readme.md

README.md

🧠 Swap Face and Hair with Mask Detection

This project swaps both face and hair from a source image to a target image using:

• SegFormer (for hair segmentation)
• MediaPipe FaceMesh (for facial structure)
• NumPy and OpenCV for blending

🔧 Setup (Google Colab or local Python)

pip install -r requirements.txt

📁 Project Structure

• swap_face_and_hair.py: main code logic
• requirements.txt: dependencies
• README.md: this file

🚀 How to Use

from PIL import Image
import numpy as np
from swap_face_and_hair import swap_face_and_hair

source_img = Image.open("source.jpg")
target_img = Image.open("target.jpg")

result = swap_face_and_hair(np.array(source_img), np.array(target_img))
result.save("result.jpg")

📝 Notes

• Make sure your source image has clear face + hair in frontal view.
• Target image should ideally be of similar resolution and head pose.
• GPU recommended for faster processing.

---

Made with ❤️ using HuggingFace Transformers and MediaPipe.