Fix model loading error when using ukbench model; Add error handling
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parent
1a20ec501b
commit
1f91548c6e
64
waifu2x.lua
64
waifu2x.lua
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@ -17,23 +17,34 @@ local function convert_image(opt)
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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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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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--local srcnn = require 'lib/srcnn'
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--local model = srcnn.waifu2x("rgb"):cuda()
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model:evaluate()
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local model_path = path.join(opt.model_dir, ("noise%d_model.t7"):format(opt.noise_level))
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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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new_x = reconstruct.image(model, x, 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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local model_path = path.join(opt.model_dir, ("scale%.1fx_model.t7"):format(opt.scale))
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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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new_x = reconstruct.scale(model, opt.scale, x, 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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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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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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x = reconstruct.image(noise_model, x)
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new_x = reconstruct.scale(scale_model, opt.scale, x, opt.crop_size)
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else
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@ -43,15 +54,30 @@ local function convert_image(opt)
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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 noise1_model, noise2_model, scale_model
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if opt.m == "scale" then
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local 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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elseif opt.m == "noise" and opt.noise_level == 1 then
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local model_path = path.join(opt.model_dir, "noise1_model.t7")
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noise1_model = torch.load(model_path, "ascii")
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if not noise1_model then
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error("Load Error: " .. model_path)
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end
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elseif opt.m == "noise" and opt.noise_level == 2 then
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local model_path = path.join(opt.model_dir, "noise2_model.t7")
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noise2_model = torch.load(model_path, "ascii")
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if not noise2_model then
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error("Load Error: " .. model_path)
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end
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end
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local fp = io.open(opt.l)
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if not fp then
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error("Open Error: " .. opt.l)
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end
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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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