虚拟鼠标开发遇ValueError解包错误，寻求调试帮助

报错信息 #

INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
Traceback (most recent call last):
  File "C:\AIproject\virMouse.py", line 18, in <module>
    lmList, bbox = detector.findPosition(img)
ValueError: not enough values to unpack (expected 2, got 0)

Process finished with exit code 1

主程序代码（virMouse.py） #

import cv2
import numpy as np
import time
import HTmodule as htm
import autopy

wCam, hCam = 640, 480

cap = cv2.VideoCapture(0)
cap.set(3, wCam)
cap.set(4, hCam)
pTime = 0
detector = htm.handDetector(maxHands=1)

while True:
     success, img = cap.read()
     img = detector.findHands(img)
     lmList, bbox = detector.findPosition(img)


     cTime = time.time()
     fps = 1 / (cTime - pTime)
     pTime = cTime
     cv2.putText(img, f'FPS:{(int(fps))}', (5, 30), cv2.FONT_HERSHEY_DUPLEX, 1, (204, 0, 0), 2)
     cv2.imshow("Image", img)
     cv2.waitKey(1)

手部追踪模块代码（HTmodule.py） #

import cv2
import mediapipe as mp
import time

class handDetector():
    def __init__(self, mode=False, maxHands=2,modelC=1, detectionCon=0.5, trackCon=0.5):
        self.mode = mode
        self.maxHands = maxHands
        self.modelC = modelC
        self.detectionCon = detectionCon
        self.trackCon = trackCon

        self.mpHands = mp.solutions.hands
        self.hands = self.mpHands.Hands(self.mode, self.maxHands, self.modelC, 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)
        # print(result.multi_hand_landmarks)

        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
    def findPosition(self, img, handNo=0, draw=True):
        lmList=[]
        if self.results.multi_hand_landmarks:
            myHand = self.results.multi_hand_landmarks[handNo]
            for id, lm in enumerate(myHand.landmark):
                # print(id,lm)
                h, w, c = img.shape
                cx, cy = int(lm.x * w), int(lm.y * h)
                # print(id, cx, cy)
                lmList.append([id, cx, cy])
                # if id == 0:
                if draw:
                    cv2.circle(img, (cx, cy), 3, (229, 25, 66), cv2.FILLED)
        return lmList


def main():
    pTime = 0
    cTime = 0
    cap = cv2.VideoCapture(0)
    detector = handDetector()
    while True:
        success, img = cap.read()
        img = detector.findHands(img)
        lmList = detector.findPosition(img, draw=False)
        # print(lmList) # PRINTS THE LIST OF LANDMARKS
        if len(lmList) != 0:
            print(lmList[4])
        cTime = time.time()
        fps = 1 / (cTime - pTime)
        pTime = cTime

        cv2.putText(img, f'FPS:{(int(fps))}', (5, 30), cv2.FONT_HERSHEY_DUPLEX, 1, (9, 9, 255), 1)

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


if __name__ == "__main__":
    main()

问题分析与解决方法 #

核心问题 #

报错的直接原因是主程序错误地期望findPosition返回两个值（lmList和bbox），但该函数实际只返回lmList一个值。当没有检测到手时，lmList是空列表，尝试将空列表解包为两个变量就会触发ValueError: not enough values to unpack (expected 2, got 0)。

解决步骤 #

1. 修正主程序的赋值语句
   如果不需要bounding box，直接将主程序中的：

   lmList, bbox = detector.findPosition(img)
   

   修改为：

   lmList = detector.findPosition(img)
   

   若确实需要手部的bounding box，可以修改HTmodule中的findPosition函数，让它同时返回lmList和bbox，示例修改如下：

   def findPosition(self, img, handNo=0, draw=True):
       lmList=[]
       bbox = []
       if self.results.multi_hand_landmarks:
           myHand = self.results.multi_hand_landmarks[handNo]
           # 计算bounding box
           x_list = []
           y_list = []
           for id, lm in enumerate(myHand.landmark):
               h, w, c = img.shape
               cx, cy = int(lm.x * w), int(lm.y * h)
               x_list.append(cx)
               y_list.append(cy)
               lmList.append([id, cx, cy])
               if draw:
                   cv2.circle(img, (cx, cy), 3, (229, 25, 66), cv2.FILLED)
           bbox = [min(x_list), min(y_list), max(x_list)-min(x_list), max(y_list)-min(y_list)]
           # 可选：绘制bbox
           if draw:
               cv2.rectangle(img, (bbox[0]-20, bbox[1]-20), 
                            (bbox[0]+bbox[2]+20, bbox[1]+bbox[3]+20), 
                            (0,255,0), 2)
       return lmList, bbox
   

   此时主程序的lmList, bbox = detector.findPosition(img)就能正常运行。

2. 增加手部检测判断
   在使用lmList之前，先判断是否有检测到手，避免后续操作出错，比如在主程序中添加：

   lmList = detector.findPosition(img)
   if len(lmList) > 0:
       # 这里写后续的鼠标控制逻辑，比如获取指尖坐标等
       print("检测到手部关键点")
   

内容的提问来源于stack exchange，提问作者UserS1912