Update app_3.py

app_3.py

@@ -995,6 +995,8 @@ def use_orientation(selected_image:gr.SelectData):
 @torch.inference_mode
 def process_image(input_image, input_text):
     """Main processing function for the Gradio interface"""
+
+    
     
     if isinstance(input_image, Image.Image):
         input_image = np.array(input_image)
@@ -1117,17 +1119,17 @@ def process_image(input_image, input_text):
             # resize the longer side to H * 0.9
             H, W, _ = image_center.shape
             if H > W:
-                W = int(W * (height * 0.9) / H)
-                H = int(height * 0.9)
+                W = int(W * (HEIGHT * 0.9) / H)
+                H = int(HEIGHT * 0.9)
             else:
-                H = int(H * (width * 0.9) / W)
-                W = int(width * 0.9)
+                H = int(H * (WIDTH * 0.9) / W)
+                W = int(WIDTH * 0.9)
                 
             image_center = np.array(Image.fromarray(image_center).resize((W, H)))
             # pad to H, W
-            start_h = (height - H) // 2
-            start_w = (width - W) // 2
-            image = np.zeros((height, width, 4), dtype=np.uint8)
+            start_h = (HEIGHT - H) // 2
+            start_w = (WIDTH - W) // 2
+            image = np.zeros((HEIGHT, WIDTH, 4), dtype=np.uint8)
             image[start_h : start_h + H, start_w : start_w + W] = image_center
             image = image.astype(np.float32) / 255.0
             image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 0.5
@@ -1280,17 +1282,17 @@ def process_image(input_image, input_text):
             # resize the longer side to H * 0.9
             H, W, _ = image_center.shape
             if H > W:
-                W = int(W * (height * 0.9) / H)
-                H = int(height * 0.9)
+                W = int(W * (HEIGHT * 0.9) / H)
+                H = int(HEIGHT * 0.9)
             else:
-                H = int(H * (width * 0.9) / W)
-                W = int(width * 0.9)
+                H = int(H * (WIDTH * 0.9) / W)
+                W = int(WIDTH * 0.9)
                 
             image_center = np.array(Image.fromarray(image_center).resize((W, H)))
             # pad to H, W
-            start_h = (height - H) // 2
-            start_w = (width - W) // 2
-            image = np.zeros((height, width, 4), dtype=np.uint8)
+            start_h = (HEIGHT - H) // 2
+            start_w = (WIDTH - W) // 2
+            image = np.zeros((HEIGHT, WIDTH, 4), dtype=np.uint8)
             image[start_h : start_h + H, start_w : start_w + W] = image_center
             image = image.astype(np.float32) / 255.0
             image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 0.5