Update app.py

app.py

@@ -57,11 +57,6 @@ class ImageClassifierCataract:
         label_background = np.ones((50, output_image.shape[1], 3), dtype=np.uint8) * 255
         output_image[-50:] = label_background
 
-        font = cv2.FONT_HERSHEY_SIMPLEX
-        font_scale = 0.4
-        cv2.putText(output_image, f"Analysis Time: {current_time.strftime('%Y-%m-%d %H:%M:%S')}", (10, output_image.shape[0] - 30), font, font_scale, (0, 0, 0), 1)
-        cv2.putText(output_image, f"Predicted Class: {predicted_class}", (10, output_image.shape[0] - 10), font, font_scale, (0, 0, 0), 1)
-
         image_height, image_width, _ = output_image.shape
         box_size = 100
         box_x = (image_width - box_size) // 2
@@ -69,17 +64,15 @@ class ImageClassifierCataract:
         object_box_color = (255, 0, 0)
         cv2.rectangle(output_image, (box_x, box_y), (box_x + box_size, box_y + box_size), object_box_color, 2)
 
-        # Crop the output image to keep only the region of interest
-        output_image = output_image[box_y:box_y+box_size, box_x:box_x+box_size]
-
-        return output_image
+        return output_image, predicted_class, current_time.strftime('%Y-%m-%d %H:%M:%S')
 
     def run_interface(self):
         input_interface = gr.Interface(
             fn=self.classify_image,
             inputs="image",
-            outputs="image",
-            live=True
+            outputs=["image", "text", "text"],
+            live=True,
+            examples=[["example.jpg"]]
         )
         input_interface.launch()