README.md

metadata

title: Register File AI API
emoji: 🚀
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
pinned: false
license: mit

🚀 Register File AI API

A comprehensive AI-powered image processing and product search API with both FastAPI backend and Gradio interface.

✨ Features

🖼️ Image Processing

• Object Detection: Automatically detect and crop products in images
• Background Removal: Remove backgrounds with AI precision
• Image Enhancement: Three different enhancement options
• Custom Backgrounds: Apply custom backgrounds to products
• AI Description Generation: Generate SEO-optimized product descriptions

🔍 Product Search

• Google Custom Search: Find similar products across the web
• Multi-platform Results: Get results from various e-commerce platforms

🎨 Background Generation

• AI Background Creation: Generate custom backgrounds using text prompts
• Multiple Styles: Support for different background styles and colors

🚀 Quick Start

Using the Gradio Interface

1. Visit the space URL
2. Upload your product image
3. Choose enhancement options
4. Generate descriptions
5. Search for similar products

Using the API Directly

The FastAPI server provides REST endpoints for programmatic access:

# Health check
curl https://your-space-url.hf.space/

# Upload image
curl -X POST "https://your-space-url.hf.space/upload" \
  -F "image=@your_image.jpg"

# Enhance image with all options
curl -X POST "https://your-space-url.hf.space/enhance_and_return_all_options" \
  -H "Content-Type: application/json" \
  -d '{
    "image_path": "uploads/your_image.jpg",
    "background": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNkYPhfDwAChAGAcFFhtgAAAABJRU5ErkJggg=="
  }'

# Generate description
curl -X POST "https://your-space-url.hf.space/choose_image_and_generate_description" \
  -H "Content-Type: application/json" \
  -d '{
    "processor_id": "your_processor_id",
    "option_number": 1
  }'

# Search products
curl -X POST "https://your-space-url.hf.space/get_search_results" \
  -H "Content-Type: application/json" \
  -d '"laptop computer"'

# Generate background
curl -X POST "https://your-space-url.hf.space/generate_background" \
  -H "Content-Type: application/json" \
  -d '"modern office background with soft lighting"'

📡 API Endpoints

Core Endpoints

Method	Endpoint	Description
GET	/	Health check and API info
GET	/health	Service health status
GET	/status	Detailed status with active processors

Image Processing

Method	Endpoint	Description
POST	/upload	Upload image file
POST	/enhance_and_return_all_options	Process image with all enhancement options
POST	/choose_image_and_generate_description	Generate AI description for selected image
DELETE	/cleanup/{processor_id}	Clean up processor to free memory

Utility Services

Method	Endpoint	Description
POST	/get_search_results	Search for similar products
POST	/generate_background	Generate custom backgrounds

🔧 Environment Variables

To use all features, set these environment variables:

SECRET_API_KEY=your_google_gemini_api_key
GOOGLE_CSE_ID=your_google_custom_search_engine_id
GOOGLE_API_KEY=your_google_api_key

💡 Usage Examples

Python Client Example

import requests
import base64
from PIL import Image

# Base URL for your Hugging Face Space
BASE_URL = "https://your-space-url.hf.space"

# Upload image
with open("product.jpg", "rb") as f:
    response = requests.post(f"{BASE_URL}/upload", files={"image": f})
    upload_result = response.json()

# Enhance image
enhance_request = {
    "image_path": upload_result["file_path"],
    "background": "data:image/png;base64,white_background_base64"
}
response = requests.post(f"{BASE_URL}/enhance_and_return_all_options", json=enhance_request)
enhancement_result = response.json()

# Generate description
desc_request = {
    "processor_id": enhancement_result["processor_id"],
    "option_number": 1
}
response = requests.post(f"{BASE_URL}/choose_image_and_generate_description", json=desc_request)
description = response.json()

print("Generated Description:", description["description"])

JavaScript/Node.js Example

const FormData = require('form-data');
const fs = require('fs');
const axios = require('axios');

const BASE_URL = 'https://your-space-url.hf.space';

async function processImage() {
    // Upload image
    const form = new FormData();
    form.append('image', fs.createReadStream('product.jpg'));
    
    const uploadResponse = await axios.post(`${BASE_URL}/upload`, form, {
        headers: form.getHeaders()
    });
    
    // Enhance image
    const enhanceResponse = await axios.post(`${BASE_URL}/enhance_and_return_all_options`, {
        image_path: uploadResponse.data.file_path,
        background: "data:image/png;base64,white_background_base64"
    });
    
    console.log('Enhancement completed:', enhanceResponse.data.processor_id);
}

processImage();

🛠️ Technical Details

Architecture

• Backend: FastAPI with async support
• Frontend: Gradio interface for easy interaction
• AI Models:
  • OwlViT for object detection
  • REMBG for background removal
  • Google Gemini for description generation
  • Various enhancement algorithms

Performance

• Optimized for CPU inference
• Background processing for long-running tasks
• Memory management with processor cleanup
• Efficient image handling with PIL/OpenCV

📄 License

MIT License - feel free to use in your projects!

🤝 Contributing

This project is part of a hackathon submission. Feel free to fork and improve!

🐛 Issues

If you encounter any issues, please check:

1. Image formats (JPG, PNG supported)
2. API key configuration
3. Network connectivity for external services

For bug reports, please include:

• Error messages
• Input image details
• Expected vs actual behavior