🧠 AR Filters Fundamentals

🎯 What are AR Filters?

AR Filters (also called AR effects, lenses, or masks) are real-time augmented reality overlays applied to a camera feed. They use face tracking, body tracking, hand tracking, and background segmentation to place digital content on the user. Popularized by Snapchat, Instagram, TikTok, and Facebook — billions of users interact with AR filters daily.

Why AR Filters Matter

Massive reach: Billions of users across social platforms. Self-expression: Users create and share personalized content. Marketing: Brands use filters for engagement. Low barrier: No app install — just open the camera. Viral potential: Filters can spread rapidly. Monetization: Sponsored filters, brand partnerships.

📌 Face Tracking📌 Real-time📌 Social📌 Viral

# AR filter pipeline (conceptual)
class ARFilterPipeline:
    def __init__(self):
        self.face_tracker = FaceTracker()
        self.body_tracker = BodyTracker()
        self.hand_tracker = HandTracker()
        self.segmenter = BackgroundSegmenter()
        self.renderer = FilterRenderer()
    
    def process_frame(self, camera_frame):
        # 1. Detect face
        face = self.face_tracker.detect(camera_frame)
        
        if face is not None:
            # 2. Get face landmarks (468 points)
            landmarks = self.face_tracker.get_landmarks(face)
            
            # 3. Get blend shapes (52 expressions)
            blendshapes = self.face_tracker.get_blendshapes(face)
            
            # 4. Get 3D face mesh
            mesh = self.face_tracker.get_mesh(face)
            
            # 5. Apply filter effects
            effects = self.apply_effects(landmarks, blendshapes, mesh)
            
            # 6. Render overlay
            output = self.renderer.render(camera_frame, effects)
        else:
            output = camera_frame
        
        return output
    
    def apply_effects(self, landmarks, blendshapes, mesh):
        effects = []
        
        # Face mask
        if self.filter_config.has_mask:
            mask = self.create_mask(mesh)
            effects.append(mask)
        
        # Makeup
        if self.filter_config.has_makeup:
            makeup = self.apply_makeup(landmarks)
            effects.append(makeup)
        
        # Accessories
        if self.filter_config.has_accessories:
            accessories = self.place_accessories(landmarks)
            effects.append(accessories)
        
        # Expression-driven effects
        if blendshapes['jaw_open'] > 0.5:
            effects.append(self.create_particle_effect('fire'))
        
        return effects

😊 Face Tracking & Landmarks

🎯 Detecting and tracking faces

Face tracking detects the face and tracks key facial features: eyes, nose, mouth, eyebrows, jawline. Modern systems (ARKit, ARCore, MediaPipe) provide 468+ 3D landmarks per face, enabling precise effects.

Face Landmarks

468 landmarks: Dense mesh of the face. Key points: Eyes (16 pts each), eyebrows (10 pts), nose (9 pts), mouth (40 pts), jawline (17 pts). 3D coordinates: x, y, z for each landmark. Head pose: Rotation (pitch, yaw, roll) + translation. Tracking: 30-60 fps on mobile.

📍 468 Landmarks👁️ Eyes👄 Mouth🧭 Head Pose

# Face tracking with MediaPipe (Python)
import cv2
import mediapipe as mp

mp_face_mesh = mp.solutions.face_mesh

class FaceTracker:
    def __init__(self):
        self.face_mesh = mp_face_mesh.FaceMesh(
            max_num_faces=1,
            refine_landmarks=True,
            min_detection_confidence=0.5,
            min_tracking_confidence=0.5
        )
    
    def process(self, frame):
        rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        results = self.face_mesh.process(rgb)
        
        if results.multi_face_landmarks:
            landmarks = results.multi_face_landmarks[0]
            return self.extract_landmarks(landmarks, frame.shape)
        return None
    
    def extract_landmarks(self, landmarks, shape):
        h, w = shape[:2]
        points = []
        for lm in landmarks.landmark:
            x = int(lm.x * w)
            y = int(lm.y * h)
            z = lm.z
            points.append((x, y, z))
        return points

# Key landmark indices (MediaPipe Face Mesh)
LANDMARKS = {
    'left_eye': [33, 133, 157, 158, 159, 160, 161, 173],
    'right_eye': [362, 263, 387, 386, 385, 384, 398, 466],
    'left_eyebrow': [70, 63, 105, 66, 107],
    'right_eyebrow': [336, 296, 334, 293, 300],
    'nose': [1, 2, 98, 327, 168, 6, 197, 195, 5],
    'mouth': [61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291, 409, 270, 269, 267, 0, 37, 39, 40, 185],
    'jawline': [172, 136, 150, 149, 176, 148, 152, 377, 400, 378, 379, 365, 397, 288, 361, 323, 454, 356, 389],
    'left_iris': [468, 469, 470, 471, 472],
    'right_iris': [473, 474, 475, 476, 477]
}

# ARKit face tracking (Swift)
"""
let configuration = ARFaceTrackingConfiguration()
configuration.maximumNumberOfTrackedFaces = 1
session.run(configuration)

func session(_ session: ARSession, didUpdate anchors: [ARAnchor]) {
    for anchor in anchors {
        if let faceAnchor = anchor as? ARFaceAnchor {
            let landmarks = faceAnchor.geometry.vertices  // 1220 vertices
            let blendShapes = faceAnchor.blendShapes  // 52 expressions
            let transform = faceAnchor.transform  // head pose
        }
    }
}
"""

# ARCore face tracking (Kotlin)
"""
val config = Config(session).apply {
    faceMode = Config.FaceMode.DEFAULT
}
session.configure(config)

override fun onUpdate(frame: Frame) {
    val faces = frame.getUpdatedTrackables(AugmentedFace::class.java)
    for (face in faces) {
        val mesh = face.mesh  // 3D mesh
        val pose = face.centerPose  // head pose
        val regionPoses = face.getRegionPoses()  // eyes, nose, etc.
    }
}
"""

🎭 Blend Shapes & Expressions

🎯 Reading facial expressions

Blend shapes (shape keys, morph targets) are coefficients that describe facial expressions: smile, frown, blink, jaw open, eyebrow raise. ARKit provides 52 blend shapes; ARCore provides 6. These drive expression-based filter effects.

Key Blend Shapes

Eyes: blink, look up/down/left/right, squint. Mouth: smile, frown, jaw open, pucker, puff. Brows: raise, lower, inner up. Cheeks: puff, squint. Nose: sneer. Tongue: out. Head: rotation + translation. Each blend shape is 0-1.

😊 Smile😮 Jaw Open😉 Blink🤨 Brow Raise

# ARKit blend shapes (Swift)
func session(_ session: ARSession, didUpdate anchors: [ARAnchor]) {
    for anchor in anchors {
        if let faceAnchor = anchor as? ARFaceAnchor {
            let blendShapes = faceAnchor.blendShapes
            
            // Read specific expressions
            let jawOpen = blendShapes[.jawOpen]?.floatValue ?? 0
            let smileLeft = blendShapes[.mouthSmileLeft]?.floatValue ?? 0
            let smileRight = blendShapes[.mouthSmileRight]?.floatValue ?? 0
            let eyeBlinkLeft = blendShapes[.eyeBlinkLeft]?.floatValue ?? 0
            let eyeBlinkRight = blendShapes[.eyeBlinkRight]?.floatValue ?? 0
            let browInnerUp = blendShapes[.browInnerUp]?.floatValue ?? 0
            
            // Detect expressions
            let isSmiling = (smileLeft + smileRight) / 2 > 0.5
            let isBlinking = (eyeBlinkLeft + eyeBlinkRight) / 2 > 0.5
            let isSurprised = jawOpen > 0.5 && browInnerUp > 0.5
            
            // Trigger effects
            if isSmiling {
                showHearts()
            }
            if isBlinking {
                showStars()
            }
            if isSurprised {
                showShockEffect()
            }
        }
    }
}

# MediaPipe blendshapes (Python)
import mediapipe as mp

mp_face_mesh = mp.solutions.face_mesh

face_mesh = mp_face_mesh.FaceMesh(
    max_num_faces=1,
    refine_landmarks=True,
    output_face_blendshapes=True  # Enable blendshapes
)

results = face_mesh.process(rgb_image)
if results.multi_face_landmarks:
    # Get blendshapes
    blendshapes = results.multi_face_blendshapes[0]
    
    for bs in blendshapes:
        print(f"{bs.category_name}: {bs.score:.3f}")
    
    # Example: detect smile
    smile = next((bs.score for bs in blendshapes if bs.category_name == 'mouthSmileLeft'), 0)
    if smile > 0.5:
        print("User is smiling!")

# ARKit 52 blend shapes list
ARKIT_BLENDSHAPES = [
    "browDownLeft", "browDownRight", "browInnerUp",
    "browOuterUpLeft", "browOuterUpRight",
    "cheekPuff", "cheekSquintLeft", "cheekSquintRight",
    "eyeBlinkLeft", "eyeBlinkRight",
    "eyeLookDownLeft", "eyeLookDownRight",
    "eyeLookInLeft", "eyeLookInRight",
    "eyeLookOutLeft", "eyeLookOutRight",
    "eyeLookUpLeft", "eyeLookUpRight",
    "eyeSquintLeft", "eyeSquintRight",
    "eyeWideLeft", "eyeWideRight",
    "jawForward", "jawLeft", "jawOpen", "jawRight",
    "mouthClose", "mouthDimpleLeft", "mouthDimpleRight",
    "mouthFrownLeft", "mouthFrownRight",
    "mouthFunnel", "mouthLeft", "mouthLowerDownLeft",
    "mouthLowerDownRight", "mouthPressLeft", "mouthPressRight",
    "mouthPucker", "mouthRight", "mouthRollLower",
    "mouthRollUpper", "mouthShrugLower", "mouthShrugUpper",
    "mouthSmileLeft", "mouthSmileRight",
    "mouthStretchLeft", "mouthStretchRight",
    "mouthUpperUpLeft", "mouthUpperUpRight",
    "noseSneerLeft", "noseSneerRight",
    "tongueOut"
]

🕸️ 3D Face Mesh

🎯 The geometry of the face

The 3D face mesh is a dense triangulated surface that follows the contours of the face. ARKit provides 1220 vertices and 2300 triangles. This mesh is used for occlusion, makeup, masks, and realistic face filters.

Face Mesh Applications

Occlusion: Hide filter elements behind the face. Makeup: Paint on the mesh surface. Masks: Wrap 3D masks to the face. Deformation: Warp the face (alien, animal). Lighting: Compute normals for realistic shading. Texture: Map textures to the face.

🕸️ 1220 Vertices🎭 Masks💄 Makeup🧱 Occlusion

# MediaPipe Face Mesh (Python + OpenCV)
import cv2
import mediapipe as mp
import numpy as np

mp_face_mesh = mp.solutions.face_mesh
mp_drawing = mp.solutions.drawing_utils

class FaceMeshRenderer:
    def __init__(self):
        self.face_mesh = mp_face_mesh.FaceMesh(
            max_num_faces=1,
            refine_landmarks=True,
            min_detection_confidence=0.5,
            min_tracking_confidence=0.5
        )
    
    def render_mesh(self, frame):
        rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        results = self.face_mesh.process(rgb)
        
        if results.multi_face_landmarks:
            for face_landmarks in results.multi_face_landmarks:
                # Draw tessellation (mesh)
                mp_drawing.draw_landmarks(
                    image=frame,
                    landmark_list=face_landmarks,
                    connections=mp_face_mesh.FACEMESH_TESSELATION,
                    landmark_drawing_spec=None,
                    connection_drawing_spec=mp_drawing.DrawingSpec(
                        color=(0, 255, 0), thickness=1
                    )
                )
                
                # Draw contours
                mp_drawing.draw_landmarks(
                    image=frame,
                    landmark_list=face_landmarks,
                    connections=mp_face_mesh.FACEMESH_CONTOURS,
                    landmark_drawing_spec=None,
                    connection_drawing_spec=mp_drawing.DrawingSpec(
                        color=(255, 0, 0), thickness=2
                    )
                )
        
        return frame

# ARKit face mesh (Swift)
"""
func session(_ session: ARSession, didUpdate anchors: [ARAnchor]) {
    for anchor in anchors {
        if let faceAnchor = anchor as? ARFaceAnchor {
            let geometry = faceAnchor.geometry
            
            // Vertices (1220)
            let vertices = geometry.vertices
            
            // Triangles (2300)
            let triangles = geometry.triangleIndices
            
            // Texture coordinates
            let texCoords = geometry.textureCoordinates
            
            // Build SCNGeometry
            let source = SCNGeometrySource(vertices: vertices)
            let element = SCNGeometryElement(
                indices: triangles,
                primitiveType: .triangles
            )
            let geometry = SCNGeometry(
                sources: [source],
                elements: [element]
            )
            
            // Apply material
            let material = SCNMaterial()
            material.diffuse.contents = UIColor.green.withAlphaComponent(0.5)
            material.isDoubleSided = true
            geometry.materials = [material]
            
            // Create node
            let node = SCNNode(geometry: geometry)
            sceneView.scene.rootNode.addChildNode(node)
        }
    }
}
"""

# Occlusion with face mesh
class FaceOcclusion:
    def __init__(self, face_mesh):
        self.face_mesh = face_mesh
    
    def apply_occlusion(self, filter_element, face_landmarks, frame):
        """Hide filter elements behind the face."""
        # Create mask from face mesh
        mask = np.zeros(frame.shape[:2], dtype=np.uint8)
        
        # Get face contour
        face_points = self.get_face_contour(face_landmarks)
        cv2.fillPoly(mask, [face_points], 255)
        
        # Apply mask to filter element
        filter_element[mask == 0] = 0
        
        return filter_element
    
    def get_face_contour(self, landmarks):
        # Get outer face contour points
        contour_indices = [10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288, 397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136, 172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109]
        return np.array([(landmarks[i].x, landmarks[i].y) for i in contour_indices], dtype=np.int32)

💄 Face Effects (Makeup, Beauty)

🎯 Enhancing and transforming the face

Face effects include: virtual makeup (lipstick, eyeshadow, blush), beauty filters (smooth skin, whiten teeth, enlarge eyes), face morphing (change face shape), and color grading.

Face Effect Types

Makeup: Lipstick, eyeshadow, eyeliner, blush, foundation. Beauty: Skin smoothing, blemish removal, teeth whitening, eye enlargement. Face morph: Slim face, enlarge eyes, change nose shape. Color: Adjust skin tone, apply artistic filters. Retouch: Remove wrinkles, even skin tone.

💄 Makeup✨ Beauty🎨 Color🔄 Morph

# Virtual makeup with face landmarks
import cv2
import numpy as np
import mediapipe as mp

class VirtualMakeup:
    def __init__(self):
        self.face_mesh = mp.solutions.face_mesh.FaceMesh(
            max_num_faces=1,
            refine_landmarks=True
        )
    
    def apply_lipstick(self, frame, landmarks, color=(0, 0, 255)):
        """Apply lipstick to the lips."""
        # Lip landmark indices (outer + inner)
        outer_lips = [61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291, 409, 270, 269, 267, 0, 37, 39, 40, 185]
        inner_lips = [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, 415, 310, 311, 312, 13, 82, 81, 80, 191]
        
        # Get lip points
        outer_points = np.array([
            (landmarks[i].x * frame.shape[1], landmarks[i].y * frame.shape[0])
            for i in outer_lips
        ], dtype=np.int32)
        
        inner_points = np.array([
            (landmarks[i].x * frame.shape[1], landmarks[i].y * frame.shape[0])
            for i in inner_lips
        ], dtype=np.int32)
        
        # Create lip mask
        mask = np.zeros(frame.shape[:2], dtype=np.uint8)
        cv2.fillPoly(mask, [outer_points], 255)
        cv2.fillPoly(mask, [inner_points], 0)  # Inner mouth (hole)
        
        # Apply color
        colored = frame.copy()
        colored[mask > 0] = color
        
        # Blend
        alpha = 0.6
        frame = cv2.addWeighted(frame, 1 - alpha, colored, alpha, 0)
        
        return frame
    
    def apply_eyeshadow(self, frame, landmarks, color=(255, 0, 0)):
        """Apply eyeshadow."""
        # Left eye upper lid
        left_eye = [33, 246, 161, 160, 159, 158, 157, 173, 133, 155, 154, 153, 145, 144, 163, 7]
        # Right eye upper lid
        right_eye = [263, 466, 388, 387, 386, 385, 384, 398, 362, 382, 381, 380, 374, 373, 390, 249]
        
        for eye_indices in [left_eye, right_eye]:
            points = np.array([
                (landmarks[i].x * frame.shape[1], landmarks[i].y * frame.shape[0])
                for i in eye_indices
            ], dtype=np.int32)
            
            # Create mask
            mask = np.zeros(frame.shape[:2], dtype=np.uint8)
            cv2.fillPoly(mask, [points], 255)
            
            # Blur for soft edges
            mask = cv2.GaussianBlur(mask, (15, 15), 0)
            
            # Apply color
            colored = frame.copy()
            colored[mask > 0] = color
            
            # Blend
            alpha = 0.4
            frame = cv2.addWeighted(frame, 1 - alpha, colored, alpha, 0)
        
        return frame
    
    def apply_blush(self, frame, landmarks, color=(147, 20, 255)):
        """Apply blush to cheeks."""
        # Left cheek center
        left_cheek = 234
        # Right cheek center
        right_cheek = 454
        
        for cheek_idx in [left_cheek, right_cheek]:
            x = int(landmarks[cheek_idx].x * frame.shape[1])
            y = int(landmarks[cheek_idx].y * frame.shape[0])
            
            # Create radial gradient
            radius = 40
            for r in range(radius, 0, -5):
                alpha = (1 - r / radius) * 0.3
                cv2.circle(frame, (x, y), r, color, -1)
                # Blend manually
                overlay = frame.copy()
                cv2.circle(overlay, (x, y), r, color, -1)
                frame = cv2.addWeighted(frame, 1 - alpha, overlay, alpha, 0)
        
        return frame
    
    def smooth_skin(self, frame, landmarks):
        """Apply skin smoothing (beauty filter)."""
        # Create face mask
        face_contour = self.get_face_contour(landmarks, frame.shape)
        mask = np.zeros(frame.shape[:2], dtype=np.uint8)
        cv2.fillPoly(mask, [face_contour], 255)
        
        # Bilateral filter for smoothing
        smoothed = cv2.bilateralFilter(frame, 15, 75, 75)
        
        # Blend only in face area
        result = frame.copy()
        result[mask > 0] = smoothed[mask > 0]
        
        return result

🎭 Face Masks & Accessories

🎯 Wearing digital content

Face masks and accessories are 3D models or 2D images placed on the face: glasses, hats, ears, animal faces, helmets, and full-face masks. They're anchored to face landmarks and follow head movement.

Mask Types

Full face: Replace the entire face (animal, alien). Partial: Add elements (ears, horns, nose). Accessories: Glasses, hats, jewelry. Anchored: Follow specific landmarks (nose, eyes). Occlusion: Hide behind face when needed. Blendshapes: Deform with expressions.

🐱 Animal👓 Glasses🎩 Hat👽 Alien

// AR face mask in Unity (AR Foundation)
using UnityEngine;
using UnityEngine.XR.ARFoundation;
using UnityEngine.XR.ARSubsystems;

public class ARFaceMask : MonoBehaviour {
    public ARFaceManager faceManager;
    public GameObject maskPrefab;
    public GameObject glassesPrefab;
    public GameObject hatPrefab;
    
    void OnEnable() {
        faceManager.facesChanged += OnFacesChanged;
    }
    
    void OnFacesChanged(ARFacesChangedEventArgs args) {
        // Added faces
        foreach (var face in args.added) {
            // Create mask
            var mask = Instantiate(maskPrefab, face.transform);
            mask.transform.localPosition = Vector3.zero;
            mask.transform.localRotation = Quaternion.identity;
            
            // Create glasses (anchored to eyes)
            var glasses = Instantiate(glassesPrefab, face.transform);
            glasses.transform.localPosition = new Vector3(0, 0.05f, 0.1f);
            
            // Create hat (anchored to head)
            var hat = Instantiate(hatPrefab, face.transform);
            hat.transform.localPosition = new Vector3(0, 0.15f, 0);
        }
        
        // Updated faces
        foreach (var face in args.updated) {
            // Face mesh updates automatically
            // Update blend shape driven effects
            UpdateBlendshapeEffects(face);
        }
        
        // Removed faces
        foreach (var face in args.removed) {
            // Clean up
        }
    }
    
    void UpdateBlendshapeEffects(ARFace face) {
        // Get blend shapes
        var blendShapes = face.blendShapes;
        
        // Jaw open -> mouth opens
        if (blendShapes.TryGetValue(ARFaceBlendShape.JawOpen, out float jawOpen)) {
            // Animate mask mouth
            maskPrefab.GetComponent().SetJawOpen(jawOpen);
        }
        
        // Eye blink -> eyes close
        if (blendShapes.TryGetValue(ARFaceBlendShape.EyeBlinkLeft, out float blinkLeft)) {
            // Animate left eye
        }
        
        // Smile -> trigger effect
        if (blendShapes.TryGetValue(ARFaceBlendShape.MouthSmileLeft, out float smile)) {
            if (smile > 0.5f) {
                TriggerSmileEffect();
            }
        }
    }
}

// 3D mask placement with landmark anchoring
public class MaskPlacement : MonoBehaviour {
    public ARFace face;
    public GameObject noseAccessory;
    public GameObject earAccessory;
    
    void Update() {
        // Get landmark positions from face mesh
        var mesh = face.GetComponent();
        
        if (mesh != null && mesh.vertices.IsCreated) {
            // Nose tip (vertex index varies by mesh)
            int noseTipIndex = GetNoseTipIndex();
            Vector3 noseTip = mesh.vertices[noseTipIndex];
            
            // Place nose accessory
            noseAccessory.transform.localPosition = noseTip;
            
            // Left ear
            int leftEarIndex = GetLeftEarIndex();
            Vector3 leftEar = mesh.vertices[leftEarIndex];
            earAccessory.transform.localPosition = leftEar;
        }
    }
}

// Spark AR face mask (JavaScript)
/*
const Scene = require('Scene');
const FaceTracking = require('FaceTracking');

const face = FaceTracking.face(0);

// Create mask
const mask = Scene.root.find('mask');

// Anchor to face
mask.transform.position = face.cameraTransform.position;
mask.transform.rotation = face.cameraTransform.rotation;

// Drive with blendshapes
const jawOpen = face.mouth.openness;
mask.child('mouth').transform.scaleY = jawOpen;

const eyeLeft = face.eye.left.closure;
mask.child('eyeLeft').transform.scaleY = eyeLeft;
*/

🌈 Background Segmentation

🎯 Separating person from background

Background segmentation separates the person from the background, enabling: background replacement, background blur, virtual backgrounds, and green screen effects — all without a green screen.

Segmentation Techniques

Person segmentation: Separate person from background. Hair segmentation: Precise hair matting. Body segmentation: Separate body parts. Depth-based: Use depth for better edges. ML-based: MediaPipe, ARKit, ARCore. Applications: Virtual backgrounds, blur, effects.

🧑 Person💇 Hair🏃 Body🌫️ Blur

# Background segmentation with MediaPipe
import cv2
import mediapipe as mp
import numpy as np

mp_selfie_segmentation = mp.solutions.selfie_segmentation

class BackgroundSegmenter:
    def __init__(self):
        self.segmenter = mp_selfie_segmentation.SelfieSegmentation(
            model_selection=1  # 0 = general, 1 = landscape
        )
    
    def process(self, frame):
        rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        results = self.segmenter.process(rgb)
        
        # Get segmentation mask
        mask = results.segmentation_mask  # (H, W) values 0-1
        
        # Threshold
        mask = (mask > 0.5).astype(np.uint8) * 255
        
        # Smooth edges
        mask = cv2.GaussianBlur(mask, (5, 5), 0)
        mask = mask / 255.0
        
        return mask
    
    def replace_background(self, frame, background):
        """Replace background with an image."""
        mask = self.process(frame)
        
        # Resize background to match frame
        bg = cv2.resize(background, (frame.shape[1], frame.shape[0]))
        
        # Composite
        mask_3ch = np.stack([mask] * 3, axis=-1)
        result = frame * mask_3ch + bg * (1 - mask_3ch)
        
        return result.astype(np.uint8)
    
    def blur_background(self, frame, blur_amount=25):
        """Blur the background."""
        mask = self.process(frame)
        
        # Blur entire frame
        blurred = cv2.GaussianBlur(frame, (blur_amount, blur_amount), 0)
        
        # Composite
        mask_3ch = np.stack([mask] * 3, axis=-1)
        result = frame * mask_3ch + blurred * (1 - mask_3ch)
        
        return result.astype(np.uint8)
    
    def virtual_green_screen(self, frame, color=(0, 255, 0)):
        """Replace background with solid color."""
        mask = self.process(frame)
        
        # Create solid color background
        bg = np.full_like(frame, color)
        
        # Composite
        mask_3ch = np.stack([mask] * 3, axis=-1)
        result = frame * mask_3ch + bg * (1 - mask_3ch)
        
        return result.astype(np.uint8)

# ARKit person segmentation (Swift)
"""
let configuration = ARWorldTrackingConfiguration()
configuration.frameSemantics = [.personSegmentationWithDepth]
session.run(configuration)

func session(_ session: ARSession, didUpdate frame: ARFrame) {
    guard let segmentationBuffer = frame.segmentationBuffer else { return }
    // Apply segmentation as mask
    // Occlude virtual content behind person
}
"""

# ARCore depth-based segmentation (Kotlin)
"""
val config = Config(session).apply {
    depthMode = Config.DepthMode.AUTOMATIC
}
session.configure(config)

override fun onUpdate(frame: Frame) {
    if (frame.hasDepth()) {
        val depthImage = frame.acquireDepthImage16Bits()
        // Use depth for background segmentation
    }
}
"""

🏃 Body Tracking Filters

🎯 Full-body AR effects

Body tracking detects and tracks the human body: pose (33+ keypoints), skeleton, and segmentation. Enables: virtual try-on, dance effects, body morphs, and interactive filters.

Body Tracking Features

Pose estimation: 33 keypoints (BlazePose). Skeleton: Full body joint positions. Segmentation: Separate body from background. Virtual try-on: Clothes, shoes, accessories. Dance effects: Trigger effects on movement. Body morphs: Change body shape.

🦴 33 Keypoints👕 Try-on💃 Dance🔄 Morph

# Body tracking with MediaPipe Pose
import cv2
import mediapipe as mp
import numpy as np

mp_pose = mp.solutions.pose

class BodyTracker:
    def __init__(self):
        self.pose = mp_pose.Pose(
            static_image_mode=False,
            model_complexity=1,
            smooth_landmarks=True,
            min_detection_confidence=0.5,
            min_tracking_confidence=0.5
        )
    
    def process(self, frame):
        rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        results = self.pose.process(rgb)
        
        if results.pose_landmarks:
            landmarks = []
            for lm in results.pose_landmarks.landmark:
                landmarks.append({
                    'x': lm.x,
                    'y': lm.y,
                    'z': lm.z,
                    'visibility': lm.visibility
                })
            return landmarks
        return None
    
    def detect_pose(self, landmarks):
        """Detect specific poses from landmarks."""
        poses = []
        
        # Check if arms are raised (dab pose)
        left_wrist = landmarks[15]
        right_wrist = landmarks[16]
        left_shoulder = landmarks[11]
        right_shoulder = landmarks[12]
        
        if left_wrist['y'] < left_shoulder['y'] and right_wrist['y'] < right_shoulder['y']:
            poses.append('arms_up')
        
        # Check for T-pose
        if abs(left_wrist['y'] - left_shoulder['y']) < 0.1 and \
           abs(right_wrist['y'] - right_shoulder['y']) < 0.1:
            poses.append('t_pose')
        
        # Check for hands on hips
        left_hip = landmarks[23]
        right_hip = landmarks[24]
        if abs(left_wrist['x'] - left_hip['x']) < 0.1 and \
           abs(right_wrist['x'] - right_hip['x']) < 0.1:
            poses.append('hands_on_hips')
        
        return poses

# Virtual try-on (clothes)
class VirtualTryOn:
    def __init__(self):
        self.body_tracker = BodyTracker()
    
    def overlay_clothes(self, frame, shirt_image):
        """Overlay a virtual shirt on the user."""
        landmarks = self.body_tracker.process(frame)
        
        if landmarks is None:
            return frame
        
        # Get shoulder and hip positions
        left_shoulder = landmarks[11]
        right_shoulder = landmarks[12]
        left_hip = landmarks[23]
        right_hip = landmarks[24]
        
        # Compute shirt position and scale
        shoulder_width = abs(right_shoulder['x'] - left_shoulder['x']) * frame.shape[1]
        torso_height = abs(left_hip['y'] - left_shoulder['y']) * frame.shape[0]
        
        # Resize shirt
        shirt_resized = cv2.resize(shirt_image, (int(shoulder_width * 1.5), int(torso_height * 1.2)))
        
        # Compute position
        center_x = int((left_shoulder['x'] + right_shoulder['x']) / 2 * frame.shape[1])
        center_y = int((left_shoulder['y'] + left_hip['y']) / 2 * frame.shape[0])
        
        # Overlay
        x = center_x - shirt_resized.shape[1] // 2
        y = center_y - shirt_resized.shape[0] // 2
        
        # Simple alpha blend
        if x >= 0 and y >= 0 and x + shirt_resized.shape[1] <= frame.shape[1] and y + shirt_resized.shape[0] <= frame.shape[0]:
            roi = frame[y:y+shirt_resized.shape[0], x:x+shirt_resized.shape[1]]
            # Assume shirt has alpha channel
            if shirt_resized.shape[2] == 4:
                alpha = shirt_resized[:, :, 3] / 255.0
                alpha_3ch = np.stack([alpha] * 3, axis=-1)
                frame[y:y+shirt_resized.shape[0], x:x+shirt_resized.shape[1]] = \
                    roi * (1 - alpha_3ch) + shirt_resized[:, :, :3] * alpha_3ch
        
        return frame

# Dance effect triggered by movement
class DanceEffect:
    def __init__(self):
        self.body_tracker = BodyTracker()
        self.prev_landmarks = None
    
    def detect_movement(self, landmarks):
        """Detect movement intensity."""
        if self.prev_landmarks is None:
            self.prev_landmarks = landmarks
            return 0
        
        # Compute average movement
        movement = 0
        for i in range(len(landmarks)):
            dx = landmarks[i]['x'] - self.prev_landmarks[i]['x']
            dy = landmarks[i]['y'] - self.prev_landmarks[i]['y']
            movement += np.sqrt(dx**2 + dy**2)
        
        movement /= len(landmarks)
        self.prev_landmarks = landmarks
        
        return movement
    
    def trigger_effect(self, frame, movement):
        """Trigger visual effect based on movement."""
        if movement > 0.05:  # Fast movement
            # Add particle effect
            h, w = frame.shape[:2]
            for _ in range(10):
                x = np.random.randint(0, w)
                y = np.random.randint(0, h)
                color = (np.random.randint(0, 255), np.random.randint(0, 255), np.random.randint(0, 255))
                cv2.circle(frame, (x, y), 5, color, -1)
        
        return frame

✋ Hand Tracking Filters

🎯 Effects on your hands

Hand tracking filters place digital content on the hands: nails, rings, gloves, magic effects, and interactive gestures. Uses 21 landmarks per hand for precise placement.

Hand Filter Types

Nail polish: Color the fingernails. Rings: Virtual jewelry. Gloves: Full hand overlay. Magic effects: Particles from fingertips. Gestures: Trigger effects with hand poses. Interactive: Touch virtual objects.

💅 Nails💍 Rings🧤 Gloves✨ Magic

# Hand tracking filters with MediaPipe
import cv2
import mediapipe as mp
import numpy as np

mp_hands = mp.solutions.hands

class HandFilter:
    def __init__(self):
        self.hands = mp_hands.Hands(
            static_image_mode=False,
            max_num_hands=2,
            min_detection_confidence=0.5,
            min_tracking_confidence=0.5
        )
    
    def process(self, frame):
        rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        results = self.hands.process(rgb)
        
        if results.multi_hand_landmarks:
            for hand_landmarks in results.multi_hand_landmarks:
                self.apply_effects(frame, hand_landmarks)
        
        return frame
    
    def apply_nail_polish(self, frame, hand_landmarks, color=(255, 0, 255)):
        """Apply nail polish to fingertips."""
        # Fingertip landmark indices
        fingertips = [4, 8, 12, 16, 20]  # Thumb, Index, Middle, Ring, Pinky
        
        h, w = frame.shape[:2]
        
        for tip_idx in fingertips:
            tip = hand_landmarks.landmark[tip_idx]
            x = int(tip.x * w)
            y = int(tip.y * h)
            
            # Create nail shape (ellipse)
            cv2.ellipse(frame, (x, y), (8, 12), 0, 0, 360, color, -1)
        
        return frame
    
    def apply_magic_effect(self, frame, hand_landmarks):
        """Emit particles from fingertips."""
        fingertips = [4, 8, 12, 16, 20]
        
        h, w = frame.shape[:2]
        
        for tip_idx in fingertips:
            tip = hand_landmarks.landmark[tip_idx]
            x = int(tip.x * w)
            y = int(tip.y * h)
            
            # Draw glow
            for r in range(20, 0, -4):
                alpha = (1 - r / 20) * 0.5
                overlay = frame.copy()
                cv2.circle(overlay, (x, y), r, (255, 255, 0), -1)
                frame = cv2.addWeighted(frame, 1 - alpha, overlay, alpha, 0)
        
        return frame
    
    def apply_ring(self, frame, hand_landmarks, finger='ring'):
        """Apply a virtual ring."""
        finger_indices = {
            'thumb': (1, 2, 3, 4),
            'index': (5, 6, 7, 8),
            'middle': (9, 10, 11, 12),
            'ring': (13, 14, 15, 16),
            'pinky': (17, 18, 19, 20)
        }
        
        indices = finger_indices[finger]
        # Get the proximal phalanx (between MCP and PIP)
        mcp = hand_landmarks.landmark[indices[0]]
        pip = hand_landmarks.landmark[indices[1]]
        
        h, w = frame.shape[:2]
        x = int((mcp.x + pip.x) / 2 * w)
        y = int((mcp.y + pip.y) / 2 * h)
        
        # Draw ring
        cv2.circle(frame, (x, y), 8, (0, 215, 255), 3)
        
        return frame
    
    def detect_gesture(self, hand_landmarks):
        """Detect hand gestures."""
        # Get finger states (extended or curled)
        fingers = []
        
        # Thumb
        if hand_landmarks.landmark[4].x < hand_landmarks.landmark[3].x:
            fingers.append(1)
        else:
            fingers.append(0)
        
        # Other fingers
        for tip, pip in [(8, 6), (12, 10), (16, 14), (20, 18)]:
            if hand_landmarks.landmark[tip].y < hand_landmarks.landmark[pip].y:
                fingers.append(1)
            else:
                fingers.append(0)
        
        # Classify gesture
        if fingers == [0, 1, 0, 0, 0]:
            return 'pointing'
        elif fingers == [0, 1, 1, 0, 0]:
            return 'peace'
        elif fingers == [1, 0, 0, 0, 0]:
            return 'thumbs_up'
        elif fingers == [0, 0, 0, 0, 0]:
            return 'fist'
        elif fingers == [1, 1, 1, 1, 1]:
            return 'open_palm'
        elif fingers == [1, 1, 0, 0, 1]:
            return 'rock'
        else:
            return 'unknown'

🌍 World Filters

🎯 Effects in the environment

World filters place AR content in the environment: portals, floating objects, creatures, weather effects, and interactive scenes. Uses plane detection, SLAM, and spatial mapping.

World Filter Types

Portals: Look into another world. Floating objects: Hover in space. Creatures: Animals in the room. Weather: Rain, snow, fire. Environment: Change walls, floor. Interactive: Touch, move, play.

🌀 Portal🐉 Creatures🌧️ Weather🏠 Environment

// World filter in Unity (AR Foundation)
using UnityEngine;
using UnityEngine.XR.ARFoundation;
using UnityEngine.XR.ARSubsystems;

public class WorldFilter : MonoBehaviour {
    public ARPlaneManager planeManager;
    public ARRaycastManager raycastManager;
    public GameObject portalPrefab;
    public GameObject creaturePrefab;
    public GameObject weatherPrefab;
    
    void Update() {
        // Place content on tap
        if (Input.touchCount > 0 && Input.GetTouch(0).phase == TouchPhase.Began) {
            PlaceContent(Input.GetTouch(0).position);
        }
    }
    
    void PlaceContent(Vector2 touchPosition) {
        // Raycast against planes
        var hits = new List();
        if (raycastManager.Raycast(touchPosition, hits, TrackableType.PlaneWithinPolygon)) {
            var hitPose = hits[0].pose;
            
            // Create portal at hit position
            var portal = Instantiate(portalPrefab, hitPose.position, hitPose.rotation);
            
            // Add floating creature
            var creature = Instantiate(creaturePrefab, hitPose.position + Vector3.up * 1.5f, Quaternion.identity);
            
            // Add weather effect
            var weather = Instantiate(weatherPrefab, hitPose.position + Vector3.up * 3f, Quaternion.identity);
        }
    }
    
    // Portal effect
    void CreatePortal(Vector3 position, Quaternion rotation) {
        var portal = Instantiate(portalPrefab, position, rotation);
        
        // Portal camera renders a different scene
        var portalCamera = portal.GetComponentInChildren();
        portalCamera.targetTexture = new RenderTexture(1024, 1024, 24);
        
        // Portal material shows the render texture
        var portalRenderer = portal.GetComponent();
        portalRenderer.material.mainTexture = portalCamera.targetTexture;
    }
    
    // Floating creature that follows the user
    void CreateCreature(Vector3 position) {
        var creature = Instantiate(creaturePrefab, position, Quaternion.identity);
        
        // Make it float
        var floatScript = creature.AddComponent();
        floatScript.amplitude = 0.2f;
        floatScript.frequency = 1.0f;
        
        // Make it look at the user
        var lookAtUser = creature.AddComponent();
    }
    
    // Weather effect
    void CreateWeather(Vector3 position) {
        var weather = Instantiate(weatherPrefab, position, Quaternion.identity);
        
        // Particle system for rain/snow
        var particles = weather.GetComponent();
        var main = particles.main;
        main.startColor = Color.white;
        main.startSize = 0.05f;
        main.startSpeed = 5.0f;
        main.maxParticles = 1000;
    }
}

// Portal effect with render texture
public class PortalEffect : MonoBehaviour {
    public Camera portalCamera;
    public RenderTexture portalTexture;
    public Material portalMaterial;
    public Transform playerCamera;
    
    void Update() {
        // Position portal camera to render the virtual world
        // from the perspective of the portal
        Vector3 playerOffsetFromPortal = playerCamera.position - transform.position;
        portalCamera.transform.position = transform.position - playerOffsetFromPortal;
        
        // Rotate to look through the portal
        portalCamera.transform.rotation = Quaternion.LookRotation(
            -playerOffsetFromPortal,
            playerCamera.up
        );
        
        // Render
        portalCamera.Render();
    }
}

// Spark AR world filter (JavaScript)
/*
const Scene = require('Scene');
const PlaneTracking = require('PlaneTracking');

// Detect planes
const planes = PlaneTracking.planeTracking.planes;

// Place content on planes
planes.forEach(plane => {
    const content = Scene.root.find('content');
    content.transform.position = plane.center;
    content.transform.rotation = plane.rotation;
});

// Tap to place
Scene.root.find('touchGesture').onTap.subscribe(() => {
    // Place at tap position
});
*/

✨ Spark AR Studio

🎯 Meta's AR filter tool

Spark AR Studio (now Meta Spark) is Meta's AR creation platform for Instagram and Facebook filters. It uses a node-based visual editor with JavaScript scripting. Features: face tracking, hand tracking, body tracking, plane tracking, and more.

Spark AR Features

Visual editor: Node-based, no coding required. JavaScript API: For advanced logic. Face tracking: 68+ landmarks, blendshapes. Hand tracking: 21 landmarks. Body tracking: Full body. Plane tracking: For world effects. Publishing: Instagram, Facebook, Messenger.

📱 Instagram📘 Facebook🎨 Visual Editor💻 JavaScript

// Spark AR: Face mask with blendshapes (JavaScript)
const Scene = require('Scene');
const FaceTracking = require('FaceTracking');
const Reactive = require('Reactive');
const Animation = require('Animation');

// Get face
const face = FaceTracking.face(0);

// Get mask object
const mask = Scene.root.find('mask');

// Anchor mask to face
mask.transform.position = face.cameraTransform.position;
mask.transform.rotation = face.cameraTransform.rotation;

// Jaw open animation
const jawOpen = face.mouth.openness;
const mouth = mask.child('mouth');
mouth.transform.scaleY = Reactive.add(1, Reactive.mul(jawOpen, 0.5));

// Eye blink
const eyeLeftClosure = face.eye.left.closure;
const eyeLeft = mask.child('eyeLeft');
eyeLeft.transform.scaleY = Reactive.sub(1, eyeLeftClosure);

const eyeRightClosure = face.eye.right.closure;
const eyeRight = mask.child('eyeRight');
eyeRight.transform.scaleY = Reactive.sub(1, eyeRightClosure);

// Smile trigger
const smileLeft = face.mouth.smileLeft;
const smileRight = face.mouth.smileRight;
const smileAvg = Reactive.div(Reactive.add(smileLeft, smileRight), 2);

// Show hearts when smiling
const hearts = Scene.root.find('hearts');
hearts.hidden = Reactive.lt(smileAvg, 0.5);

// Head rotation
const headRotation = face.cameraTransform.rotation;
mask.transform.rotation = headRotation;

// Spark AR: Hand tracking filter
const HandTracking = require('HandTracking');
const hand = HandTracking.hand(0);

// Get index fingertip
const indexTip = hand.indexFinger.tip;
const effect = Scene.root.find('magicEffect');
effect.transform.position = indexTip.worldPosition;

// Pinch detection
const thumbTip = hand.thumb.tip;
const distance = Reactive.distance(indexTip.worldPosition, thumbTip.worldPosition);
const isPinching = Reactive.lt(distance, 0.05);
effect.hidden = Reactive.not(isPinching);

// Spark AR: Body tracking filter
const BodyTracking = require('BodyTracking');
const body = BodyTracking.body(0);

// Get shoulders
const leftShoulder = body.leftArm.shoulder;
const rightShoulder = body.rightArm.shoulder;

// Place virtual shirt
const shirt = Scene.root.find('shirt');
shirt.transform.position = body.center;
shirt.transform.rotation = body.rotation;

// Spark AR: Plane tracking filter
const PlaneTracking = require('PlaneTracking');
const planes = PlaneTracking.planeTracking.planes;

// Place content on planes
planes.forEach((plane, index) => {
    const content = Scene.root.find('content' + index);
    content.transform.position = plane.center;
    content.transform.rotation = plane.rotation;
});

// Spark AR: Publishing
/*
1. Create project in Spark AR Studio
2. Design filter (masks, effects, interactions)
3. Test in Spark AR Player (simulator)
4. Test on device via Spark AR app
5. Submit for review
6. Publish to Instagram/Facebook
7. Monitor analytics
*/

🎨 Effect House (TikTok)

🎯 TikTok's AR filter tool

Effect House is TikTok's AR effect creation platform. It offers face tracking, body tracking, hand tracking, and a visual scripting system. Effects can go viral on TikTok, reaching millions of users.

Effect House Features

Visual scripting: Node-based, no coding. Face tracking: Landmarks + blendshapes. Body tracking: 3D pose. Hand tracking: 21 landmarks. Green screen: Background segmentation. Publishing: Direct to TikTok. Analytics: Track usage.

🎵 TikTok🎨 Visual Scripting🟢 Green Screen📊 Analytics

// Effect House: Visual scripting (conceptual)
// Effect House uses a node-based visual scripting system

// Face mask setup
FaceTracker → FaceMesh → MaskMaterial → RenderOutput

// Blendshape-driven animation
FaceTracker.JawOpen → Multiply(0.5) → Add(1) → Mask.Mouth.ScaleY
FaceTracker.EyeBlinkLeft → Invert → Mask.EyeLeft.ScaleY
FaceTracker.MouthSmile → GreaterThan(0.5) → TriggerHearts

// Hand tracking filter
HandTracker.IndexTip → Position → MagicEffect.Position
HandTracker.Pinch → If → ShowParticles

// Body tracking filter
BodyTracker.Skeleton → PoseDetection → DanceEffect

// Background segmentation
Camera → PersonSegmentation → Mask → Composite(Background)

// Effect House: JavaScript-like scripting
// (Effect House supports a visual scripting language)

// Face mask
const face = await EffectHouse.FaceTracker.getFace(0);
const mask = EffectHouse.Scene.find('mask');

mask.transform.position = face.position;
mask.transform.rotation = face.rotation;

// Jaw open
const jawOpen = face.blendshapes.jawOpen;
mask.find('mouth').scaleY = 1 + jawOpen * 0.5;

// Smile trigger
const smile = face.blendshapes.mouthSmile;
if (smile > 0.5) {
    EffectHouse.Scene.find('hearts').visible = true;
} else {
    EffectHouse.Scene.find('hearts').visible = false;
}

// Hand tracking
const hand = await EffectHouse.HandTracker.getHand(0);
const indexTip = hand.landmarks.indexTip;
const effect = EffectHouse.Scene.find('effect');
effect.position = indexTip.position;

// Body tracking
const body = await EffectHouse.BodyTracker.getBody(0);
const shirt = EffectHouse.Scene.find('shirt');
shirt.position = body.center;
shirt.rotation = body.rotation;

// Green screen
const segmentation = await EffectHouse.Segmentation.getMask();
const background = EffectHouse.Scene.find('background');
background.mask = segmentation;

// Publishing
/*
1. Create effect in Effect House
2. Test in simulator
3. Test on device (TikTok app)
4. Submit for review
5. Publish to TikTok
6. Track analytics (views, uses, shares)
7. Iterate and improve
*/

👻 Snap Lens Studio

🎯 Snapchat's AR filter tool

Lens Studio is Snapchat's AR creation platform. It's the most mature AR filter tool, with advanced features: face tracking, body tracking, hand tracking, world tracking, and custom shaders. Used by millions of creators.

Lens Studio Features

Face tracking: 68+ landmarks, blendshapes. Body tracking: 3D skeleton. Hand tracking: 21 landmarks. World tracking: SLAM, surface detection. Custom shaders: GLSL. Scripting: JavaScript API. Publishing: Snapchat.

👻 Snapchat🎨 Custom Shaders💻 JavaScript🌍 World Tracking

// Lens Studio: Face mask (JavaScript)
//@input Component.ScriptComponent faceMesh
//@input SceneObject mask

var faceMesh = script.faceMesh;
var mask = script.mask;

// Update mask position from face
function updateMask() {
    var faceTransform = faceMesh.getTransform();
    mask.getTransform().setWorldPosition(faceTransform.getWorldPosition());
    mask.getTransform().setWorldRotation(faceTransform.getWorldRotation());
}

// Blendshape-driven animation
var jawOpen = faceMesh.getBlendshapeValue("jawOpen");
mask.getChild(0).getTransform().setLocalScale(new vec3(1, 1 + jawOpen * 0.5, 1));

// Eye blink
var eyeBlinkLeft = faceMesh.getBlendshapeValue("eyeBlinkLeft");
mask.getChild(1).getTransform().setLocalScale(new vec3(1, 1 - eyeBlinkLeft, 1));

// Smile trigger
var smileLeft = faceMesh.getBlendshapeValue("mouthSmileLeft");
var smileRight = faceMesh.getBlendshapeValue("mouthSmileRight");
var smileAvg = (smileLeft + smileRight) / 2;

if (smileAvg > 0.5) {
    // Show hearts
    global.heartsEnabled = true;
}

// Lens Studio: Hand tracking
//@input Component.ScriptComponent handTracking
//@input SceneObject magicEffect

var handTracking = script.handTracking;
var magicEffect = script.magicEffect;

function updateHandEffect() {
    var hand = handTracking.getHand(0);
    if (hand.isTracked()) {
        var indexTip = hand.getLandmark("indexTip");
        magicEffect.getTransform().setWorldPosition(indexTip.getPosition());
        
        // Pinch detection
        var thumbTip = hand.getLandmark("thumbTip");
        var distance = indexTip.getPosition().distance(thumbTip.getPosition());
        
        if (distance < 5.0) {
            magicEffect.enabled = true;
        } else {
            magicEffect.enabled = false;
        }
    }
}

// Lens Studio: Custom shader (GLSL)
/*
//@input Asset.Material maskMaterial

// Fragment shader
varying vec2 uv;
uniform sampler2D faceTexture;
uniform float time;

void main() {
    vec4 color = texture2D(faceTexture, uv);
    
    // Add glow effect
    float glow = sin(time * 2.0) * 0.5 + 0.5;
    color.rgb += vec3(glow, 0.0, glow);
    
    gl_FragColor = color;
}
*/

// Lens Studio: Publishing
/*
1. Create lens in Lens Studio
2. Test in preview
3. Test on device (Snapchat app)
4. Submit for review
5. Publish to Snapchat
6. Track analytics
7. Iterate
*/

// Lens Studio: Advanced features
// - Face mesh deformation
// - Body tracking with 3D skeleton
// - World tracking with surface detection
// - Custom shaders (GLSL)
// - Physics simulation
// - Audio reactive effects
// - Multi-face tracking
// - Voice ML

🚀 Future: AI-Generated Filters

🎯 The next generation of AR filters

AI is transforming AR filters: generative filters (text-to-filter), AI avatars, real-time style transfer, neural face reenactment, and personalized effects.

AI in AR Filters

Generative: Create filters from text prompts. Style transfer: Real-time artistic filters. Face reenactment: Control a 3D avatar with your face. AI avatars: Photorealistic digital humans. Personalization: Filters adapt to the user. Neural rendering: Photorealistic effects.

🎨 Text-to-Filter🖌️ Style Transfer🧑 AI Avatar🧠 Neural

# AI-generated AR filters
import torch
from diffusers import StableDiffusionPipeline

class AIFilterGenerator:
    """Generate AR filters from text prompts."""
    def __init__(self):
        self.sd = StableDiffusionPipeline.from_pretrained(
            "runwayml/stable-diffusion-v1-5"
        ).to("cuda")
    
    def generate_filter(self, prompt):
        """Generate a filter texture from text prompt."""
        # Generate 2D filter texture
        image = self.sd(prompt).images[0]
        
        # Convert to filter elements
        filter_elements = self.extract_elements(image)
        
        return filter_elements
    
    def extract_elements(self, image):
        """Extract filter elements (mask, texture, effects)."""
        return {
            'texture': image,
            'mask': self.generate_mask(image),
            'effects': self.generate_effects(image)
        }

# Real-time style transfer for AR filters
class StyleTransferFilter:
    def __init__(self):
        self.model = load_model("style_transfer")
    
    def apply_style(self, frame, style_image):
        """Apply artistic style to the frame in real-time."""
        # Fast neural style transfer
        styled = self.model(frame, style_image)
        return styled

# Face reenactment for AI avatars
class FaceReenactment:
    def __init__(self):
        self.model = load_model("face_reenactment")
    
    def animate_avatar(self, avatar_image, face_landmarks, blendshapes):
        """Animate a 3D avatar with the user's facial expressions."""
        # Drive avatar with blendshapes
        animated = self.model(avatar_image, blendshapes)
        return animated

# Personalized filters
class PersonalizedFilter:
    def __init__(self):
        self.user_profile = {}
    
    def adapt_filter(self, user_data):
        """Adapt filter based on user preferences and behavior."""
        # Track user interactions
        # Learn preferences
        # Generate personalized effects
        pass

# Neural face rendering
class NeuralFaceRenderer:
    def __init__(self):
        self.nerf = load_model("nerf_face")
    
    def render_face(self, camera_pose, expression):
        """Render photorealistic face from any viewpoint."""
        image = self.nerf(camera_pose, expression)
        return image

# Future: Text-to-Filter pipeline
"""
User types: "Make me look like a cyberpunk hacker"

AI generates:
1. Neon face paint texture
2. Glowing eye effect
3. Circuit board pattern overlay
4. Holographic glitch effect
5. Appropriate sound effects

Result: Custom AR filter in seconds
"""

# Future: AI-powered Spark AR
"""
Spark AR + AI:
- Text-to-filter generation
- Real-time style transfer
- AI-driven animation
- Personalized effects
- Neural rendering
"""

# Future: AI-powered Effect House
"""
Effect House + AI:
- Generate 3D assets from text
- AI-driven effects
- Real-time style transfer
- Smart segmentation
- Personalized filters
"""

# Future: AI-powered Lens Studio
"""
Lens Studio + AI:
- Text-to-3D for filters
- Neural style transfer
- AI face reenactment
- Generative backgrounds
- Real-time neural rendering
"""
  