Update tasks/image.py

tasks/image.py

@@ -163,7 +163,7 @@ def compute_max_iou(true_boxes, pred_box):
 
 @router.post(ROUTE, tags=["Image Task"],
               description=DESCRIPTION)
-async def evaluate_image(model_path: str = "models/yolo11s_best.pt", request: ImageEvaluationRequest = ImageEvaluationRequest()):
+async def evaluate_image(model_path: str = "models_v3/yolo11s_best.engine", request: ImageEvaluationRequest = ImageEvaluationRequest()):
     """
     Evaluate image classification and object detection for forest fire smoke.
     
@@ -184,10 +184,8 @@ async def evaluate_image(model_path: str = "models/yolo11s_best.pt", request: Im
     # Split dataset
     train_test = dataset["train"]
     test_dataset = dataset["val"]
-    if("yolo" in model_path):
-        model = YOLO(model_path, task="detect")
-    if("detr" in model_path):
-        model = RTDETR(model_path)
+    
+    model = YOLO(model_path, task="detect")
     
     # Start tracking emissions
     tracker.start()
@@ -203,7 +201,7 @@ async def evaluate_image(model_path: str = "models/yolo11s_best.pt", request: Im
     pred_boxes = []
     true_boxes_list = []  # List of lists, each inner list contains boxes for one image
 
-    for example in tqdm(test_dataset):
+    for example in test_dataset:
         # Parse true annotation (YOLO format: class_id x_center y_center width height)
         annotation = example.get("annotations", "").strip()
         has_smoke = len(annotation) > 0