refactor

waifu2x.lua

@@ -82,13 +82,10 @@ local function convert_image(opt)
       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 t, scale_model = pcall(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)
+	 if not t then
+	    scale_model = model
 	 end
 	 local t = sys.clock()
 	 x = alpha_util.make_border(x, alpha, reconstruct.offset_size(scale_model))
@@ -100,13 +97,6 @@ local function convert_image(opt)
 	 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, opt.batch_size)
@@ -120,7 +110,7 @@ local function convert_image(opt)
    image_loader.save_png(opt.o, new_x, tablex.update({depth = opt.depth, inplace = true}, meta))
 end
 local function convert_frames(opt)
-   local model_path, scale_model
+   local model_path, scale_model, t
    local noise_scale_model = {}
    local noise_model = {}
    local scale_f, image_f
@@ -140,38 +130,23 @@ local function convert_frames(opt)
    if opt.m == "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
    elseif opt.m == "noise" then
       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
    elseif opt.m == "noise_scale" then
       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)
+	 t, scale_model = pcall(torch.load, model_path, "ascii")
+	 if not t then
+	    scale_model = noise_scale_model[opt.noise_level]
 	 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)