feat: yolov8m custom model

app.py

@@ -3,7 +3,9 @@ from ultralytics import YOLO
 import cv2
 
 # Yolov8 nano on custom data with BS=32
-model = YOLO('custom_model.pt')
+# model = YOLO('custom_model.pt')
+# Use YoloV8 Medium model trained on Custom data with bs32
+model = YOLO('yolov8m_bs32.pt')
 
 def infer(path):
     img = cv2.imread(path)

flagged/log.csv

@@ -0,0 +1,2 @@
+Input Image,Prediction,flag,username,timestamp
+,,,,2024-01-13 22:00:45.914749

yolov8m_bs32.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:62d7cb0ac8ad42cdb52d722b5214b58966dbcfe9f49f92745030053fdacd794a
+size 52014550