Egypt-Metro/ai

Egypt Metro AI Models YOLOv8 Object Detection App Description This is a web application built with Flask that performs object detection using YOLOv8 model. It allows you to upload images or videos, or use the webcam for real-time object detection. The detected objects are labeled with bounding boxes and class names. Installation $ git clone github.com $ cd egypt-metro-ai $ pip install -r requirements.txt Usage Follow the steps below to run the application: Make sure you have Python and pip installed. Install the required dependencies by running the following command in the project directory: $ pip install -r requirements.txt Run the application using the following command: $ python main.py Open your web browser and visit localhost . Upload an image or video file, or use the webcam for real-time object detection. View the object detection results on the web page. File Structure maln.py: The main Flask application file. infer.py: Contains functions for running YOLOv8 object detection. templates: Contains HTML templates for rendering the web pages. static/web_images: Contains static images used in the web application. yolo_assets: Contains the YOLOv8 model, class names file, and output directory for detections. README.md: The README file with instructions and information about the project. requirements.txt: Lists the required Python packages and their versions. Dependencies The project relies on the following dependencies: Flask==2.3.2 Flask-WTF==1.1.1 opencv-python==4.7.0.72 ultralytics==8.0.99 Contributing Contributions are welcome! If you find any issues or have suggestions for improvements, please feel free to create an issue or submit a pull request. License This project is licensed under the MIT License. See the LICENSE file for more information. Acknowledgments Special thanks to the creators of YOLOv8 and Flask for their excellent frameworks. Contact If you have any questions or inquiries …