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							- require './lib/portable'
 
- require 'sys'
 
- require 'pl'
 
- require './lib/LeakyReLU'
 
- local iproc = require './lib/iproc'
 
- local reconstruct = require './lib/reconstruct'
 
- local image_loader = require './lib/image_loader'
 
- local BLOCK_OFFSET = 7
 
- torch.setdefaulttensortype('torch.FloatTensor')
 
- local function convert_image(opt)
 
-    local x, alpha = image_loader.load_float(opt.i)
 
-    local new_x = nil
 
-    local t = sys.clock()
 
-    if opt.o == "(auto)" then
 
-       local name = path.basename(opt.i)
 
-       local e = path.extension(name)
 
-       local base = name:sub(0, name:len() - e:len())
 
-       opt.o = path.join(path.dirname(opt.i), string.format("%s(%s).png", base, opt.m))
 
-    end
 
-    if opt.m == "noise" then
 
-       local model = torch.load(path.join(opt.model_dir, ("noise%d_model.t7"):format(opt.noise_level)), "ascii")
 
-       model:evaluate()
 
-       new_x = reconstruct.image(model, x, BLOCK_OFFSET, opt.crop_size)
 
-    elseif opt.m == "scale" then
 
-       local model = torch.load(path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale)), "ascii")
 
-       model:evaluate()
 
-       new_x = reconstruct.scale(model, opt.scale, x, BLOCK_OFFSET, opt.crop_size)
 
-    elseif opt.m == "noise_scale" then
 
-       local noise_model = torch.load(path.join(opt.model_dir, ("noise%d_model.t7"):format(opt.noise_level)), "ascii")
 
-       local scale_model = torch.load(path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale)), "ascii")
 
-       noise_model:evaluate()
 
-       scale_model:evaluate()
 
-       x = reconstruct.image(noise_model, x, BLOCK_OFFSET)
 
-       new_x = reconstruct.scale(scale_model, opt.scale, x, BLOCK_OFFSET, opt.crop_size)
 
-    else
 
-       error("undefined method:" .. opt.method)
 
-    end
 
-    image_loader.save_png(opt.o, new_x, alpha)
 
-    print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
 
- end
 
- local function convert_frames(opt)
 
-    local noise1_model = torch.load(path.join(opt.model_dir, "noise1_model.t7"), "ascii")
 
-    local noise2_model = torch.load(path.join(opt.model_dir, "noise2_model.t7"), "ascii")
 
-    local scale_model = torch.load(path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale)), "ascii")
 
-    noise1_model:evaluate()
 
-    noise2_model:evaluate()
 
-    scale_model:evaluate()
 
-    
 
-    local fp = io.open(opt.l)
 
-    local count = 0
 
-    local lines = {}
 
-    for line in fp:lines() do
 
-       table.insert(lines, line)
 
-    end
 
-    fp:close()
 
-    for i = 1, #lines do
 
-       if opt.resume == 0 or path.exists(string.format(opt.o, i)) == false then
 
- 	 local x, alpha = image_loader.load_float(lines[i])
 
- 	 local new_x = nil
 
- 	 if opt.m == "noise" and opt.noise_level == 1 then
 
- 	    new_x = reconstruct.image(noise1_model, x, BLOCK_OFFSET, opt.crop_size)
 
- 	 elseif opt.m == "noise" and opt.noise_level == 2 then
 
- 	    new_x = reconstruct.image(noise2_model, x, BLOCK_OFFSET)
 
- 	 elseif opt.m == "scale" then
 
- 	    new_x = reconstruct.scale(scale_model, opt.scale, x, BLOCK_OFFSET, opt.crop_size)
 
- 	 elseif opt.m == "noise_scale" and opt.noise_level == 1 then
 
- 	    x = reconstruct.image(noise1_model, x, BLOCK_OFFSET)
 
- 	    new_x = reconstruct.scale(scale_model, opt.scale, x, BLOCK_OFFSET, opt.crop_size)
 
- 	 elseif opt.m == "noise_scale" and opt.noise_level == 2 then
 
- 	    x = reconstruct.image(noise2_model, x, BLOCK_OFFSET)
 
- 	    new_x = reconstruct.scale(scale_model, opt.scale, x, BLOCK_OFFSET, opt.crop_size)
 
- 	 else
 
- 	    error("undefined method:" .. opt.method)
 
- 	 end
 
- 	 local output = nil
 
- 	 if opt.o == "(auto)" then
 
- 	    local name = path.basename(lines[i])
 
- 	    local e = path.extension(name)
 
- 	    local base = name:sub(0, name:len() - e:len())
 
- 	    output = path.join(path.dirname(opt.i), string.format("%s(%s).png", base, opt.m))
 
- 	 else
 
- 	    output = string.format(opt.o, i)
 
- 	 end
 
- 	 image_loader.save_png(output, new_x, alpha)
 
- 	 xlua.progress(i, #lines)
 
- 	 if i % 10 == 0 then
 
- 	    collectgarbage()
 
- 	 end
 
-       else
 
- 	 xlua.progress(i, #lines)
 
-       end
 
-    end
 
- end
 
- local function waifu2x()
 
-    local cmd = torch.CmdLine()
 
-    cmd:text()
 
-    cmd:text("waifu2x")
 
-    cmd:text("Options:")
 
-    cmd:option("-i", "images/miku_small.png", 'path of the input image')
 
-    cmd:option("-l", "", 'path of the image-list')
 
-    cmd:option("-scale", 2, 'scale factor')
 
-    cmd:option("-o", "(auto)", 'path of the output file')
 
-    cmd:option("-model_dir", "./models/anime_style_art_rgb", 'model directory')
 
-    cmd:option("-m", "noise_scale", 'method (noise|scale|noise_scale)')
 
-    cmd:option("-noise_level", 1, '(1|2)')
 
-    cmd:option("-crop_size", 128, 'patch size per process')
 
-    cmd:option("-resume", 0, "skip existing files (0|1)")
 
-    
 
-    local opt = cmd:parse(arg)
 
-    if string.len(opt.l) == 0 then
 
-       convert_image(opt)
 
-    else
 
-       convert_frames(opt)
 
-    end
 
- end
 
- waifu2x()
 
 
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