人脸识别代码执行遇TypeError：imgModeList[3]赋值报错求助

问题描述 #

开发人脸识别项目时，执行到imgBackground[44:44 + 633, 808:808 + 414] = imgModeList[3]代码行时抛出错误，错误信息：

TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'

已确认切片逻辑正确，注释该行后仍存在问题，附上代码片段及报错栈。

代码片段 #

while True:
    success, img = cap.read()
    img_small = cv2.resize(img, (0, 0), None, 0.25, 0.25)
    img_small = cv2.cvtColor(img_small, cv2.COLOR_BGR2RGB)

    faceCurFrame = face_recognition.face_locations(img_small)
    encodeCurFrame = face_recognition.face_encodings(img_small, faceCurFrame)

    for encodeFace, faceLoc in zip(encodeCurFrame, faceCurFrame):
        matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
        faceDist = face_recognition.face_distance(encodeListKnown, encodeFace)
        print("matches", matches)
        print("faceDis", faceDist)

        matchIndex = np.argmin(faceDist)
        print("Match Index", matchIndex)

        if matches[matchIndex]:
            print("Known face was detected")
            print(studentsId[matchIndex])

    imgBackground[162:162 + 480, 55:55 + 640] = img
    imgBackground[44:44 + 633, 808:808 + 414] = imgModeList[3]
    # cv2.imshow("Webcam", img)
    cv2.imshow("Face Attendance", imgBackground)
    cv2.waitKey(1)

报错栈 #

Traceback (most recent call last):
  File "C:\Users\Tony Alosius\PycharmProjects\pythonProject1\main.py", line 52, in <module>
    imgBackground[44:44 + 633, 808:808 + 414] = imgModeList[3]
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
[ WARN:0] global D:\a\opencv-python\opencv-python\opencv\modules\videoio\src\cap_msmf.cpp (438) `anonymous-namespace'::SourceReaderCB::~SourceReaderCB terminating async callback

原因分析与解决方案 #

核心原因 #

1. imgModeList[3]为None：大概率是图像加载失败（比如路径错误、文件损坏），导致列表对应位置未获取到有效图像数组。
2. 摄像头读取失败：cap.read()返回success=False时，img为None，后续赋值给imgBackground切片也会触发同类错误，这也是注释目标行后仍报错的原因。
3. imgBackground未正确初始化：如果imgBackground本身是None，任何切片赋值操作都会失败。

具体修复步骤 #

1. 校验imgModeList的图像加载
   确保每个图像都成功加载，避免列表中出现None：

   imgModeList = []
   # 假设modePaths是图像路径列表
   for path in modePaths:
       img = cv2.imread(path)
       if img is not None:
           imgModeList.append(img)
       else:
           print(f"加载失败：{path}")
   # 检查索引3是否有效
   if len(imgModeList) <= 3 or imgModeList[3] is None:
       print("错误：imgModeList[3]未有效加载")
       # 可选择退出或使用默认图像
   

2. 增加摄像头读取有效性判断
   在使用img前先确认摄像头读取成功：

   while True:
       success, img = cap.read()
       if not success:
           print("摄像头读取失败，退出循环")
           break
       # 后续图像处理代码...
   

3. 确认imgBackground初始化正确
   确保imgBackground是预先创建的有效numpy数组，比如：

   # 示例：创建一个指定尺寸的黑色背景图
   imgBackground = np.zeros((720, 1280, 3), dtype=np.uint8)
   # 或读取背景图像
   imgBackground = cv2.imread("background_path.jpg")
   if imgBackground is None:
       print("背景图加载失败")
       exit()
   

内容的提问来源于stack exchange，提问作者Tony Alosius