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https://github.com/sohitbennett/roadsafe

A Deep learning computer vision system for real-time traffic safety monitoring.
https://github.com/sohitbennett/roadsafe

computer-vision esrgan keras numpy pandas python scikit-learn tensorflow tesseract-ocr yolov5 yolov8

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A Deep learning computer vision system for real-time traffic safety monitoring.

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# 🚦 RoadSafe

RoadSafe is a deep learning–powered computer vision system designed for **real-time traffic safety monitoring**.
The project integrates multiple models for **helmet detection, seatbelt compliance, vehicle occupancy recognition, and license plate extraction**, enabling automated enforcement and improved road safety.

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## ✨ Features

- 🪖 **Helmet Detection** – Ensures two-wheeler riders follow safety compliance.
- ⛑️ **Seatbelt Detection** – Identifies drivers/passengers not wearing seatbelts.
- 🧍 **Occupancy Detection** – Counts people in vehicles to monitor overcrowding.
- 🔢 **License Plate Extraction** – Detects and extracts number plates using OCR (Tesseract).
- 🖼️ **Image Enhancement** – Integrated **ESRGAN** for super-resolution on low-quality traffic footage.
- ⚡ **Real-Time Analysis** – Built with **YOLOv5/YOLOv8 + OpenCV** for live video stream monitoring.

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## 🛠️ Tech Stack

- **Languages**: Python
- **Deep Learning Frameworks**: TensorFlow, Keras, PyTorch
- **Models**: YOLOv5, YOLOv8, ESRGAN
- **Libraries**: OpenCV, NumPy, Pandas, scikit-learn
- **OCR**: Tesseract OCR

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