Update tasks/image.py

tasks/image.py

@@ -107,9 +107,8 @@ async def evaluate_image(request: ImageEvaluationRequest):
     pred_boxes = []  # Flattened list of predicted boxes
     true_boxes_list = []  # Flattened list of ground truth boxes
 
-    i=0
+    print('Start of prediction...')
     for example in test_dataset:
-        i += 1
         # Extract image and annotations
         image = example["image"]
         annotation = example.get("annotations", "").strip()
@@ -139,15 +138,13 @@ async def evaluate_image(request: ImageEvaluationRequest):
         else:
             predictions.append(0)  # No smoke predicted
             pred_boxes.append([])  # Add empty list if no prediction
-        if i >=10:
-            print("fini")
-            break
-            
+
+    print('Prediction done.')
     # Filter out entries with empty boxes
     filtered_true_boxes_list = []
     filtered_pred_boxes = []
     
-    
+    print('Box analysis...')
     for true_boxes, pred_boxes_entry in zip(true_boxes_list, pred_boxes):
         if true_boxes and pred_boxes_entry:  # Keep only if neither is empty
             filtered_true_boxes_list.append(true_boxes)
@@ -198,5 +195,5 @@ async def evaluate_image(request: ImageEvaluationRequest):
             "test_seed": request.test_seed
         }
     }
-    
+    print(results)
     return results