{"id":29022919,"url":"https://github.com/sofian2022/projetpfa-autonomousbvehicles","last_synced_at":"2025-06-26T03:04:16.139Z","repository":{"id":300567320,"uuid":"1006489790","full_name":"sofian2022/ProjetPFA-AutonomousbVehicles","owner":"sofian2022","description":"A modular autonomous vehicle project in Python featuring real-time object detection (MobileNet SSD), license plate recognition (YOLOv8, EasyOCR), and traffic sign classification (CNN)","archived":false,"fork":false,"pushed_at":"2025-06-24T15:05:44.000Z","size":54773,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-24T16:24:12.620Z","etag":null,"topics":["autonomous-vehicles","computer-vision","deep-learning","keras","license-plate-recognition","object-detection","opencv","python-pytorch","raspberry-pi","robotics","self-driving-car","tensorflow","traffic-sign-recognition","yolov8"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sofian2022.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LIcense Plate Number Detection/Test_WebCam.py","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-22T11:46:08.000Z","updated_at":"2025-06-24T15:05:48.000Z","dependencies_parsed_at":"2025-06-24T16:34:39.677Z","dependency_job_id":null,"html_url":"https://github.com/sofian2022/ProjetPFA-AutonomousbVehicles","commit_stats":null,"previous_names":["sofian2022/projet-pfa-autonomousbvehicles","sofian2022/projetpfa-autonomousbvehicles"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sofian2022/ProjetPFA-AutonomousbVehicles","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sofian2022%2FProjetPFA-AutonomousbVehicles","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sofian2022%2FProjetPFA-AutonomousbVehicles/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sofian2022%2FProjetPFA-AutonomousbVehicles/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sofian2022%2FProjetPFA-AutonomousbVehicles/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sofian2022","download_url":"https://codeload.github.com/sofian2022/ProjetPFA-AutonomousbVehicles/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sofian2022%2FProjetPFA-AutonomousbVehicles/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261990352,"owners_count":23241188,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["autonomous-vehicles","computer-vision","deep-learning","keras","license-plate-recognition","object-detection","opencv","python-pytorch","raspberry-pi","robotics","self-driving-car","tensorflow","traffic-sign-recognition","yolov8"],"created_at":"2025-06-26T03:04:14.802Z","updated_at":"2025-06-26T03:04:16.101Z","avatar_url":"https://github.com/sofian2022.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003c!-- Project Banner --\u003e\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"Traffic signs Detection And Recognition/images/project.jpg\" alt=\"Project Banner\" width=\"70%\"/\u003e\n\u003c/p\u003e\n\n# 🚗 Autonomous Vehicle Project\n\n[![Build Status](https://img.shields.io/badge/build-passing-brightgreen)](https://github.com/sofian2022/Projet_PFA-Autonomous_Vehicles)\n[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE)\n\nWelcome to the Autonomous Vehicle Project! This repository contains a modular, multi-component system for smart vehicle perception and control, developed as part of a PFA (Projet de Fin d'Année). It integrates state-of-the-art computer vision and deep learning for real-time object detection, license plate recognition, and traffic sign classification, with hardware control for a physical prototype.\n\n---\n\n## ✨ Features\n\n| 🚦  | **Traffic Sign Recognition**   | Classifies traffic signs using a CNN trained on the GTSRB dataset, with a user-friendly GUI.             |\n| --- | ------------------------------ | -------------------------------------------------------------------------------------------------------- |\n| 🔍  | **Real-time Object Detection** | Detects objects (cars, pedestrians, cyclists) using a pre-trained MobileNet SSD model.                   |\n| 🏷️  | **License Plate Recognition**  | Detects license plates with YOLOv8, recognizes characters with EasyOCR, and checks status in a database. |\n| 🛠️  | **Hardware Integration**       | Scripts for controlling camera, motors, servos, ultrasonic sensors, and LEDs.                            |\n\n---\n\n## 🗂️ Project Structure\n\n```\n.\n├── LIcense Plate Number Detection/\n│   ├── check_vehicle_status.py\n│   ├── license_plate_recognition.py\n│   ├── add_sample_vehicles.py\n│   ├── db_connector.py\n│   ├── Test_WebCam.py\n│   └── license_plate_detector.pt\n│\n├── Traffic signs Detection And Recognition/\n│   ├── Train.ipynb\n│   ├── Test_images/\n│   ├── Test/\n│   │   ├── rpiCam.py\n│   │   ├── interface.py\n│   │   └── cameraPC.py\n│   ├── model/\n│   │   ├── traffic_classifiernew.h5\n│   │   └── model_trained_epoch30.p\n│   └── images/\n│       ├── project.jpg\n│       ├── predictions.png\n│       └── GUI.jpg\n│\n├── Object Detection/\n│   ├── detect.py\n│   ├── MobileNetSSD_deploy.prototxt.txt\n│   └── MobileNetSSD_deploy.caffemodel\n│\n├── Materiels_Test/\n│   ├── servoMotor.py\n│   ├── leds.py\n│   ├── ultrasonic.py\n│   ├── motor.py\n│   └── Camera.py\n│\n├── README.md\n└── requirements.txt\n```\n\n---\n\n## 🛠️ Technologies Used\n\n- **Python 3**\n- **PyTorch** (YOLOv8 for license plate detection)\n- **TensorFlow/Keras** (traffic sign recognition)\n- **Caffe** (object detection model)\n- **OpenCV** (image/video processing)\n- **EasyOCR** (license plate OCR)\n- **Pillow** (GUI image handling)\n- **MongoDB** (vehicle/license plate database)\n- **Tkinter** (traffic sign classifier GUI)\n- **NumPy**, **Matplotlib**, **ultralytics**, **requests**\n\n---\n\n## 🚀 Quick Start\n\n1. **Clone the repository:**\n   ```bash\n   git clone https://github.com/sofian2022/Projet_PFA-Autonomous_Vehicles.git\n   cd Projet_PFA-Autonomous_Vehicles\n   ```\n2. **Create a virtual environment (recommended):**\n   ```bash\n   python -m venv venv\n   source venv/bin/activate  # On Windows use venv\\Scripts\\activate\n   ```\n3. **Install dependencies:**\n   ```bash\n   pip install -r requirements.txt\n   ```\n4. **Database Setup (for License Plate Recognition):**\n   - Ensure MongoDB is running.\n   - Update connection details in `LIcense Plate Number Detection/db_connector.py` if needed.\n   - Populate the database with `add_sample_vehicles.py` if desired.\n\n---\n\n## 🖥️ Usage\n\n- **Object Detection:**\n\n  ```bash\n  cd Object Detection\n  python detect.py\n  ```\n\n  Starts real-time object detection using your webcam.\n\n- **License Plate Recognition:**\n  Main script: `license_plate_recognition.py` (see script for usage details; can process images or video streams).\n\n- **Traffic Sign Classifier GUI:**\n\n  ```bash\n  cd \"Traffic signs Detection And Recognition/Test\"\n  python interface.py\n  ```\n\n  Opens a GUI for uploading and classifying traffic sign images.\n\n- **Hardware Tests:**\n  Scripts in `Materiels_Test/` are for Raspberry Pi or similar hardware with the appropriate components.\n\n---\n\n## 📸 Screenshots\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"Traffic signs Detection And Recognition/images/predictions.png\" alt=\"Traffic Sign Predictions\" width=\"45%\"/\u003e\n  \u003cimg src=\"Traffic signs Detection And Recognition/images/GUI.jpg\" alt=\"Traffic Sign GUI\" width=\"45%\"/\u003e\n\u003c/p\u003e\n\n---\n\n## 📄 License\n\nThis project is open-source. Please credit the original authors if you use or modify this code.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsofian2022%2Fprojetpfa-autonomousbvehicles","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsofian2022%2Fprojetpfa-autonomousbvehicles","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsofian2022%2Fprojetpfa-autonomousbvehicles/lists"}