Clocksp/face-emotion-recognition

1import cv22import mediapipe as mp3 4from mediapipe.tasks.python import vision5from mediapipe.tasks.python import BaseOptions6from mediapipe.tasks.python.vision import RunningMode7 8def get_detector():9    options = vision.FaceLandmarkerOptions(10        base_options=BaseOptions(model_asset_path="face_landmarker.task"),11        running_mode=RunningMode.IMAGE,12        num_faces=113    )14    return vision.FaceLandmarker.create_from_options(options)15 16 17def get_face_landmarks(image, draw=False):18    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)19    mp_image = mp.Image(20        image_format=mp.ImageFormat.SRGB,21        data=image_rgb22    )23 24    detector = get_detector()25    result = detector.detect(mp_image)26 27 28    if not result.face_landmarks:29        return None30 31    face_landmarks = result.face_landmarks[0] 32 33    xs_, ys_, zs_ = [], [], []34 35    for lm in face_landmarks[:468]:36        xs_.append(lm.x)37        ys_.append(lm.y)38        zs_.append(lm.z)39 40    min_x, min_y, min_z = min(xs_), min(ys_), min(zs_)41 42    image_landmarks = []43    for i in range(len(xs_)):44        image_landmarks.append(xs_[i] - min_x)45        image_landmarks.append(ys_[i] - min_y)46        image_landmarks.append(zs_[i] - min_z)47 48    if draw:49        h, w, _ = image.shape50        for lm in face_landmarks:51            x = int(lm.x * w)52            y = int(lm.y * h)53            cv2.circle(image, (x, y), 1, (0, 255, 0), -1)54 55    return image_landmarks