TypeError: create_bool(): incompatible function arguments

Question

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

score 3 · Answer 1 · edited Jul 01 '22 at 08:39

3

I solved the problem by passing the named (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):

See also: Why You Should Typically Use Named Arguments in Python | Thomas Stringer

edited Jul 01 '22 at 08:39

hc_dev

8,389
1
26
38

answered Apr 28 '22 at 10:02

Ahmad Anis

2,322
4
25
54

Confirmed. Work for me too also in pose detection – Willy satrio nugroho May 08 '22 at 10:04
Advantage of _named arguments_ among expressiveness is also robustness in case of changed parameter-order by a new version. – hc_dev Jul 01 '22 at 08:41

score 2 · Answer 2 · edited Nov 06 '21 at 17:45

2

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.

edited Nov 06 '21 at 17:45

Tomerikoo

18,379
16
47
61

answered Nov 06 '21 at 17:21

Hamza Chaudhary

71
6

score 1 · Answer 3 · edited Nov 09 '21 at 11:18

1

try this

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

edited Nov 09 '21 at 11:18

Suraj Rao

29,388
11
94
103

answered Nov 09 '21 at 11:17

howdd

11
1

score 1 · Answer 4 · answered Oct 25 '22 at 07:15

just use this one

self.hands = self.mpHands.Hands(self.mode, self.maxHands
                                        ,min_detection_confidence = 0.5
                                        ,min_tracking_confidence = 0.5
                                )

self.face_mesh = self.mpFaceMesh.FaceMesh(self.mode,self.maxFaces
                                                 ,min_detection_confidence = 0.5
                                                 ,min_tracking_confidence = 0.5
                                          )

self.pose = self.mpPose.Pose(self.mode, self.complexity
                                       ,min_detection_confidence = 0.5
                                        ,min_tracking_confidence = 0.5
                                         ,self.landmarks
                             )

Your answer could be improved with additional supporting information. Please [edit] to add further details, such as citations or documentation, so that others can confirm that your answer is correct. You can find more information on how to write good answers [in the help center](/help/how-to-answer). — Community, Oct 28 '22 at 09:39

score 0 · Answer 5 · edited Sep 18 '21 at 22:55

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

score -1 · Answer 6 · answered Nov 06 '21 at 14:38

-1

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

answered Nov 06 '21 at 14:38

Manifest Man

873
10
16

TypeError: create_bool(): incompatible function arguments

6 Answers6