This project implements an object detection model trained on images of F1 single-seaters using the YOLOv8 architecture. The model was trained on a dataset of 2025-season F1 cars and was able to detect F1 teams with a high degree of accuracy.
The Problem
People who are just starting in the world of Formula 1 often do not have knowledge about the teams, drivers, and other related aspects. That is why this project was created to help people identify Formula 1 teams.
The Solution
An object detection model trained with images of F1 single-seaters using the YOLOv8 architecture. The model was trained on a dataset of 2025 season F1 car images and was able to detect F1 teams with a high level of accuracy.
Technical Features
- Dataset: Images of 2025 season F1 single-seaters
- Model: YOLOv8
- Labeling Platform: Roboflow
- Training Environment: Google Colab
- Language: Python