This is a face detection web application built with Next.js, Auth.js, and PostgreSQL. It allows users to log in using third-party providers (Google, GitHub, etc.), submit image URLs, and detect faces in the images with bounding box results and confidence scores.
- User Authentication: Sign in using Google, GitHub, or classical email & password via Auth.js.
- Face Detection: Input an image URL, and the app detects faces with bounding boxes and confidence scores.
- User Stats: Track and display the number of images processed by each user.
- Responsive Design: The app adapts to various screen sizes for an optimal user experience.
- Database Integration: User data and sessions are stored using PostgreSQL via Neon.
- Real-Time Interaction: Users can see face detection results in real-time with an interactive form and image display.
- Sign in via Google, GitHub or credentials.
- Submit an image URL to detect faces using the API4AI Face Detection API.
- View the image with detected faces highlighted by bounding boxes and confidence scores.
- Track your stats (number of images processed).
- Next.js - Framework for server-rendered React applications.
- Auth.js - Authentication library for managing user sessions.
- Vercel - Hosting platform for deployment.
- API4AI Face Detection API - Used for detecting faces in images and returning face analysis data.
- Google Cloud OAuth - For authenticating users with Google.
- GitHub OAuth - For authenticating users with GitHub.
- Tailwind CSS - A utility-first CSS framework used for quickly styling and creating responsive designs.
This project is licensed under the MIT License - see the LICENSE file for details.