faces.py

# Face Detection
import cv2
import mediapipe as mp

class InlineFaceDetector:
    def __init__(self, min_detection_confidence=0.5, bounding_box_color=(0, 255, 0), max_faces=None):
        self.detector = mp.solutions.face_detection.FaceDetection(min_detection_confidence=min_detection_confidence)
        self.color = bounding_box_color
        self.max_faces = max_faces
        self._results = None
        self._boxes = []

    def find_faces(self, img_bgr):
        # Convert BGR -> RGB
        img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
        self._results = self.detector.process(img_rgb)
        boxes = []
        if self._results and self._results.detections:
            detections = self._results.detections
            if self.max_faces is not None:
                detections = detections[: self.max_faces]
            ih, iw = img_bgr.shape[0], img_bgr.shape[1]
            for det in detections:
                box = det.location_data.relative_bounding_box
                bw = int(box.width * iw)
                bh = int(box.height * ih)
                x1 = int(box.xmin * iw)
                y1 = int(box.ymin * ih)
                x2 = x1 + bw
                y2 = y1 + bh
                cx = (x1 + x2) // 2
                cy = (y1 + y2) // 2
                boxes.append((x1, y1, x2, y2, bw, bh, cx, cy))
        self._boxes = boxes

    def draw_detection(self, img_bgr, draw_text=True):
        # Overlay rectangles (and % score) onto the given BGR frame
        if not self._results or not self._results.detections:
            return img_bgr
        detections = self._results.detections
        if self.max_faces is not None:
            detections = detections[: self.max_faces]
        for i, det in enumerate(detections):
            if i >= len(self._boxes):
                break
            x1, y1, x2, y2, _, _, _, _ = self._boxes[i]
            cv2.rectangle(img_bgr, (x1, y1), (x2, y2), self.color, 2)
            if draw_text and det.score:
                pct = int(det.score[0] * 100)
                cv2.putText(img_bgr, f"{pct}%", (x1, y1 - 10), cv2.FONT_HERSHEY_PLAIN, 1.5, self.color, 2)
        return img_bgr

    def get_boxes(self): # Return last parsed face boxes (x1, y1, x2, y2, w, h, cx, cy)
        return self._boxes