Ошибка типа: объект 'NoneType' не является подписным opencv- python / python face_recognition - PullRequest
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Ошибка типа: объект 'NoneType' не является подписным opencv- python / python face_recognition

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/ 16 марта 2020

У меня есть сценарий face_recognition python, и он работает нормально, если выполняется, но он случайным образом показывает ошибку, если выполняется: 

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

Эта ошибка показывает, что случайное выполнение иногда иногда приводит к этой ошибке. Я не понимаю, что происходит, но я изменяю допуск face_recognition в api.py с 0,6 до 0,4 раньше. Я не уверен, что chage делает случайную ошибку в opencv

Я хочу запустить свой скрипт и не получаю никаких случайных ошибок, как это, какое-либо решение?

версия среды:

  • python = 3.8.2
  • opencv-contrib- python 4.2.0.32
  • opencv- python 4.2.0.32
  • face -признание 1.3.0
  • модели распознавания лиц 0.3.0

My python скрипт: 

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()
...