README.md

metadata

title: CleanCut Background Remover
emoji: ✂️
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: mit
models:
  - ZhengPeng7/BiRefNet

CleanCut - AI Background Remover

Professional background removal powered by BiRefNet model.

Features

• 🚀 High-quality background removal
• 🎨 Preserves fine details (hair, fur, etc.)
• 📱 Mobile app support via API
• 🔥 Fast processing with GPU acceleration

API Usage

Endpoint

POST https://[your-space-name].hf.space/remove-background

Example (Python)

import requests
from PIL import Image
import io

# Send image
with open('image.jpg', 'rb') as f:
    response = requests.post(
        'https://[your-space-name].hf.space/remove-background',
        files={'file': f}
    )

# Save result
if response.status_code == 200:
    img = Image.open(io.BytesIO(response.content))
    img.save('result.png')

Example (Flutter/Dart)

import 'package:dio/dio.dart';

final dio = Dio();
final formData = FormData.fromMap({
  'file': await MultipartFile.fromFile(imagePath),
});

final response = await dio.post(
  'https://[your-space-name].hf.space/remove-background',
  data: formData,
);

if (response.statusCode == 200) {
  // response.data contains the PNG image bytes
}

Model Information

• Model: BiRefNet-dynamic
• License: MIT
• Paper: BiRefNet: Bilateral Reference Network

Development

This is the server component for the CleanCut mobile app.

Local Setup

pip install -r requirements.txt
python app.py

Links

• 📱 Mobile App (Coming soon)
• 💻 GitHub Repository
• 📄 Model Card