640 64 half

tasks/image.py

@@ -26,7 +26,7 @@ print("CUDA version:", torch.version.cuda)
 print("cuDNN version:", torch.backends.cudnn.version())
 
 #MODEL_TYPE = "YOLOv11n"
-DESCRIPTION = f"best_YOLOv11n_640_full_batch_64.engine on TensorRT"
+DESCRIPTION = f"best_YOLOv11n_640_half_batch_64.engine on TensorRT"
 ROUTE = "/image"
 
 def parse_boxes(annotation_string):
@@ -129,7 +129,7 @@ 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_640_full_batch_64.engine'
+    PATH_TO_MODEL = 'models/best_YOLOv11n_640_half_batch_64.engine'
     INFERENCE_ENGINE_TYPE = 'pt'
     INPUT_SIZE = 640
     N_TEST_BATCHES = 2