AI Face Makeup Application & Enhancement Through Codeformer

This repository contains a Python script for face makeup application and enhancement using the CodeFormer model. The script leverages face recognition and CodeFormer, a deep learning model, to enhance facial features in images.

Prerequisites

Before running the script, make sure you have the following dependencies installed:

• Python
• OpenCV (pip install opencv-python)
• PyTorch (pip install torch torchvision)
• NumPy (pip install numpy)
• basicsr library (Ensure that the required libraries are installed. You can find them in the requirements.txt file.)

Usage

1. Install the required Python packages:

   pip install -r requirements.txt

   or through the provided CodeFormer.ipynb nootebook.

2. Replace the ./CodeFormer/inference_codeformer.py with the inferece_codeformer.py file provided in this repository.

3. Run the inference_codeformer.py script script:

   python face_restoration.py

Options

The script includes options for different makeup styles:

• option_makeup = 1: Deep Gray Eyebrows, Red Lip, Gray Eyes, Black Eyeliner
• option_makeup = 2: Brown Eyebrows, Hot Pink Lip, Gray Eyes, Brown Eyeliner
• option_makeup = 3: Deep Gray Eyebrows, Dark Orange Brown Lip, Gray Eyes, Black Eyeliner
• option_makeup = 4: Deep Gray Eyebrows, Light Pink Lip, Gray Eyes, Brown Eyeliner
• option_makeup = 5: Deep Gray Eyebrows, Crimson Lip, Gray Eyes, Black Eyeliner

You can modify the option_makeup variable in the inferece_codeformer.py script to choose a specific makeup style.

Examples

The following were the results from the DLIB makeup application code

Below are the results from the DLIB library refined through Codeformer

Shown below are the final results with makeup application through DLIB and refinement through Codeformer

Acknowledgments

• The CodeFormer model is used for face restoration.
• Face recognition is performed using the face_recognition library.