Add resize_blur parameter

latest graphicsmagick is required

lib/iproc.lua

@@ -48,7 +48,7 @@ function iproc.float2byte(src)
    end
    return dest, conversion
 end
-function iproc.scale(src, width, height, filter)
+function iproc.scale(src, width, height, filter, blur)
    local conversion, color
    src, conversion = iproc.byte2float(src)
    filter = filter or "Box"
@@ -58,20 +58,20 @@ function iproc.scale(src, width, height, filter)
       color = "I"
    end
    local im = gm.Image(src, color, "DHW")
-   im:size(math.ceil(width), math.ceil(height), filter)
+   im:size(math.ceil(width), math.ceil(height), filter, blur)
    local dest = im:toTensor("float", color, "DHW")
    if conversion then
       dest = iproc.float2byte(dest)
    end
    return dest
 end
-function iproc.scale_with_gamma22(src, width, height, filter)
+function iproc.scale_with_gamma22(src, width, height, filter, blur)
    local conversion
    src, conversion = iproc.byte2float(src)
    filter = filter or "Box"
    local im = gm.Image(src, "RGB", "DHW")
    im:gammaCorrection(1.0 / 2.2):
-      size(math.ceil(width), math.ceil(height), filter):
+      size(math.ceil(width), math.ceil(height), filter, blur):
       gammaCorrection(2.2)
    local dest = im:toTensor("float", "RGB", "DHW"):clamp(0.0, 1.0)
    if conversion then

lib/pairwise_transform_scale.lua

@@ -6,13 +6,14 @@ function pairwise_transform.scale(src, scale, size, offset, n, options)
    local filters = options.downsampling_filters
    local unstable_region_offset = 8
    local downsampling_filter = filters[torch.random(1, #filters)]
+   local blur = torch.uniform(options.resize_blur_min, options.resize_blur_max)
    local y = pairwise_utils.preprocess(src, size, 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)
+					     y:size(2) * down_scale, downsampling_filter, blur)
       if options.x_upsampling then
 	 x = iproc.scale(small, y:size(3), y:size(2), options.upsampling_filter)
       else
@@ -20,7 +21,7 @@ function pairwise_transform.scale(src, scale, size, offset, n, options)
       end
    else
       local small = iproc.scale(y, y:size(3) * down_scale,
-				  y:size(2) * down_scale, downsampling_filter)
+				  y:size(2) * down_scale, downsampling_filter, blur)
       if options.x_upsampling then
 	 x = iproc.scale(small, y:size(3), y:size(2), options.upsampling_filter)
       else

lib/settings.lua

@@ -54,6 +54,8 @@ cmd:option("-gamma_correction", 0, 'Resizing with colorspace correction(sRGB:gam
 cmd:option("-upsampling_filter", "Box", 'upsampling filter for 2x scale training (dev)')
 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", 0.85, 'min blur parameter for ResizeImage')
+cmd:option("-resize_blur_max", 1.05, 'max blur parameter for ResizeImage')
 
 local function to_bool(settings, name)
    if settings[name] == 1 then

train.lua

@@ -149,7 +149,9 @@ local function transformer(model, x, is_validation, n, offset)
 					 active_cropping_tries = active_cropping_tries,
 					 rgb = (settings.color == "rgb"),
 					 gamma_correction = settings.gamma_correction,
-					 x_upsampling = not reconstruct.has_resize(model)
+					 x_upsampling = not reconstruct.has_resize(model),
+					 resize_blur_min = settings.resize_blur_min,
+					 resize_blur_max = settings.resize_blur_max,
 				      })
    elseif settings.method == "noise" then
       return pairwise_transform.jpeg(x,