TypeError: create_int(): 不兼容的函数参数

Question

我最近一直在用python学习计算机视觉，在做手部检测项目的时候遇到了这个错误：-

Traceback (most recent call last):
File "c:\Users\idhant\OneDrive - 007lakshya\Idhant\Programming\Projects\MY MACHINE 
LEARNING PROJECTS\Hand Tracking Module.py", line 64, in <module>
main()
File "c:\Users\idhant\OneDrive - 007lakshya\Idhant\Programming\Projects\MY MACHINE 
LEARNING PROJECTS\Hand Tracking Module.py", line 41, in main
detector = handDetector()
File "c:\Users\idhant\OneDrive - 007lakshya\Idhant\Programming\Projects\MY MACHINE 
LEARNING PROJECTS\Hand Tracking Module.py", line 13, in __init__
self.hands = self.mpHands.Hands(self.mode, self.maxHands, self.detectionCon, 
self.trackCon)
File "C:\Users\idhant\AppData\Roaming\Python\Python39\site- 
packages\mediapipe\python\solutions\hands.py", line 114, in __init__
super().__init__(
File "C:\Users\idhant\AppData\Roaming\Python\Python39\site- 
packages\mediapipe\python\solution_base.py", line 258, in __init__
self._input_side_packets = {
File "C:\Users\idhant\AppData\Roaming\Python\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\idhant\AppData\Roaming\Python\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_int(): incompatible function arguments. The following argument types 
are supported:
1. (arg0: int) -> mediapipe.python._framework_bindings.packet.Packet

Invoked with: 0.5
[ WARN:0] global D:\a\opencv-python\opencv- 
python\opencv\modules\videoio\src\cap_msmf.cpp (438) `anonymous- 
 namespace'::SourceReaderCB::~SourceReaderCB terminating async callback

我尝试了很多调试它，但没有成功:(，所以请帮助我，这是我编写的代码：-

import cv2
import mediapipe as mp
import time

class handDetector():
    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)
    results = self.hands.process(imgRGB)
    # print(results.multi_hand_landmarks)

    if results.multi_hand_landmarks:
        for handLms in results.multi_hand_landmarks:
            if draw:
                self.mpDraw.draw_landmarks(img, handLms, self.mpHands.HAND_CONNECTIONS)
    return img

            # for id, lm in enumerate(handLms.landmark):
            #     # print(id, lm)
            #     h, w, c = img.shape
            #     cx, cy = int(lm.x*w), int(lm.y*h)
            #     print(id, cx, cy)
            #     # if id == 4:
            #     cv2.circle(img, (cx, cy), 15, (255,0,255), cv2.FILLED)



def main():
    pTime = 0
    cTime = 0
    cap = cv2.VideoCapture(0)
    detector = handDetector()

while True:
    success, img = cap.read()
    img = detector.findHands(img)
    
    cTime = time.time()
    fps = 1/(cTime-pTime)
    pTime = cTime

    cv2.putText(img, str(int(fps)),(10, 70), cv2.FONT_HERSHEY_COMPLEX, 3, (255,0,255),3)

    cv2.imshow("Image", img)
    cv2.waitKey(1)








if __name__ == "__main__":
    main()

我已经尝试过制作一个手部检测器类，它可以做同样的事情来检测手，但我们也可以在我们的其他文件中使用它，这就是我编写这段代码的原因，并遇到了这个问题！

Answer 1

在def __init__()，处代码：

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

尝试为Hands() 中的第三个参数添加模型复杂度，如下所示：

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

所以self.mpHands.Hands()中一共有五个参数

这是我的完整代码：

class handDetector():
    def __init__(self, mode=False, maxHands=1, modelComplexity=1, detectionCon=0.5, trackCon=0.5):
        self.mode = mode
        self.maxHands = maxHands
        self.modelComplex = modelComplexity
        self.detectionCon = detectionCon
        self.trackCon = trackCon

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

Answer 2

您需要在handDetector() 类的__init__ 方法中再分配一个参数。

您的完整代码可能如下所示：

import cv2
import mediapipe as mp
import time

# class creation
class handDetector():
    def __init__(self, mode=False, maxHands=2, detectionCon=0.5,modelComplexity=1,trackCon=0.5):
        self.mode = mode
        self.maxHands = maxHands
        self.detectionCon = detectionCon
        self.modelComplex = modelComplexity
        self.trackCon = trackCon
        self.mpHands = mp.solutions.hands
        self.hands = self.mpHands.Hands(self.mode, self.maxHands,self.modelComplex,
                                        self.detectionCon, self.trackCon)
        self.mpDraw = mp.solutions.drawing_utils # it gives small dots onhands total 20 landmark points

    def findHands(self,img,draw=True):
        # Send rgb image to hands
        imgRGB = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
        self.results = self.hands.process(imgRGB) # process the frame
    #     print(results.multi_hand_landmarks)

        if self.results.multi_hand_landmarks:
            for handLms in self.results.multi_hand_landmarks:

                if draw:
                    #Draw dots and connect them
                    self.mpDraw.draw_landmarks(img,handLms,
                                                self.mpHands.HAND_CONNECTIONS)

           return img

    def findPosition(self,img, handNo=0, draw=True):
        """Lists the position/type of landmarks
        we give in the list and in the list ww have stored
        type and position of the landmarks.
        List has all the lm position"""

        lmlist = []

        # check wether any landmark was detected
        if self.results.multi_hand_landmarks:
            #Which hand are we talking about
            myHand = self.results.multi_hand_landmarks[handNo]
            # Get id number and landmark information
            for id, lm in enumerate(myHand.landmark):
                # id will give id of landmark in exact index number
                # height width and channel
                h,w,c = img.shape
                #find the position
                cx,cy = int(lm.x*w), int(lm.y*h) #center
                # print(id,cx,cy)
                lmlist.append([id,cx,cy])

                # Draw circle for 0th landmark
                if draw:
                    cv2.circle(img,(cx,cy), 15 , (255,0,255), cv2.FILLED)

        return lmlist

def main():
    #Frame rates
    pTime = 0
    cTime = 0
    cap = cv2.VideoCapture(0)
    detector = handDetector()

    while True:
        success,img = cap.read()
        img = detector.findHands(img)
        lmList = detector.findPosition(img)
        if len(lmList) != 0:
            print(lmList[4])

        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("Video",img)
        if cv2.waitKey(1) == ord('q'):
            break

    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    main()

Answer 3

我不知道它现在是否有帮助，或者可能供将来参考。 这是最后一个版本的 mediapipe 的已知问题。 恢复到 0.8.8 版本即可解决问题。