创建FaceMeshDetector类时遇TypeError：create_bool()参数类型不兼容

问题现象 #

直接运行MediaPipe FaceMesh逻辑正常，但封装为FaceMeshDetector类后触发类型错误：

TypeError: create_bool(): incompatible function arguments. The following argument types are supported: 1. (arg0: bool) -> mediapipe.python._framework_bindings.packet.Packet，实际传入了0.5

错误回溯指向FaceMesh初始化步骤。

问题原因 #

你在初始化FaceMesh时参数顺序不匹配官方定义：
MediaPipe FaceMesh的构造函数参数顺序为：
static_image_mode=False, max_num_faces=1, refine_landmarks=False, min_detection_confidence=0.5, min_tracking_confidence=0.5

而你的类__init__参数顺序是static_mode, maxFaces, minDetectionCon, minTrackCon，直接按位置传递时，第三个参数minDetectionCon（值为0.5）被传给了官方定义的第三个参数refine_landmarks——这个参数要求是布尔值，因此触发类型错误。

修复方案 #

方案1：使用关键字参数传递（推荐，彻底避免顺序问题） #

修改类__init__中FaceMesh的初始化代码，明确指定每个参数的名称：

self.faceMesh = self.mpFaceMesh.FaceMesh(
    static_image_mode=self.static_mode,
    max_num_faces=self.maxFaces,
    min_detection_confidence=self.minDetectionCon,
    min_tracking_confidence=self.minTrackCon
)

方案2：调整类的参数顺序与官方一致 #

如果偏好位置参数，可调整类的__init__参数顺序，补充官方的refine_landmarks参数（默认False）：

def __init__(self, static_mode=False, maxFaces=2, refine_landmarks=False, minDetectionCon=0.5, minTrackCon=0.5):
    self.static_mode = static_mode
    self.maxFaces = maxFaces
    self.refine_landmarks = refine_landmarks
    self.minDetectionCon = minDetectionCon
    self.minTrackCon = minTrackCon

    self.mpDraw = mp.solutions.drawing_utils
    self.mpFaceMesh = mp.solutions.face_mesh
    self.faceMesh = self.mpFaceMesh.FaceMesh(self.static_mode, self.maxFaces, self.refine_landmarks,
                                             self.minDetectionCon, self.minTrackCon)
    self.drawSpec = self.mpDraw.DrawingSpec(thickness=1, circle_radius=1)

完整修复后的代码 #

import cv2
import mediapipe as mp
import time

class FaceMeshDetector:

    def __init__(self, static_mode=False, maxFaces=2, minDetectionCon=0.5, minTrackCon=0.5):
        self.static_mode = static_mode
        self.maxFaces = maxFaces
        self.minDetectionCon = minDetectionCon
        self.minTrackCon = minTrackCon

        self.mpDraw = mp.solutions.drawing_utils
        self.mpFaceMesh = mp.solutions.face_mesh
        # 使用关键字参数初始化FaceMesh
        self.faceMesh = self.mpFaceMesh.FaceMesh(
            static_image_mode=self.static_mode,
            max_num_faces=self.maxFaces,
            min_detection_confidence=self.minDetectionCon,
            min_tracking_confidence=self.minTrackCon
        )
        self.drawSpec = self.mpDraw.DrawingSpec(thickness=1, circle_radius=1)

    def findFaceMesh(self, img, draw=True):
        self.imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.faceMesh.process(self.imgRGB)
        faces = []
        if self.results.multi_face_landmarks:
            for faceLms in self.results.multi_face_landmarks:
                if draw:
                    self.mpDraw.draw_landmarks(img, faceLms, self.mpFaceMesh.FACEMESH_CONTOURS, self.drawSpec,
                                               self.drawSpec)

                face = []
                for id, lm in enumerate(faceLms.landmark):
                    ih, iw, ic = img.shape
                    x, y = int(lm.x * iw), int(lm.y * ih)
                    face.append([x, y])
                faces.append(face)
        return img, faces


def main():
    cap = cv2.VideoCapture(0)
    pTime = 0
    detector = FaceMeshDetector()
    while True:
        success, img = cap.read()
        img, faces = detector.findFaceMesh(img)
        if len(faces) != 0:
            print(faces[0])
        cTime = time.time()
        fps = 1 / (cTime - pTime)
        pTime = cTime
        cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN, 3, (0, 255, 0), 3)
        cv2.imshow("Image", img)
        cv2.waitKey(1)


if __name__ == '__main__':
    main()

内容的提问来源于stack exchange，提问作者Roma