'TypeError: create_bool(): incompatible function arguments

I made a code detector that can detect hand, face, pose, etc. But when I run this in Visual Studio, I get the following error message:

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

Invoked with: 0.5

This is my code:

import cv2
import mediapipe as mp
import time

class findhand():
    def __init__(self, mode=False, maxHands=2, detectionCon=0.5
             ,trackCon=0.5):

        self.mode = mode
        self.maxHands = maxHands
        self.detectionCon = detectionCon
        self.trackCon = trackCon

        self.mpHands = mp.solutions.hands

        self.hands = self.mpHands.Hands(self.mode, self.maxHands
                                        ,self.detectionCon
                                        ,self.trackCon)
        self.mpDraw = mp.solutions.drawing_utils

    def findHands(self, img, draw=True):
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.hands.process(imgRGB)
        if self.results.multi_hand_landmarks:
            for handLms in self.results.multi_hand_landmarks:
                if draw:
                    self.mpDraw.draw_landmarks(img, handLms,
                                               self.mpHands.HAND_CONNECTIONS)

        return img

class findFace():
    def __init__(self, mode=False, maxFaces=1, detectionCon=0.5
               ,trackCon=0.5):
        self.mode = mode
        self.maxFaces = maxFaces
        self.detectionCon = detectionCon
        self.trackCon = trackCon
        self.mpFaceMesh = mp.solutions.face_mesh

        self.face_mesh = self.mpFaceMesh.FaceMesh(self.mode
                                                 ,self.maxFaces
                                                 ,self.detectionCon
                                                 ,self.trackCon)

        self.mpDraw = mp.solutions.drawing_utils

   def findFace(self, img, draw=True):

        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.face_mesh.process(imgRGB)

        if self.results.multi_face_landmarks:
            for faceLms in self.results.multi_face_landmarks:
                if draw:
                    self.mpDraw.draw_landmarks(img, faceLms,
                                               self.mpFaceMesh.FACE_CONNECTIONS)

        return img

class findPose():
    def __init__(self, mode=False, complexity=1,detectionCon=0.5,landmarks=True
                 ,trackCon=0.5):
        self.mode = mode
        self.maxFace = 1
        self.detectionCon = 0.5
        self.trackCon = 0.5
        self.landmarks = landmarks
        self.complexity = complexity
        self.mpPose = mp.solutions.pose

        self.pose = self.mpPose.Pose(self.mode, self.complexity
                                         ,self.detectionCon
                                         ,self.trackCon
                                         ,self.landmarks)
        self.mpDraw = mp.solutions.drawing_utils

    def findPose(self, img, draw=True):
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
        self.results = self.pose.process(imgRGB)

        if self.result.pose_landmarks:
            PoseLms = self.results.pose_landmarks
            mpDraw.draw_landmarks(img, PoseLms, self.mpPose.POSE_CONNECTIONS,
                                  drawSpec, drawSpec)

        return img

def main():

    cTime, pTime = 0, 0

    hand_detector = findhand()
    face_detector = findFace()
    pose_detector = findPose()

    cap = cv2.VideoCapture(1, cv2.CAP_DSHOW)

    while True:

        success, img = cap.read()
        img = face_detector.findFace(img)
        if not success:
            print("GPU Didn't Success At Loading Video")
            continue

        handlmList = hand_detector.findHands(img)

        cTime = time.time()
        fps = 1 / (cTime - pTime)
        pTime = cTime

        cv2.putText(img, str(int(fps)), (10, 70),
                    cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255), 3)
        cv2.imshow("Detector", img)

        if cv2.waitKey(1) != -1:
            cv2.destroyAllWindows()
            break


if __name__ == "__main__":
    main()

The full error message is:

Traceback (most recent call last):
  File "c:\Users\tmdgh\Desktop\DetectionModule2.py", line 135, in <module>
    main()
  File "c:\Users\tmdgh\Desktop\DetectionModule2.py", line 107, in main
    pose_detector = findPose()
  File "c:\Users\tmdgh\Desktop\DetectionModule2.py", line 76, in __init__
    self.pose = self.mpPose.Pose(self.mode 
  File "C:\Users\tmdgh\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\mediapipe\python\solutions\pose.py", line 146, in __init__
    super().__init__(
  File "C:\Users\tmdgh\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\mediapipe\python\solution_base.py", line 258, in __init__
    self._input_side_packets = {
  File "C:\Users\tmdgh\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\mediapipe\python\solution_base.py", line 259, in <dictcomp>
    name: self._make_packet(self._side_input_type_info[name], data)
  File "C:\Users\tmdgh\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\LocalCache\local-packages\Python39\site-packages\mediapipe\python\solution_base.py", line 513, in _make_packet
    return getattr(packet_creator, 'create_' + packet_data_type.value)(data)
TypeError: create_bool(): incompatible function arguments. The following argument types are supported:
    1. (arg0: bool) -> mediapipe.python._framework_bindings.packet.Packet

Invoked with: 0.5

python mediapipe

Solution 1:^[1]

Replace this line:

self.hands = self.mpHands.Hands(self.mode, self.maxHands ,self.detectionCon ,self.trackCon)

With this one:

self.hands = self.mpHands.Hands(self.mode, self.maxHands, self.modelComplex, self.detectionCon, self.trackCon)

Also add parameter of modelComplex in __init__ method, you are getting this error because you are missing one parameter that is model complexity.

Solution 2:^[2]

try this

def __init__(self, mode=False, maxHands=2, detectionCon=False, trackCon=0.5):

Solution 3:^[3]

I solved the problem by passing the keyword arguments instead of positional arguments. This ensured right argument is being passed at right place.

self.mpHands.Hands(
                   static_image_mode=True/False,
                   model_complexity=yourNumber,
                   smooth_landmarks=True/False,
                   enable_segmentation=True/False,
                   smooth_segmentation=True/False,
                   min_detection_confidence=yourConfidence,
                   min_tracking_confidence=yourConfidence):

Solution 4:^[4]

If you look at the Pose(SolutionBase) class of MediaPipe, you can see def __init__:

class Pose(SolutionBase):
    def __init__(self,
                 static_image_mode=False,
                 model_complexity=1,
                 smooth_landmarks=True,
                 enable_segmentation=False,
                 smooth_segmentation=True,
                 min_detection_confidence=0.5,
                 min_tracking_confidence=0.5):

You should have the same parameters in the class findPose() __init__. Of course you can name them whatever you want, but the sequence and types must be the same.

More information: https://google.github.io/mediapipe/solutions/pose#model_complexity

https://www.youtube.com/watch?v=01sAkU_NvOY watch from 1:11

Solution 5:^[5]

This seems to be related to the version of mediapipe or opencv you are using. Please look out to the appropriate combinaison of version and you should be good

Sources

This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.

Source: Stack Overflow

Solution	Source
Solution 1	Tomerikoo
Solution 2	Suraj Rao
Solution 3	Ahmad Anis
Solution 4	ddejohn
Solution 5	Manifest Man

'TypeError: create_bool(): incompatible function arguments

Solution 1:[1]

Solution 2:[2]

Solution 3:[3]

Solution 4:[4]

Solution 5:[5]