Question

我正在尝试创建一个for循环，该循环使用一个图像文件夹，并将名称剥离到一个列表中，然后将图像编码为另一个列表中的numpy数组。在我尝试使用face_recognition库的比较功能之前，代码工作正常。我已经附上了部分代码。

错误：

VisibleDeprecationWarning：不推荐使用粗糙的嵌套序列（它是具有不同长度或形状的list-or-tuples或ndarray的list-tuple）创建ndarray。如果您打算这样做，则在创建ndarray时必须指定“ dtype = object” 返回np.linalg.norm（face_encodings-face_to_compare，axis = 1）

代码：

import cv2 
import face_recognition
import dlib
from imutils import paths
import imutils
import os
import numpy as np


def main():
    video_capture = cv2.VideoCapture(0)
    print(cv2.CAP_PROP_FPS)

    
    knownNames = []
    knownFaces = []
    frameNumber = 0
    faceLocation = []

    imagePaths = list(paths.list_images("dataset"))
    for (i, imagePath) in enumerate(imagePaths):
        # extract the person name from the image path
        print("[INFO] processing image {}/{}".format(i + 1,
            len(imagePaths)))
        name = imagePath.split(os.path.sep)[-2]

        
        image = cv2.imread(imagePath)
        imageEncoding = face_recognition.face_encodings(image)

        knownNames.append(name)
        knownFaces.append(imageEncoding)

    while True:
        ret, frame = video_capture.read()

        # ***problems start here***
        rgb_frame = frame[:, :, ::-1]
        face_locations = face_recognition.face_locations(rgb_frame, model="hog")
        face_encodings = face_recognition.face_encodings(rgb_frame, face_locations, model="large")

        for face_encoding in face_encodings:
            # See if the face is a match for the known face(s)
            match = face_recognition.compare_faces(knownFaces, face_encoding, tolerance=0.6)

            if match[0]:
                name = [knownNames][0]

        cv2.imshow('video', frame)

        if cv2.waitKey(5) & 0xFF == ord('q'):
            break

    video_capture.release()
    cv2.destroyAllWindows()
if __name__=='__main__':
    main()

尝试实现face_recognition库时出错：numpy arrary折旧必须添加'dtype = object'

0 个答案: