🧠 NexLens – Image Analysis

This project leverages API KEY to perform AI-powered image analysis within a Streamlit web application. Users can upload images and receive AI-generated insights based on their queries.

🌐 Live Demo:Click here to try NexLens Image Analysis

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📑 Table of Contents

• Project Overview
• Features
• Technology Stack
• Installation
• Usage
• Project Structure
• Contributing
• License
• Author

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📌 Project Overview

The NexLens Image Analysis System integrates Google's Generative AI (Gemini API) to analyze images and generate insights based on user prompts. The application provides a seamless UI through Streamlit, making AI-powered image interpretation accessible and intuitive.

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✨ Features

• 🧠 AI-Powered Image Analysis – Uses Gemini API for advanced image understanding.
• 🖼️ Supports JPG, JPEG, PNG – Upload and analyze popular image formats.
• ⚡ Real-Time AI Responses – Get instant, insightful feedback.
• 💡 User-Friendly Interface – Clean and interactive UI with Streamlit.
• 🔐 Secure API Management – API keys managed safely using .env.
• 🛡️ Robust Error Handling – Smooth user experience with clean failure handling.

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🛠️ Technology Stack

Frontend:

• Streamlit (UI & interaction)
• Pillow (image processing)

Backend:

• Google Generative AI (Gemini API)
• Python
• dotenv (for secure environment variables)

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⚙️ Installation

1️⃣ Clone the Repository

git clone https://github.com/iamDeepakHR/AI-Powered-Image-Analysis-Using-Python.git
cd AI-Powered-Image-Analysis-Using-Python

2️⃣ Create a Virtual Environment

python -m venv venv
source venv/bin/activate # On Mac/Linux
venv\Scripts\activate # On Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Configure API Key

Create a .env file in the project directory and add:

GENAI_API_KEY=your_google_gemini_api_key

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▶️ Usage

Run the App

streamlit run app.py

How to Use

1. Upload an image (JPG, JPEG, or PNG).
2. Enter a query or description related to the image.
3. Click "Analyze Image" and get AI-generated insights instantly!

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📁 Project Structure

📂 NexLens-Image-Analysis
│-- 📜 app.py # Main Streamlit app
│-- 📜 requirements.txt # Project dependencies
│-- 📜 Procfile # For deployment on platforms like Render/Heroku
│-- 📜 .env # API key (keep secret)
│-- 📜 README.md # Project documentation

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🤝 Contributing

We welcome contributions to improve the project! To contribute:

1. Fork the repo.
2. Create a new branch: git checkout -b feature-name
3. Make changes and commit: git commit -m "Add feature"
4. Push: git push origin feature-name
5. Submit a pull request.

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📄 License

This project is licensed under the MIT License.

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🙋‍♂️ Author

👨‍💻 Developed by Deepak H R

• 🌐 GitHub
• 🔗 LinkedIn

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