| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291 | require 'image'local gm = require 'graphicsmagick'local iproc = require './iproc'local reconstruct = require './reconstruct'local pairwise_transform = {}local function random_half(src, p, min_size)   p = p or 0.5   local filter = ({"Box","Blackman", "SincFast", "Jinc"})[torch.random(1, 4)]   if p > torch.uniform() then      return iproc.scale(src, src:size(3) * 0.5, src:size(2) * 0.5, filter)   else      return src   endendlocal function color_augment(x)   local color_scale = torch.Tensor(3):uniform(0.8, 1.2)   x = x:float():div(255)   for i = 1, 3 do      x[i]:mul(color_scale[i])   end   x[torch.lt(x, 0.0)] = 0.0   x[torch.gt(x, 1.0)] = 1.0   return x:mul(255):byte()endlocal function flip_augment(x, y)   local flip = torch.random(1, 4)   if y then      if flip == 1 then	 x = image.hflip(x)	 y = image.hflip(y)      elseif flip == 2 then	 x = image.vflip(x)	 y = image.vflip(y)      elseif flip == 3 then	 x = image.hflip(image.vflip(x))	 y = image.hflip(image.vflip(y))      elseif flip == 4 then      end      return x, y   else      if flip == 1 then	 x = image.hflip(x)      elseif flip == 2 then	 x = image.vflip(x)      elseif flip == 3 then	 x = image.hflip(image.vflip(x))      elseif flip == 4 then      end      return x   endendlocal INTERPOLATION_PADDING = 16function pairwise_transform.scale(src, scale, size, offset, options)   options = options or {color_augment = true, random_half = true, rgb = true}   if options.random_half then      src = random_half(src)   end   local yi = torch.random(INTERPOLATION_PADDING, src:size(2) - size - INTERPOLATION_PADDING)   local xi = torch.random(INTERPOLATION_PADDING, src:size(3) - size - INTERPOLATION_PADDING)   local down_scale = 1.0 / scale   local y = image.crop(src,			xi - INTERPOLATION_PADDING, yi - INTERPOLATION_PADDING,			xi + size + INTERPOLATION_PADDING, yi + size + INTERPOLATION_PADDING)   local filters = {      "Box",        -- 0.012756949974688      "Blackman",   -- 0.013191924552285      --"Cartom",     -- 0.013753536746706      --"Hanning",    -- 0.013761314529647      --"Hermite",    -- 0.013850225205266      "SincFast",   -- 0.014095824314306      "Jinc",       -- 0.014244299255442   }   local downscale_filter = filters[torch.random(1, #filters)]      y = flip_augment(y)   if options.color_augment then      y = color_augment(y)   end   local x = iproc.scale(y, y:size(3) * down_scale, y:size(2) * down_scale, downscale_filter)   x = iproc.scale(x, y:size(3), y:size(2))   y = y:float():div(255)   x = x:float():div(255)   if options.rgb then   else      y = image.rgb2yuv(y)[1]:reshape(1, y:size(2), y:size(3))      x = image.rgb2yuv(x)[1]:reshape(1, x:size(2), x:size(3))   end   y = image.crop(y, INTERPOLATION_PADDING + offset, INTERPOLATION_PADDING + offset, y:size(3) - offset -	INTERPOLATION_PADDING, y:size(2) - offset - INTERPOLATION_PADDING)   x = image.crop(x, INTERPOLATION_PADDING, INTERPOLATION_PADDING, x:size(3) - INTERPOLATION_PADDING, x:size(2) - INTERPOLATION_PADDING)      return x, yendfunction pairwise_transform.jpeg_(src, quality, size, offset, options)   options = options or {color_augment = true, random_half = true, rgb = true}   if options.random_half then      src = random_half(src)   end   local yi = torch.random(0, src:size(2) - size - 1)   local xi = torch.random(0, src:size(3) - size - 1)   local y = src   local x   if options.color_augment then      y = color_augment(y)   end   x = y   for i = 1, #quality do      x = gm.Image(x, "RGB", "DHW")      x:format("jpeg")      x:samplingFactors({1.0, 1.0, 1.0})      local blob, len = x:toBlob(quality[i])      x:fromBlob(blob, len)      x = x:toTensor("byte", "RGB", "DHW")   end      y = image.crop(y, xi, yi, xi + size, yi + size)   x = image.crop(x, xi, yi, xi + size, yi + size)   y = y:float():div(255)   x = x:float():div(255)   x, y = flip_augment(x, y)      if options.rgb then   else      y = image.rgb2yuv(y)[1]:reshape(1, y:size(2), y:size(3))      x = image.rgb2yuv(x)[1]:reshape(1, x:size(2), x:size(3))   end      return x, image.crop(y, offset, offset, size - offset, size - offset)endfunction pairwise_transform.jpeg(src, level, size, offset, options)   if level == 1 then      return pairwise_transform.jpeg_(src, {torch.random(65, 85)},				      size, offset,				      options)   elseif level == 2 then      local r = torch.uniform()      if r > 0.6 then	 return pairwise_transform.jpeg_(src, {torch.random(27, 70)},					 size, offset,					 options)      elseif r > 0.3 then	 local quality1 = torch.random(37, 70)	 local quality2 = quality1 - torch.random(5, 10)	 return pairwise_transform.jpeg_(src, {quality1, quality2},					    size, offset,					    options)      else	 local quality1 = torch.random(52, 70)	 return pairwise_transform.jpeg_(src,					 {quality1,					  quality1 - torch.random(5, 15),					  quality1 - torch.random(15, 25)},					 size, offset,					 options)      end   else      error("unknown noise level: " .. level)   endendfunction pairwise_transform.jpeg_scale_(src, scale, quality, size, offset, options)   if options.random_half then      src = random_half(src)   end   local down_scale = 1.0 / scale   local filters = {      "Box",        -- 0.012756949974688      "Blackman",   -- 0.013191924552285      --"Cartom",     -- 0.013753536746706      --"Hanning",    -- 0.013761314529647      --"Hermite",    -- 0.013850225205266      "SincFast",   -- 0.014095824314306      "Jinc",       -- 0.014244299255442   }   local downscale_filter = filters[torch.random(1, #filters)]   local yi = torch.random(INTERPOLATION_PADDING, src:size(2) - size - INTERPOLATION_PADDING)   local xi = torch.random(INTERPOLATION_PADDING, src:size(3) - size - INTERPOLATION_PADDING)   local y = src   local x      if options.color_augment then      y = color_augment(y)   end   x = y   x = iproc.scale(x, y:size(3) * down_scale, y:size(2) * down_scale, downscale_filter)   for i = 1, #quality do      x = gm.Image(x, "RGB", "DHW")      x:format("jpeg")      x:samplingFactors({1.0, 1.0, 1.0})      local blob, len = x:toBlob(quality[i])      x:fromBlob(blob, len)      x = x:toTensor("byte", "RGB", "DHW")   end   x = iproc.scale(x, y:size(3), y:size(2))   y = image.crop(y,		  xi, yi,		  xi + size, yi + size)   x = image.crop(x,		  xi, yi,		  xi + size, yi + size)   x = x:float():div(255)   y = y:float():div(255)   x, y = flip_augment(x, y)   if options.rgb then   else      y = image.rgb2yuv(y)[1]:reshape(1, y:size(2), y:size(3))      x = image.rgb2yuv(x)[1]:reshape(1, x:size(2), x:size(3))   end      return x, image.crop(y, offset, offset, size - offset, size - offset)endfunction pairwise_transform.jpeg_scale(src, scale, level, size, offset, options)   options = options or {color_augment = true, random_half = true}   if level == 1 then      return pairwise_transform.jpeg_scale_(src, scale, {torch.random(65, 85)},					    size, offset, options)   elseif level == 2 then      local r = torch.uniform()      if r > 0.6 then	 return pairwise_transform.jpeg_scale_(src, scale, {torch.random(27, 70)},					       size, offset, options)      elseif r > 0.3 then	 local quality1 = torch.random(37, 70)	 local quality2 = quality1 - torch.random(5, 10)	 return pairwise_transform.jpeg_scale_(src, scale, {quality1, quality2},					       size, offset, options)      else	 local quality1 = torch.random(52, 70)	    return pairwise_transform.jpeg_scale_(src, scale,						  {quality1,						   quality1 - torch.random(5, 15),						   quality1 - torch.random(15, 25)},						  size, offset, options)      end   else      error("unknown noise level: " .. level)   endendlocal function test_jpeg()   local loader = require './image_loader'   local src = loader.load_byte("../images/miku_CC_BY-NC.jpg")   local y, x = pairwise_transform.jpeg_(src, {}, 128, 0, false)   image.display({image = y, legend = "y:0"})   image.display({image = x, legend = "x:0"})   for i = 2, 9 do      local y, x = pairwise_transform.jpeg_(pairwise_transform.random_half(src),					    {i * 10}, 128, 0, {color_augment = false, random_half = true})      image.display({image = y, legend = "y:" .. (i * 10), max=1,min=0})      image.display({image = x, legend = "x:" .. (i * 10),max=1,min=0})      --print(x:mean(), y:mean())   endendlocal function test_scale()   local loader = require './image_loader'   local src = loader.load_byte("../images/miku_CC_BY-NC.jpg")      for i = 1, 9 do      local y, x = pairwise_transform.scale(src, 2.0, 128, 7, {color_augment = true, random_half = true, rgb = true})      image.display({image = y, legend = "y:" .. (i * 10), min = 0, max = 1})      image.display({image = x, legend = "x:" .. (i * 10), min = 0, max = 1})      print(y:size(), x:size())      --print(x:mean(), y:mean())   endendlocal function test_jpeg_scale()   local loader = require './image_loader'   local src = loader.load_byte("../images/miku_CC_BY-NC.jpg")      for i = 1, 9 do      local y, x = pairwise_transform.jpeg_scale(src, 2.0, 1, 128, 7, {color_augment = true, random_half = true})      image.display({image = y, legend = "y1:" .. (i * 10), min = 0, max = 1})      image.display({image = x, legend = "x1:" .. (i * 10), min = 0, max = 1})      print(y:size(), x:size())      --print(x:mean(), y:mean())   end   for i = 1, 9 do      local y, x = pairwise_transform.jpeg_scale(src, 2.0, 2, 128, 7, {color_augment = true, random_half = true})      image.display({image = y, legend = "y2:" .. (i * 10), min = 0, max = 1})      image.display({image = x, legend = "x2:" .. (i * 10), min = 0, max = 1})      print(y:size(), x:size())      --print(x:mean(), y:mean())   endend--test_scale()--test_jpeg()--test_jpeg_scale()return pairwise_transform
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