import cv2
import mediapipe as mp

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

drawing_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
cap = cv2.VideoCapture(0)
with mp_face_mesh.FaceMesh(
        max_num_faces=1,
        refine_landmarks=True,
        min_detection_confidence=0.5,
        min_tracking_confidence=0.5) as face_mesh:
    while cap.isOpened():
        success, image = cap.read()
        if not success:
            print("Ignoring empty camera frame.")
            continue
        # Initialize the face mesh model
        face_mesh = mp_face_mesh.FaceMesh(static_image_mode=False, max_num_faces=1, min_detection_confidence=0.5)

        # Load the input image
        # lecture de la vidéo
        ret, frame = cap.read()
        # conversion de l'image en RGB    
        image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        # Process the image and extract the landmarks
        results = face_mesh.process(image)
        if results.multi_face_landmarks:
            landmarks = results.multi_face_landmarks[0]

            # Define the landmark indices for the corners of the eyes and the tip of the nose
            left_eye = [33, 133, 246, 161, 160, 159, 158, 157, 173, 133]
            right_eye = [362, 263, 373, 380, 381, 382, 384, 385, 386, 362]
            nose_tip = 4

            # Calculate the distance between the eyes and the nose tip
            left_eye_x = landmarks.landmark[left_eye[0]].x * image.shape[1]
            right_eye_x = landmarks.landmark[right_eye[0]].x * image.shape[1]
            nose_x = landmarks.landmark[nose_tip].x * image.shape[1]
            eye_distance = abs(left_eye_x - right_eye_x)
            nose_distance = abs(nose_x - (left_eye_x + right_eye_x) / 2)

            # Determine the gender based on the eye and nose distances
            if eye_distance > 1.5 * nose_distance:
                gender = "Female"
            else:
                gender = "Male"

            # Draw the landmarks on the image
            cv2.putText(image, gender, (10, 50),cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
        # affichage de la vidéo
        cv2.imshow('Video', cv2.cvtColor(image, cv2.COLOR_RGB2BGR))
        if cv2.waitKey(10) & 0xFF == ord('q'):
            break

# libération de la caméra et des ressources
cap.release()
cv2.destroyAllWindows()