Image Identifier

Project Overview

This Image Identifier is a web application built with Next.js that uses Google's Gemini AI to analyze and provide detailed information about uploaded images. The app offers a user-friendly interface for image upload, displays AI-generated information about the image, and provides related keywords and questions for further exploration.

Features

• Image upload and preview
• AI-powered image analysis using Google Gemini API
• Detailed information display about the identified image
• Related keywords generation for further exploration
• AI-generated related questions about the image
• Responsive design for various screen sizes

Tech Stack

• Next.js 14 (React framework)
• TypeScript
• Tailwind CSS for styling
• Google Generative AI (Gemini API)

Key Functionalities

1. Image Upload: Users can upload an image through the ImageUploader component.
2. Image Analysis: The uploaded image is sent to the Gemini AI API for analysis.
3. Information Display: The AI-generated information about the image is displayed in the ResultDisplay component.
4. Related Keywords: The app extracts and displays related keywords from the AI response.
5. Related Questions: The app generates and displays related questions about the image using a separate AI query.
6. Regenerate Content: Users can click on keywords to regenerate content with a focus on that specific aspect.
7. Ask Related Questions: Users can click on generated questions to get more specific information about the image.

Setup and Installation

1. Clone the repository
2. Install dependencies: npm install
3. Set up environment variables:
   • Create a .env.local file in the root directory
   • Add your Google Gemini API key: NEXT_PUBLIC_GOOGLE_GEMINI_API_KEY=your_api_key_here
4. Run the development server: npm run dev
5. Open http://localhost:3000 in your browser

Deployment

This project can be easily deployed on platforms like Vercel or Netlify. Make sure to set up the environment variables in your deployment platform's settings.

Future Improvements

• Implement user authentication for personalized experiences
• Add image categorization and tagging features
• Implement a gallery of previously analyzed images
• Optimize performance for faster image processing
• Add multi-language support for global users

License

This project is licensed under the MIT License.

Landing Page

After image analysis