing detai
 cmd:option("-save_history", 0, 'save all model (0|1)')
 cmd:option("-plot", 0, 'plot loss chart(0|1)')
 cmd:option("-downsampling_filters", "Box,Lanczos,Sinc", '(comma separated)downsampling filters for 2x scale training. (Point,Box,Triangle,Hermite,Hanning,Hamming,Blackman,Gaussian,Quadratic,Cubic,Catrom,Mitchell,Lanczos,Bessel,Sinc)')
-cmd:option("-gamma_correction", 0, 'Resizing with colorspace correction(sRGB:gamma 2.2) in scale training (0|1)')
 cmd:option("-max_training_image_size", -1, 'if training image is larger than N, image will be crop randomly when data converting')
 cmd:option("-use_transparent_png", 0, 'use transparent png (0|1)')
 cmd:option("-resize_blur_min", 0.95, 'min blur parameter for ResizeImage')
@@ -75,7 +74,6 @@ for k, v in pairs(opt) do
 end
 to_bool(settings, "plot")
 to_bool(settings, "save_history")
-to_bool(settings, "gamma_correction")
 to_bool(settings, "use_transparent_png")
 
 if settings.plot then

tools/benchmark.lua

@@ -26,7 +26,6 @@ cmd:option("-jpeg_quality", 75, 'jpeg quality')
 cmd:option("-jpeg_times", 1, 'jpeg compression times')
 cmd:option("-jpeg_quality_down", 5, 'value of jpeg quality to decrease each times')
 cmd:option("-range_bug", 0, 'Reproducing the dynamic range bug that is caused by MATLAB\'s rgb2ycbcr(1|0)')
-cmd:option("-gamma_correction", 0, 'Resizing with colorspace correction(sRGB:gamma 2.2) (0|1)')
 cmd:option("-save_image", 0, 'save converted images')
 cmd:option("-save_baseline_image", 0, 'save baseline images')
 cmd:option("-output_dir", "./", 'output directroy')
@@ -50,7 +49,6 @@ if cudnn then
    cudnn.fastest = true
    cudnn.benchmark = false
 end
-to_bool(opt, "gamma_correction")
 to_bool(opt, "save_all")
 to_bool(opt, "tta")
 if opt.save_all then
@@ -122,17 +120,10 @@ local function baseline_scale(x, filter)
 		      filter)
 end
 local function transform_scale(x, opt)
-   if opt.gamma_correction then
-      return iproc.scale_with_gamma22(x,
-			 x:size(3) * 0.5,
-			 x:size(2) * 0.5,
-			 opt.filter, opt.resize_blur)
-   else
-      return iproc.scale(x,
-			 x:size(3) * 0.5,
-			 x:size(2) * 0.5,
-			 opt.filter, opt.resize_blur)
-   end
+   return iproc.scale(x,
+		      x:size(3) * 0.5,
+		      x:size(2) * 0.5,
+		      opt.filter, opt.resize_blur)
 end
 
 local function benchmark(opt, x, input_func, model1, model2)

train.lua

@@ -150,7 +150,6 @@ local function transformer(model, x, is_validation, n, offset)
 	    active_cropping_rate = active_cropping_rate,
 	    active_cropping_tries = active_cropping_tries,
 	    rgb = (settings.color == "rgb"),
-	    gamma_correction = settings.gamma_correction,
 	    x_upsampling = not reconstruct.has_resize(model),
 	    resize_blur_min = settings.resize_blur_min,
 	 resize_blur_max = settings.resize_blur_max}, meta)
@@ -188,7 +187,6 @@ local function transformer(model, x, is_validation, n, offset)
 	    active_cropping_rate = active_cropping_rate,
 	    active_cropping_tries = active_cropping_tries,
 	    rgb = (settings.color == "rgb"),
-	    gamma_correction = settings.gamma_correction,
 	    x_upsampling = not reconstruct.has_resize(model),
 	    resize_blur_min = settings.resize_blur_min,
 	    resize_blur_max = settings.resize_blur_max}, meta)