640 64 full

models/best_YOLOv11n_640_full_batch_64.engine

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0a2ccf9e5aa27abe9a0bcedb90e2d2e47e3f63570089d6468935165382d473e7
+size 12180938

models/best_YOLOv11n_640_half_batch_64.engine

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:17a4f1f2e5a3ee61cc253859d685e300c79738ae5cc8fce9b934423745b09b79
+size 7352705

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_128.engine on TensorRT"
+DESCRIPTION = f"best_YOLOv11n_640_full_batch_64.engine on TensorRT"
 ROUTE = "/image"
 
 def parse_boxes(annotation_string):
@@ -129,11 +129,11 @@ 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_640_full_batch_128.engine'
+    PATH_TO_MODEL = 'models/best_YOLOv11n_640_full_batch_64.engine'
     INFERENCE_ENGINE_TYPE = 'pt'
     INPUT_SIZE = 640
     N_TEST_BATCHES = 2
-    BATCH_SIZE = 128 # Can be adjusted as needed
+    BATCH_SIZE = 64 # Can be adjusted as needed
     print("PATH_TO_MODEL", PATH_TO_MODEL)