feat: Face detection with YOLOv8n-face and MediaPipe

yolov8n/.gitignore

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+yolo_face_env/

yolov8n/README.md

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+

yolov8n/requirements.txt

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+appnope==0.1.4
+asttokens==3.0.0
+certifi==2025.8.3
+charset-normalizer==3.4.3
+comm==0.2.2
+contourpy==1.3.3
+cycler==0.12.1
+debugpy==1.8.13
+decorator==5.2.1
+executing==2.2.0
+filelock==3.19.1
+fonttools==4.59.2
+fsspec==2025.9.0
+idna==3.10
+ipykernel==6.29.5
+ipython==9.1.0
+ipython_pygments_lexers==1.1.1
+jedi==0.19.2
+Jinja2==3.1.6
+jupyter_client==8.6.3
+jupyter_core==5.7.2
+kiwisolver==1.4.9
+MarkupSafe==3.0.2
+matplotlib==3.10.6
+matplotlib-inline==0.1.7
+mpmath==1.3.0
+nest-asyncio==1.6.0
+networkx==3.5
+numpy==2.2.5
+opencv-python==4.12.0.88
+packaging==24.2
+pandas==2.2.3
+parso==0.8.4
+pexpect==4.9.0
+pillow==11.3.0
+platformdirs==4.3.7
+polars==1.33.1
+prompt_toolkit==3.0.50
+psutil==7.0.0
+ptyprocess==0.7.0
+pure_eval==0.2.3
+Pygments==2.19.1
+pyparsing==3.2.3
+python-dateutil==2.9.0.post0
+pytz==2025.2
+PyYAML==6.0.2
+pyzmq==26.4.0
+requests==2.32.5
+scipy==1.16.2
+setuptools==80.9.0
+six==1.17.0
+stack-data==0.6.3
+sympy==1.14.0
+torch==2.8.0
+torchvision==0.23.0
+tornado==6.4.2
+traitlets==5.14.3
+typing_extensions==4.15.0
+tzdata==2025.2
+ultralytics==8.3.199
+ultralytics-thop==2.0.17
+urllib3==2.5.0
+wcwidth==0.2.13
+wheel @ file:///opt/homebrew/Cellar/python%403.13/3.13.1/libexec/wheel-0.45.1-py3-none-any.whl#sha256=da46333d5dcbde6e20cf7e2f8fff9e9ce76e8c94dc4afd6fb95fc4bc2745fb5e

yolov8n/yolo_mediapipe_face.py

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+import argparse
+import time
+from pathlib import Path
+
+import cv2
+import numpy as np
+import torch
+from ultralytics import YOLO
+import mediapipe as mp
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="YOLO + MediaPipe 얼굴 검출 및 랜드마크")
+    parser.add_argument(
+        "--model",
+        type=str,
+        default="face_yolov8n.pt",
+        help="YOLO face 모델 경로(.pt). 기본값: face_yolov8n.pt",
+    )
+    parser.add_argument(
+        "--device",
+        type=str,
+        default="cuda" if torch.cuda.is_available() else "cpu",
+        choices=["cpu", "cuda"],
+        help="추론 디바이스 선택",
+    )
+    parser.add_argument(
+        "--conf",
+        type=float,
+        default=0.5,
+        help="신뢰도 임계값 (0~1)",
+    )
+    parser.add_argument(
+        "--camera",
+        type=int,
+        default=0,
+        help="웹캠 인덱스 (기본 0)",
+    )
+    parser.add_argument(
+        "--show-fps",
+        action="store_true",
+        help="화면에 FPS 표기",
+    )
+    return parser.parse_args()
+
+
+class YOLOMediaPipeFaceDetector:
+    def __init__(self, yolo_model_path):
+        # YOLO 모델 로딩
+        self.yolo_model = YOLO(yolo_model_path)
+
+        # MediaPipe Face Mesh 초기화
+        self.mp_face_mesh = mp.solutions.face_mesh
+        self.face_mesh = self.mp_face_mesh.FaceMesh(
+            static_image_mode=False,
+            max_num_faces=5,
+            refine_landmarks=True,
+            min_detection_confidence=0.5,
+            min_tracking_confidence=0.5
+        )
+        self.mp_drawing = mp.solutions.drawing_utils
+        self.mp_drawing_styles = mp.solutions.drawing_styles
+
+    def detect_faces_and_landmarks(self, frame, conf_threshold=0.5):
+        # YOLO로 얼굴 바운딩 박스 검출
+        yolo_results = self.yolo_model.predict(
+            source=frame,
+            conf=conf_threshold,
+            verbose=False,
+        )
+
+        boxes = []
+        confs = []
+
+        if yolo_results and len(yolo_results) > 0:
+            r = yolo_results[0]
+            if r.boxes is not None and len(r.boxes) > 0:
+                xyxy = r.boxes.xyxy.cpu().numpy()
+                scores = r.boxes.conf.cpu().numpy()
+                boxes = xyxy.tolist()
+                confs = scores.tolist()
+
+        # MediaPipe로 얼굴 랜드마크 검출
+        rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        mp_results = self.face_mesh.process(rgb_frame)
+
+        landmarks = []
+        if mp_results.multi_face_landmarks:
+            for face_landmarks in mp_results.multi_face_landmarks:
+                landmarks.append(face_landmarks)
+
+        return boxes, confs, landmarks
+
+    def draw_results(self, frame, boxes, confs, landmarks):
+        output = frame.copy()
+        h, w = frame.shape[:2]
+
+        # YOLO 바운딩 박스 그리기
+        for (x1, y1, x2, y2), conf in zip(boxes, confs):
+            x1, y1, x2, y2 = map(int, [x1, y1, x2, y2])
+            cv2.rectangle(output, (x1, y1), (x2, y2), (0, 255, 0), 2)
+            label = f"face {conf:.2f}"
+            (tw, th), _ = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, 0.6, 2)
+            cv2.rectangle(output, (x1, max(0, y1 - th - 6)), (x1 + tw + 6, y1), (0, 255, 0), -1)
+            cv2.putText(output, label, (x1 + 3, y1 - 4), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 0), 2)
+
+        # MediaPipe 랜드마크 그리기
+        for face_landmarks in landmarks:
+            # 주요 랜드마크 인덱스 (MediaPipe Face Mesh 기준)
+            # 코끝: 1, 좌안: 33, 우안: 362, 입 중앙: 13
+            key_points = {
+                'nose_tip': 1,
+                'left_eye': 33,
+                'right_eye': 362,
+                'mouth_center': 13,
+                'left_mouth': 61,
+                'right_mouth': 291
+            }
+
+            colors = {
+                'nose_tip': (0, 0, 255),      # 빨간색
+                'left_eye': (255, 0, 0),      # 파란색
+                'right_eye': (0, 255, 0),     # 초록색
+                'mouth_center': (255, 255, 0), # 노란색
+                'left_mouth': (255, 0, 255),  # 자주색
+                'right_mouth': (0, 255, 255)  # 청록색
+            }
+
+            for name, idx in key_points.items():
+                if idx < len(face_landmarks.landmark):
+                    landmark = face_landmarks.landmark[idx]
+                    x = int(landmark.x * w)
+                    y = int(landmark.y * h)
+
+                    cv2.circle(output, (x, y), 3, colors[name], -1)
+
+                    # 코 좌표 텍스트 표시
+                    if name == 'nose_tip':
+                        cv2.putText(output, f"nose({x},{y})", (x + 5, y - 5), 
+                                  cv2.FONT_HERSHEY_SIMPLEX, 0.4, (0, 0, 255), 1)
+
+        return output
+
+
+def main():
+    args = parse_args()
+
+    model_path = Path(args.model)
+    if not model_path.exists():
+        print("[오류] YOLO 모델(.pt) 파일이 없습니다.")
+        print("- 현재 경로:", Path.cwd())
+        print("- 찾은 경로:", model_path.resolve())
+        return
+
+    print("YOLO + MediaPipe 얼굴 검출기 초기화 중...")
+    detector = YOLOMediaPipeFaceDetector(str(model_path))
+
+    print("웹캠 오픈 중... (종료: q)")
+    cap = cv2.VideoCapture(args.camera)
+    if not cap.isOpened():
+        print("[오류] 웹캠을 열 수 없습니다.")
+        return
+
+    prev_time = time.time()
+    try:
+        while True:
+            ok, frame = cap.read()
+            if not ok:
+                print("[오류] 프레임을 읽을 수 없습니다.")
+                break
+
+            # 얼굴 및 랜드마크 검출
+            boxes, confs, landmarks = detector.detect_faces_and_landmarks(frame, args.conf)
+
+            # 결과 그리기
+            drawn = detector.draw_results(frame, boxes, confs, landmarks)
+
+            # FPS 표시
+            if args.show_fps:
+                now = time.time()
+                fps = 1.0 / max(1e-6, (now - prev_time))
+                prev_time = now
+                cv2.putText(drawn, f"FPS: {fps:.1f}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
+
+            # 얼굴 수 표시
+            cv2.putText(drawn, f"faces: {len(boxes)}", (10, 65), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2)
+            cv2.putText(drawn, f"landmarks: {len(landmarks)}", (10, 100), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
+
+            cv2.imshow("YOLO + MediaPipe Face Detection", drawn)
+
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+
+    finally:
+        cap.release()
+        cv2.destroyAllWindows()
+
+
+if __name__ == "__main__":
+    main()