🚦 TRAFFIC VISION

Detection of accidents on the road using computer vision.

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📋 Description

TRAFFIC VISION is an AI-powered system that detects accidents and traffic anomalies from video feeds.
This project leverages deep learning models (e.g., YOLO, CNNs) for real-time accident detection, with potential integration into smart city systems for enhanced traffic safety.

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📦 Installation

Install PyTorch
Visit https://pytorch.org and select the appropriate installation command for your system (OS, Python version, CUDA).

Example:

pip3 install torch torchvision

Install other dependencies

pip install -r requirements.txt

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⚙️ Configuration (config.yaml)

Main sections you can edit:

• source_info — video source and ROI.
• detection — YOLO model, tracker, detection params.
• show — on-screen display options.
• web_mov — web streaming settings.
• video_writer — save video to disk.
• notify — Telegram alerts (location, buffer, bot token, chat ID).

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🚀 Run the Application

python3 src/main.py

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🌍 Frontend repository

https://github.com/khurshed555/ai-hackathon-samarkand-arch-frontend

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🎬 Demo

❇️ The usual case and the passage in the wrong place

⚠️ An emergency