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