Update tasks/image.py

tasks/image.py

@@ -106,8 +106,10 @@ async def evaluate_image(request: ImageEvaluationRequest):
     true_labels = []
     pred_boxes = []  # Flattened list of predicted boxes
     true_boxes_list = []  # Flattened list of ground truth boxes
-    
+
+    i=0
     for example in test_dataset:
+        i += 1
         # Extract image and annotations
         image = example["image"]
         annotation = example.get("annotations", "").strip()
@@ -127,7 +129,7 @@ async def evaluate_image(request: ImageEvaluationRequest):
             true_boxes_list.append([])  # Add empty list for no ground truth smoke
     
         # Perform YOLO inference
-        results = yolo_model .predict(image, verbose=False)
+        results = yolo_model .predict(image)
         
         # Extract predicted box if predictions exist
         if len(results[0].boxes):
@@ -137,7 +139,9 @@ 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
             
     # Filter out entries with empty boxes
     filtered_true_boxes_list = []