Add support for new noise_scale method
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parent
6c758ec5c0
commit
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88
waifu2x.lua
88
waifu2x.lua
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@ -73,23 +73,41 @@ local function convert_image(opt)
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new_x = alpha_util.composite(new_x, alpha, model)
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new_x = alpha_util.composite(new_x, alpha, model)
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print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
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print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
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elseif opt.m == "noise_scale" then
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elseif opt.m == "noise_scale" then
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local noise_model_path = path.join(opt.model_dir, ("noise%d_model.t7"):format(opt.noise_level))
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local model_path = path.join(opt.model_dir, ("noise%d_scale%.1fx_model.t7"):format(opt.noise_level, opt.scale))
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local noise_model = torch.load(noise_model_path, "ascii")
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if path.exists(model_path) then
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local scale_model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
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local scale_model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
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local scale_model = torch.load(scale_model_path, "ascii")
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local scale_model = torch.load(scale_model_path, "ascii")
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local model = torch.load(model_path, "ascii")
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if not model then
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error("Load Error: " .. model_path)
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end
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if not scale_model then
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error("Load Error: " .. model_path)
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end
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local t = sys.clock()
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x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
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new_x = scale_f(model, opt.scale, x, opt.crop_size, opt.upsampling_filter)
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new_x = alpha_util.composite(new_x, alpha, scale_model)
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print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
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else
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local noise_model_path = path.join(opt.model_dir, ("noise%d_model.t7"):format(opt.noise_level))
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local noise_model = torch.load(noise_model_path, "ascii")
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local scale_model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
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local scale_model = torch.load(scale_model_path, "ascii")
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if not noise_model then
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if not noise_model then
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error("Load Error: " .. noise_model_path)
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error("Load Error: " .. noise_model_path)
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end
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if not scale_model then
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error("Load Error: " .. scale_model_path)
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end
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local t = sys.clock()
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x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
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x = image_f(noise_model, x, opt.crop_size)
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new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, opt.upsampling_filter)
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new_x = alpha_util.composite(new_x, alpha, scale_model)
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print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
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end
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end
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if not scale_model then
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error("Load Error: " .. scale_model_path)
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end
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local t = sys.clock()
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x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
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x = image_f(noise_model, x, opt.crop_size)
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new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, opt.upsampling_filter)
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new_x = alpha_util.composite(new_x, alpha, scale_model)
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print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
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else
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else
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error("undefined method:" .. opt.method)
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error("undefined method:" .. opt.method)
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end
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end
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@ -97,6 +115,7 @@ local function convert_image(opt)
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end
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end
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local function convert_frames(opt)
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local function convert_frames(opt)
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local model_path, scale_model
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local model_path, scale_model
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local noise_scale_model = {}
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local noise_model = {}
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local noise_model = {}
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local scale_f, image_f
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local scale_f, image_f
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if opt.tta == 1 then
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if opt.tta == 1 then
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@ -119,15 +138,28 @@ local function convert_frames(opt)
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error("Load Error: " .. model_path)
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error("Load Error: " .. model_path)
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end
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end
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elseif opt.m == "noise_scale" then
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elseif opt.m == "noise_scale" then
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model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
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local model_path = path.join(opt.model_dir, ("noise%d_scale%.1fx_model.t7"):format(opt.noise_level, opt.scale))
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scale_model = torch.load(model_path, "ascii")
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if path.exists(model_path) then
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if not scale_model then
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noise_scale_model[opt.noise_level] = torch.load(model_path, "ascii")
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error("Load Error: " .. model_path)
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if not noise_scale_model[opt.noise_level] then
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end
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error("Load Error: " .. model_path)
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model_path = path.join(opt.model_dir, string.format("noise%d_model.t7", opt.noise_level))
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end
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noise_model[opt.noise_level] = torch.load(model_path, "ascii")
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model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
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if not noise_model[opt.noise_level] then
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scale_model = torch.load(model_path, "ascii")
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error("Load Error: " .. model_path)
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if not scale_model then
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error("Load Error: " .. model_path)
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end
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else
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model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
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scale_model = torch.load(model_path, "ascii")
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if not scale_model then
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error("Load Error: " .. model_path)
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end
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model_path = path.join(opt.model_dir, string.format("noise%d_model.t7", opt.noise_level))
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noise_model[opt.noise_level] = torch.load(model_path, "ascii")
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if not noise_model[opt.noise_level] then
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error("Load Error: " .. model_path)
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end
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end
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end
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end
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end
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local fp = io.open(opt.l)
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local fp = io.open(opt.l)
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@ -155,8 +187,12 @@ local function convert_frames(opt)
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new_x = alpha_util.composite(new_x, alpha, scale_model)
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new_x = alpha_util.composite(new_x, alpha, scale_model)
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elseif opt.m == "noise_scale" then
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elseif opt.m == "noise_scale" then
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x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
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x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
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x = image_f(noise_model[opt.noise_level], x, opt.crop_size)
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if noise_scale_model[opt.noise_level] then
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new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, upsampling_filter)
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new_x = scale_f(noise_scale_model[opt.noise_level], opt.scale, x, opt.crop_size, upsampling_filter)
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else
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x = image_f(noise_model[opt.noise_level], x, opt.crop_size)
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new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, upsampling_filter)
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end
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new_x = alpha_util.composite(new_x, alpha, scale_model)
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new_x = alpha_util.composite(new_x, alpha, scale_model)
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else
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else
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error("undefined method:" .. opt.method)
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error("undefined method:" .. opt.method)
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