https://github.com/eng-m-abdrabbou/object-detection-python-yolo
Real-time object detection web app using YOLOv5 and Flask for instant webcam object recognition.
https://github.com/eng-m-abdrabbou/object-detection-python-yolo
flask object-detection opencv python pytorch rest-api restful-api torch ultralytics yolov8
Last synced: 3 months ago
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Real-time object detection web app using YOLOv5 and Flask for instant webcam object recognition.
- Host: GitHub
- URL: https://github.com/eng-m-abdrabbou/object-detection-python-yolo
- Owner: Eng-M-Abdrabbou
- License: mit
- Created: 2025-02-21T18:22:19.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-13T15:28:06.000Z (about 1 year ago)
- Last Synced: 2025-06-13T16:45:18.148Z (about 1 year ago)
- Topics: flask, object-detection, opencv, python, pytorch, rest-api, restful-api, torch, ultralytics, yolov8
- Language: HTML
- Homepage:
- Size: 9.83 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# VisionAid: Real-Time Object Detection Web Application
## 🚀 Project Overview
VisionAid is a web-based object detection application that uses YOLOv5 to perform real-time object recognition through your webcam. The application provides instant identification and confidence scores for detected objects. This model is pre-trained on the COCO dataset on roughly 80 objects.
## 🔧 Technologies Used
- **Backend**: Flask (Python)
- **Object Detection**: YOLOv5 (ultralytics)
- **Frontend**: HTML5, JavaScript
- **Computer Vision**: OpenCV, Torch
## ✨ Features
- Real-time webcam object detection
- Instant object identification
- Confidence score for each detected object
- Simple, intuitive web interface
## 📦 Prerequisites
- Python 3.8+
- Webcam-enabled device
## 🛠️ Installation
### 1. Clone the Repository
```bash
git clone git@github.com:Eng-M-Abdrabbou/Object-Detection-Python-YOLO.git
cd Object-Detection-Python-YOLO
```
### 2. Install Dependencies
```bash
pip install -r requirements.txt
```
### 3. Run the Application
```bash
python app.py
```
## 🖥️ How It Works
1. The application accesses your webcam
2. Captures video frames in real-time
3. Processes each frame using YOLOv5 object detection
4. Displays detected objects with confidence scores
## 🔍 Supported Object Classes
The application can detect a wide range of objects using the YOLOv5n pre-trained model, including:
- People
- Vehicles
- Animals
- Everyday objects
- And many more!
## 📸 Screenshots
## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## 📄 License
This project is licensed under the MIT License.
## 🙏 Acknowledgments
- [Ultralytics](https://github.com/ultralytics/yolov5) for YOLOv5
- [Flask](https://flask.palletsprojects.com/) Web Framework