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https://github.com/nafisrayan/threejs-python-flask

The project is an innovative VR application that integrates Three.js for 3D visualization, Python for backend processing, and Flask as the web framework. It features interactive 3D scenes with real-time object detection using the YOLO algorithm. The application supports multiple .gltf models and includes augmented reality feat
https://github.com/nafisrayan/threejs-python-flask

ai augmented-reality flask gltf handgesture llm nlp python threejs virtual-reality vr xr yolo

Last synced: about 1 month ago
JSON representation

Host: GitHub
URL: https://github.com/nafisrayan/threejs-python-flask
Owner: NafisRayan
Created: 2024-10-14T18:44:37.000Z (4 months ago)
Default Branch: main
Last Pushed: 2024-12-30T22:35:07.000Z (about 2 months ago)
Last Synced: 2024-12-30T23:24:45.815Z (about 2 months ago)
Topics: ai, augmented-reality, flask, gltf, handgesture, llm, nlp, python, threejs, virtual-reality, vr, xr, yolo
Language: HTML
Homepage:
Size: 11.5 MB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: Readme.md

Awesome Lists containing this project

README

# ThreeJS-Python-Flask

This project combines Three.js, Python, and Flask to create an interactive 3D web application with real-time object detection using YOLO (You Only Look Once).

## Table of Contents

- [Project Overview](#project-overview)
- [Features](#features)
- [Technologies Used](#technologies-used)
- [Setup Instructions](#setup-instructions)
- [Usage](#usage)
- [Contributing](#contributing)

## Project Overview

This repository showcases an innovative integration of Three.js for 3D visualization, Python for backend processing, and Flask for creating a web application. The project demonstrates how to combine these technologies to build an interactive environment with real-time object detection capabilities.

## Screenshots

Here are some screenshots of the app showcasing its key features and design:

Home Screen

### Features

- Interactive 3D scene rendered using Three.js
- Real-time object detection using YOLO algorithm
- Web-based interface built with Flask
- Support for multiple .gltf models
- XR (Augmented Reality) support with hand tracking
- Responsive design for desktop and mobile devices

## Technologies Used

- Frontend: Three.js
- Backend: Python
- Web Framework: Flask
- Object Detection: YOLO (You Only Look Once)
- Additional Dependencies:
- Ultralytics for YOLO integration
- OpenCV for video processing
- Tailwind CSS for styling

## Setup Instructions

To run this project locally, follow these steps:

1. Clone the repository:
git clone https://github.com/NafisRayan/ThreeJS-Python-Flask.git

2. Install dependencies:
pip install flask opencv-python ultralytics numpy

3. Ensure you have Node.js installed on your system.

4. Navigate to the project directory:
cd ThreeJS-Python-Flask

5. Run the Flask server:
python app.py

6. Access the application by opening a web browser and navigating to `http://localhost:5000`.

## Usage

Once the application is running, you'll see a live video feed with real-time object detection overlaid on a 3D scene. You can interact with the scene using keyboard controls or XR controllers if available.

- Use arrow keys or WASD to move the camera
- Press Space to jump
- Left-click and drag to rotate the camera
- Right-click and drag to pan the camera

For a more immersive experience, use a VR headset and controllers to explore the 3D environment.

## Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

1. Fork the repository
2. Create a new branch (`git checkout -b feature/amazing-feature`)
3. Make your changes
4. Commit your changes (`git commit -am 'Add some amazing feature'`)
5. Push to the branch (`git push origin feature/amazing-feature`)
6. Open a Pull Request