python - TypeError: 'NoneType'对象无法下标opencv-python/python face_recognition

Question

我有face_recognition python脚本，如果执行可以正常运行，但是如果执行则随机显示错误:

  Traceback (most recent call last):
    File "faces_test.py", line 38, in <module>
      rgb_frame = frame[:, :, ::-1]
  TypeError: 'NoneType' object is not subscriptable

该错误表明有时运行有时会出现该错误。我不知道会发生什么，但是我之前将api.py的face_recognition容忍度从0.6更改为0.4。我不确定chage会对opencv造成随机错误

我想运行我的脚本，并且不会得到这样的随机错误，任何解决方案？

环境版本:

python = 3.8.2

opencv-contrib-python 4.2.0.32

opencv-python 4.2.0.32

人脸识别1.3.0

人脸识别模型0.3.0

我的python脚本:

import face_recognition
import cv2
import numpy as np

# This is a super simple (but slow) example of running face recognition on live video from your webcam.
# There's a second example that's a little more complicated but runs faster.

# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
# specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.

# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(0 + cv2.CAP_DSHOW)

# Load a sample picture and learn how to recognize it.
obama_image = face_recognition.load_image_file("./training/obama.jpg")
obama_face_encoding = face_recognition.face_encodings(obama_image)[0]

# Load a second sample picture and learn how to recognize it.
biden_image = face_recognition.load_image_file("./training/biden.jpg")
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]

# Create arrays of known face encodings and their names
known_face_encodings = [
    obama_face_encoding,
    biden_face_encoding
]
known_face_names = [
    "obama",
    "biden"
]

while True:
    # Grab a single frame of video
    ret, frame = video_capture.read()

    # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
    rgb_frame = frame[:, :, ::-1]

    # Find all the faces and face enqcodings in the frame of video
    face_locations = face_recognition.face_locations(rgb_frame)
    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

    # Loop through each face in this frame of video
    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
        # See if the face is a match for the known face(s)
        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)

        name = "Unknown"

        # If a match was found in known_face_encodings, just use the first one.
        # if True in matches:
        #     first_match_index = matches.index(True)
        #     name = known_face_names[first_match_index]

        # Or instead, use the known face with the smallest distance to the new face
        face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
        best_match_index = np.argmin(face_distances)
        #print(face_distances)
        #print(best_match_index)
        if matches[best_match_index]:
            name = known_face_names[best_match_index]
            print(name)

        # Draw a box around the face
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

        # Draw a label with a name below the face
        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    # Display the resulting image
    cv2.imshow('Video', frame)

    # Hit 'q' on the keyboard to quit!
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()

Answer 1

很抱歉收到您的回复，但是如果您仍在使用OpenCV进行编码，那么可能会有所帮助。
第一评论
您可能没有通过网络摄像头源获得任何视频。
例如，看这段代码

# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(0 + cv2.CAP_DSHOW)

有时，摄像机将在插槽“1”而不是“0”中进行初始化。重要的是要考虑到这些初始化可能会反弹。如果要确保可以正确识别摄像机，则可以始终在变量中显式定义摄像机位置，还可以进行一些错误处理。
问题一的示例:

def setup_camera():
    """
    Initialize camera by calling cv2.VideoCapture
    Produces a variable that you can read from using self.capture.read
    If camera doesn't connect prints error and Camera not conntected
    """

    device = '/dev/v4l/by-id/usb-HD_Camera_Manufacturer_USB_2.0_Camera-video-index0'

    try:
        capture = cv2.VideoCapture(device)
        print("Camera Connection Successful")
        self.capture.release()
    except IOError as e:
        print(e)
        print("Camera Not Connected")

这至少可以帮助您入门，并且会告诉您是否未在录制摄像头。
如果您希望能够在系统上轻松找到相机(并且您正在使用linux-我是一个Ubuntu专家，如果您使用的是Windows，抱歉。)，您可以运行v4l-utils这样的简单程序包来查找相机。类似于以下代码:

sudo apt-get install v4l-utils
v4l2-ctl --list-devices

应该给您以下答复:

USB 2.0 Camera: HD USB Camera (usb-0000:00:1a.0-1.5):
    /dev/video0

然后，您可以使用udevadm运行命令以获取有关 / dev / video0 的更多信息:

udevadm info --query=all --name=/dev/video0

这将返回如下内容:

P: /devices/pci0000:00/0000:00:1a.0/usb1/1-1/1-1.5/1-1.5:1.0/video4linux/video0
N: video0
S: v4l/by-id/usb-HD_Camera_Manufacturer_USB_2.0_Camera-video-index0
S: v4l/by-path/pci-0000:00:1a.0-usb-0:1.5:1.0-video-index0
E: COLORD_DEVICE=1
E: COLORD_KIND=camera
E: DEVLINKS=/dev/v4l/by-path/pci-0000:00:1a.0-usb-0:1.5:1.0-video-index0 /dev/v4l/by-id/usb-HD_Camera_Manufacturer_USB_2.0_Camera-video-index0
E: DEVNAME=/dev/video0
E: DEVPATH=/devices/pci0000:00/0000:00:1a.0/usb1/1-1/1-1.5/1-1.5:1.0/video4linux/video0
E: ID_BUS=usb
E: ID_FOR_SEAT=video4linux-pci-0000_00_1a_0-usb-0_1_5_1_0
E: ID_MODEL=USB_2.0_Camera
E: ID_MODEL_ENC=USB\x202.0\x20Camera
E: ID_MODEL_ID=9230
E: ID_PATH=pci-0000:00:1a.0-usb-0:1.5:1.0
E: ID_PATH_TAG=pci-0000_00_1a_0-usb-0_1_5_1_0
E: ID_REVISION=0100
E: ID_SERIAL=HD_Camera_Manufacturer_USB_2.0_Camera
E: ID_TYPE=video
E: ID_USB_DRIVER=uvcvideo
E: ID_USB_INTERFACES=:0e0100:0e0200:
E: ID_USB_INTERFACE_NUM=00
E: ID_V4L_CAPABILITIES=:capture:
E: ID_V4L_PRODUCT=USB 2.0 Camera: HD USB Camera
E: ID_V4L_VERSION=2
E: ID_VENDOR=HD_Camera_Manufacturer
E: ID_VENDOR_ENC=HD\x20Camera\x20Manufacturer
E: ID_VENDOR_ID=05a3
E: MAJOR=81
E: MINOR=0
E: SUBSYSTEM=video4linux
E: TAGS=:uaccess:seat:
E: USEC_INITIALIZED=23692957

如您所见， DEVLINKS 中的第二个值提供了可用于调用相机的硬件位置。
第二条评论
OpenCV具有内置函数，可以对帧进行转换。您的方法和我将使用的示例都在this post中。为了更深入地研究事物，让我们尝试一下。
例如 -
您使用的代码方法很好:

# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)

rgb_frame = frame[:, :, ::-1]

如果问题二不起作用，请尝试使用此示例:

rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

结论
我希望这一答复能有所帮助。我不认为这是转换问题，但很可能是相机初始化问题。尝试获取更准确的相机进纸位置，这将为您提供更强大的相机调用方法。祝你今天愉快!