Update tasks/image.py

tasks/image.py

@@ -31,7 +31,7 @@ device = torch.device("cuda")
 
 def load_camera_models():
     models = {}
-    folder = "cameras_dataset"
+    folder = "cameras_dataset/"
     cameras = ['brison-200', 'brison-110', 'courmettes-212', 'courmettes-160', 'brison-290', 'marguerite-29','default']
 
     # Ensure the folder exists
@@ -154,7 +154,7 @@ def compute_max_iou(true_boxes, pred_box):
 
 # @router.post(ROUTE, tags=["Image Task"],
 #              description=DESCRIPTION)
-async def evaluate_image( request: ImageEvaluationRequest = ImageEvaluationRequest()):
+async def evaluate_image(model_path,request: ImageEvaluationRequest = ImageEvaluationRequest()):
 # def evaluate_image(model_path: str, request: ImageEvaluationRequest = ImageEvaluationRequest()):
     """
     Evaluate image classification and object detection for forest fire smoke.
@@ -174,7 +174,7 @@ async def evaluate_image( request: ImageEvaluationRequest = ImageEvaluationReque
     dataset = load_dataset(request.dataset_name, token=os.getenv("HF_TOKEN"))
     
     # Split dataset
-    train_test = dataset["train"]
+    # train_test = dataset["train"]
     test_dataset = dataset["val"]
 
     models = load_camera_models()