face_detection.py

# backend/core/face_detection.py
import cv2
from ultralytics import YOLO
import numpy as np

class FaceDetector:
    def __init__(self, model_path='yolov8n-face.pt'):
        self.model = YOLO(model_path)
        self.confidence_threshold = 0.5
        
    def detect_faces(self, frame):
        """Detect faces in a frame using YOLO"""
        results = self.model(frame)
        faces = []
        
        for result in results:
            boxes = result.boxes
            for box in boxes:
                if box.conf > self.confidence_threshold:
                    x1, y1, x2, y2 = box.xyxy[0].cpu().numpy().astype(int)
                    face = frame[y1:y2, x1:x2]
                    faces.append({
                        'bbox': (x1, y1, x2, y2),
                        'face_img': face,
                        'confidence': box.conf
                    })
        return faces