fixed

tasks/image.py

@@ -37,7 +37,7 @@ print("CUDA version:", torch.version.cuda)
 print("cuDNN version:", torch.backends.cudnn.version())
 
 #MODEL_TYPE = "YOLOv11n"
-DESCRIPTION = f"YOLOv11n 1280 not quantisized model with batch 32 inference on TensorRT"
+DESCRIPTION = f"YOLOv11n 1280 not quantisized model with batch 1 inference on TensorRT"
 print(14)
 ROUTE = "/image"
 print(15)
@@ -141,11 +141,11 @@ async def evaluate_image(request: ImageEvaluationRequest):
     #PATH_TO_MODEL = 'models/best_YOLOv11n_1280.onnx'
     #PATH_TO_MODEL = 'models/best_yolov6n_1280.pt'
     #PATH_TO_MODEL = 'models/best_YOLOv11n_1280_real_half.onnx'
-    PATH_TO_MODEL = 'models/best_YOLOv11n_1280_half_batch_32.engine'
+    PATH_TO_MODEL = 'models/best_YOLOv11n_1280_full_batch_1.engine'
     INFERENCE_ENGINE_TYPE = 'pt'
     INPUT_SIZE = 1280
     N_TEST_BATCHES = 2
-    BATCH_SIZE = 32 # Can be adjusted as needed
+    BATCH_SIZE = 1 # Can be adjusted as needed
     print("PATH_TO_MODEL", PATH_TO_MODEL)
     def preprocessor(frame):
         #frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # Only when read from file