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Add support for new noise_scale method

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nagadomi 2016-06-08 09:32:27 +09:00
parent 6c758ec5c0
commit 37bc7a5eea
1 changed files with 63 additions and 27 deletions
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90
waifu2x.lua
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@ -73,23 +73,41 @@ local function convert_image(opt)
new_x = alpha_util.composite(new_x, alpha, model)
print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
elseif opt.m == "noise_scale" then
local noise_model_path = path.join(opt.model_dir, ("noise%d_model.t7"):format(opt.noise_level))
local noise_model = torch.load(noise_model_path, "ascii")
local scale_model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
local scale_model = torch.load(scale_model_path, "ascii")
if not noise_model then
error("Load Error: " .. noise_model_path)
local model_path = path.join(opt.model_dir, ("noise%d_scale%.1fx_model.t7"):format(opt.noise_level, opt.scale))
if path.exists(model_path) then
local scale_model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
local scale_model = torch.load(scale_model_path, "ascii")
local model = torch.load(model_path, "ascii")
if not model then
error("Load Error: " .. model_path)
end
if not scale_model then
error("Load Error: " .. model_path)
end
local t = sys.clock()
x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
new_x = scale_f(model, opt.scale, x, opt.crop_size, opt.upsampling_filter)
new_x = alpha_util.composite(new_x, alpha, scale_model)
print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
else
local noise_model_path = path.join(opt.model_dir, ("noise%d_model.t7"):format(opt.noise_level))
local noise_model = torch.load(noise_model_path, "ascii")
local scale_model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
local scale_model = torch.load(scale_model_path, "ascii")
if not noise_model then
error("Load Error: " .. noise_model_path)
end
if not scale_model then
error("Load Error: " .. scale_model_path)
end
local t = sys.clock()
x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
x = image_f(noise_model, x, opt.crop_size)
new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, opt.upsampling_filter)
new_x = alpha_util.composite(new_x, alpha, scale_model)
print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
end
if not scale_model then
error("Load Error: " .. scale_model_path)
end
local t = sys.clock()
x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
x = image_f(noise_model, x, opt.crop_size)
new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, opt.upsampling_filter)
new_x = alpha_util.composite(new_x, alpha, scale_model)
print(opt.o .. ": " .. (sys.clock() - t) .. " sec")
else
error("undefined method:" .. opt.method)
end
@ -97,6 +115,7 @@ local function convert_image(opt)
end
local function convert_frames(opt)
local model_path, scale_model
local noise_scale_model = {}
local noise_model = {}
local scale_f, image_f
if opt.tta == 1 then
@ -119,15 +138,28 @@ local function convert_frames(opt)
error("Load Error: " .. model_path)
end
elseif opt.m == "noise_scale" then
model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
scale_model = torch.load(model_path, "ascii")
if not scale_model then
error("Load Error: " .. model_path)
end
model_path = path.join(opt.model_dir, string.format("noise%d_model.t7", opt.noise_level))
noise_model[opt.noise_level] = torch.load(model_path, "ascii")
if not noise_model[opt.noise_level] then
error("Load Error: " .. model_path)
local model_path = path.join(opt.model_dir, ("noise%d_scale%.1fx_model.t7"):format(opt.noise_level, opt.scale))
if path.exists(model_path) then
noise_scale_model[opt.noise_level] = torch.load(model_path, "ascii")
if not noise_scale_model[opt.noise_level] then
error("Load Error: " .. model_path)
end
model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
scale_model = torch.load(model_path, "ascii")
if not scale_model then
error("Load Error: " .. model_path)
end
else
model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
scale_model = torch.load(model_path, "ascii")
if not scale_model then
error("Load Error: " .. model_path)
end
model_path = path.join(opt.model_dir, string.format("noise%d_model.t7", opt.noise_level))
noise_model[opt.noise_level] = torch.load(model_path, "ascii")
if not noise_model[opt.noise_level] then
error("Load Error: " .. model_path)
end
end
end
local fp = io.open(opt.l)
@ -155,8 +187,12 @@ local function convert_frames(opt)
new_x = alpha_util.composite(new_x, alpha, scale_model)
elseif opt.m == "noise_scale" then
x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
x = image_f(noise_model[opt.noise_level], x, opt.crop_size)
new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, upsampling_filter)
if noise_scale_model[opt.noise_level] then
new_x = scale_f(noise_scale_model[opt.noise_level], opt.scale, x, opt.crop_size, upsampling_filter)
else
x = image_f(noise_model[opt.noise_level], x, opt.crop_size)
new_x = scale_f(scale_model, opt.scale, x, opt.crop_size, upsampling_filter)
end
new_x = alpha_util.composite(new_x, alpha, scale_model)
else
error("undefined method:" .. opt.method)