In this project, the objective is to perform vehicle detection on a specified video, focusing specifically on vehicles detection present on the highway. The YOLOv8 model, known for its efficiency and accuracy in object detection, is employed for this task. The goal is to accurately detect and track vehicles while ensuring the detections are restricted to the highway section of the video.
video Link
Key Points:
- YOLOv8, a robust and efficient object detection model, is utilized for vehicle detection in the project.
- The project's main emphasis is on detecting vehicles within the highway area of the provided video.
- The project leverages the capabilities of YOLOv8 to achieve precise vehicle detection and tracking, distinguishing vehicles on the highway from those on other roads or areas within the video.
- Used detect.py to check how OD works
- yolo_on_loop is used to loop for the detection
- plotlinesonimage shows how lines are drawn on the image
- getBBoxes gives info about bounding boxes predicted by yolo on an image
- use result.py to convert predictes images to video frames