Day 4: Extracting and Aligning Facial Features #FaceAlignment #DeepfakePreparation

On Day 4, we’ll focus on extracting facial landmarks and aligning faces. These steps are crucial for ensuring that the face swapping process appears natural and realistic. By the end of this session, your app will be able to identify key facial features and align them for transformations.

Table of Contents

1. What Is Facial Feature Extraction?

Facial feature extraction involves detecting key points on a face, such as eyes, nose, mouth, and jawline. These points, or landmarks, help:

Align Faces: Ensure the source and target faces are positioned similarly.
Warp Faces: Transform the source face to match the target face’s orientation.

Popular pre-trained models for feature extraction:

Mediapipe Facemesh (TensorFlow.js): Detects 468 facial landmarks.
Dlib: Provides robust facial landmark detection.
OpenCV: Detects up to 68 facial landmarks.

2. Enhancing Face Detection with Landmarks

Step 1: Update the Model for Landmark Detection

Extend the code in FaceSwapScreen.js to use a face landmark detection model:

import React, { useState, useEffect } from 'react';
import { View, Image, StyleSheet, ActivityIndicator } from 'react-native';
import * as tf from '@tensorflow/tfjs';
import * as faceLandmarksDetection from '@tensorflow-models/face-landmarks-detection';

export default function FaceSwapScreen({ route }) {
    const { imageUri } = route.params;
    const [model, setModel] = useState(null);
    const [landmarks, setLandmarks] = useState([]);
    const [loading, setLoading] = useState(true);

    useEffect(() => {
        const loadModel = async () => {
            await tf.ready();
            const loadedModel = await faceLandmarksDetection.load(
                faceLandmarksDetection.SupportedPackages.mediapipeFacemesh
            );
            setModel(loadedModel);
            setLoading(false);
        };

        loadModel();
    }, []);

    useEffect(() => {
        const detectLandmarks = async () => {
            if (!model) return;

            const img = document.createElement('img');
            img.src = imageUri;

            const predictions = await model.estimateFaces({
                input: img,
                returnTensors: false,
            });

            if (predictions.length > 0) {
                console.log('Detected Landmarks:', predictions[0].scaledMesh);
                setLandmarks(predictions[0].scaledMesh);
            }
        };

        detectLandmarks();
    }, [model]);

    return (
        <View style={styles.container}>
            {loading ? (
                <ActivityIndicator size="large" color="#0000ff" />
            ) : (
                <Image source={{ uri: imageUri }} style={styles.image} />
            )}
        </View>
    );
}

const styles = StyleSheet.create({
    container: { flex: 1, justifyContent: 'center', alignItems: 'center' },
    image: { width: 300, height: 400 },
});

3. Visualizing Facial Landmarks

Step 1: Add a Canvas Overlay

Use a Canvas to draw detected landmarks over the face:

import Canvas from 'react-native-canvas';

const drawLandmarks = (canvas, landmarks) => {
    const ctx = canvas.getContext('2d');
    ctx.fillStyle = 'red';

    landmarks.forEach(([x, y]) => {
        ctx.beginPath();
        ctx.arc(x, y, 2, 0, 2 * Math.PI);
        ctx.fill();
    });
};

<Canvas
    ref={(canvas) => {
        if (canvas && landmarks.length > 0) {
            drawLandmarks(canvas, landmarks);
        }
    }}
/>;

4. Aligning Faces for Swapping

Step 1: Perform Affine Transformation

Align the source face to the target face using three key points:

Left Eye
Right Eye
Nose

Example using OpenCV (if installed):

const alignFaces = (sourceLandmarks, targetLandmarks) => {
    const srcTri = [
        sourceLandmarks[33], // Left eye
        sourceLandmarks[263], // Right eye
        sourceLandmarks[1], // Nose
    ];

    const tgtTri = [
        targetLandmarks[33], // Left eye
        targetLandmarks[263], // Right eye
        targetLandmarks[1], // Nose
    ];

    const warpMatrix = cv.getAffineTransform(srcTri, tgtTri);

    // Apply warp to the source image
    const alignedFace = cv.warpAffine(sourceImage, warpMatrix, targetImageSize);
    return alignedFace;
};

5. Testing the Facial Feature Extraction

Step 1: Run the App

Start your development server:

expo start

Step 2: Test with Sample Images

Upload images with clear faces.
Verify the detected landmarks are accurate.
Check if the alignment matches key features like eyes and nose.

6. Key Considerations

Face Orientation: Ensure the app handles rotated or tilted faces correctly.
Landmark Quality: Some models work better with high-resolution images.
Performance Optimization: Process only a single face per image if needed to improve speed.

7. Key Concepts Covered

Facial landmark detection using TensorFlow.js.
Visualizing landmarks with a canvas overlay.
Aligning faces for transformations using affine transformations.

Next Steps

On Day 5, we’ll:

Apply transformations and warping techniques for face swapping.
Learn how to blend the swapped face seamlessly into the target.

References and Links:

SEO Keywords: facial landmark detection tutorial, face alignment in React Native, TensorFlow.js face mesh, affine transformation for face swapping, building deepfake apps.

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