🏎️ FormulaTracker — Detect F1 cars by team with YOLO

The goal of this project is to train a YOLO model on a custom dataset to detect Formula 1 cars and classify them by team in video footage.

Dataset I built on Kaggle • Ultralytics YOLO docs •

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📊 Dataset

• Source: curated from a full Grand Prix broadcast. Non-relevant segments were trimmed out.
• Annotation tool: labelImg
• Split: train = 442 images, val = 111 images
• Classes (10):

Team
Alfa Romeo Racing
Ferrari
Haas
McLaren
Mercedes
Racing Point
RedBull
Renault
Toro Rosso
Williams

🏋️ Train the model

Hyperparameters	value
task	detect
mode	train
model	yolo11l.pt
epochs	200
batch	16
imgsz	640

Results

Confusion matrix

Sample Predictions (validation batch)

🚀 Roadmap / Future ideas

• 🚥 Real-time speed estimation: approximate car speeds using multi-frame tracking + homography.
• 📺 On-screen overlay: draw team labels on live or recorded video streams.
• 🧩 Tracking: integrate ByteTrack/BoT-SORT for consistent track IDs across frames.
• 🏁 More seasons: expand dataset with multiple races and lighting/weather conditions.