4. Data set and folder structure

6. Training ML model

8. Summary of object detection using YOLO

7. Testing ML model

5. Label images/objects using CVAT

4. Data set and folder structure

3. Install dependencies for custom object detection using YOLO

2. Setup python virtual environment, activate and deactive it for machine learning applications

1. Overview and steps to follow for custom object detection using YOLO

Installing framework for computer vision, image processing, data analytics and machine learning

Custom object classification using Machine Learning

Custom Object Detection using YOLOv8

Master in Mechatronics, specialization in Applied ML and Robotics, University of Agder