upscaler fix

Author: yownas

modules/upscale_pipeline.py

@@ -77,12 +77,17 @@ def process(
         input_image = np.array(input_image).astype(np.float32) / 255.0
         input_image = torch.from_numpy(input_image)[None,]
 
+        worker.outputs.append(["preview", (-1, f"Load upscaling model ...", None)])
         upscaler_name = controlnet["upscaler"]
-        worker.outputs.append(["preview", (-1, f"Load upscaling model {upscaler_name}...", None)])
-        print(f"Upscale: Loading model {upscaler_name}")
         upscale_path = path_manager.get_file_path(upscaler_name)
         if upscale_path == None:
             upscale_path = path_manager.get_file_path("4x-UltraSharp.pth")
+        upscaler_model = self.load_upscaler_model(upscale_path)
+
+        worker.outputs.append(["preview", (-1, f"Upscaling image ...", None)])
+        decoded_latent = ImageUpscaleWithModel().upscale(
+            upscaler_model, input_image
+        )[0]
 
         try:
             upscaler_model = self.load_upscaler_model(upscale_path)
@@ -92,17 +97,6 @@ def process(
                 upscaler_model, input_image
             )[0]
 
-            worker.outputs.append(["preview", (-1, f"Converting ...", None)])
-            images = [
-                np.clip(255.0 * y.cpu().numpy(), 0, 255).astype(np.uint8)
-                for y in decoded_latent
-            ]
-            worker.outputs.append(["preview", (-1, f"Done ...", None)])
-        except:
-            traceback.print_exc()
-            worker.outputs.append(["preview", (-1, f"Oops ...", "error.png")])
-            images =  []
-
             worker.outputs.append(["preview", (-1, f"Converting ...", None)])
             images = [
                 np.clip(255.0 * y.cpu().numpy(), 0, 255).astype(np.uint8)