Added ability to resume Video Upscaling
You can stop the Video Upscaling by sending "Ctrl + C" to the terminal. Then simply run the same command again to start video upscaling, and it will skip all frames already processed.
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parent
bf22c84e4a
commit
c48c3eb017
83
waifu2x.lua
83
waifu2x.lua
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@ -15,7 +15,6 @@ local function convert_image(opt)
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local x = 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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@ -23,8 +22,7 @@ local function convert_image(opt)
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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,
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("noise%d_model.t7"):format(opt.noise_level)), "ascii")
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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)
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elseif opt.m == "scale" then
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@ -32,8 +30,7 @@ local function convert_image(opt)
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model:evaluate()
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new_x = reconstruct.scale(model, opt.scale, x, BLOCK_OFFSET)
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elseif opt.m == "noise_scale" then
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local noise_model = torch.load(path.join(opt.model_dir,
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("noise%d_model.t7"):format(opt.noise_level)), "ascii")
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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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@ -62,37 +59,51 @@ local function convert_frames(opt)
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end
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fp:close()
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for i = 1, #lines do
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local x = 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)
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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)
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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)
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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)
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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.save(output, new_x)
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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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if file_exists(string.format(opt.o, i)) == false then
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local x = 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)
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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)
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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)
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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)
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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.save(output, new_x)
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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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function file_exists(name)
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local f=io.open(name,"r")
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if f~=nil then
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io.close(f)
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return true
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else
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return false
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end
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end
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