关于python人脸识别库的数据类型问题

Question

import face_recognition
import cv2
import os

def file_name(dir):
    names = os.listdir(dir)
    i=0
    for name in names:
        index = name.rfind('.')
        name = name[:index]
        names[i]=name
        i=i+1
    return names

def file_list(dir):
    list_name=os.listdir(dir)
    return list_name
video_capture = cv2.VideoCapture(0)
face_dir="E:\\face"
names1=file_name(face_dir)
root=file_list(face_dir)
for name1 in names1:
    image = face_recognition.load_image_file("E:\\face\\"+name1+".jpg")
    name1 = face_recognition.face_encodings(image)[0]
    # name1 = name1.astype('float64')



# Create arrays of known face encodings and their names
known_face_encodings = names1
known_face_names = names1
print(known_face_encodings)
# Initialize some variables
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True

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

    # Resize frame of video to 1/4 size for faster face recognition processing
    small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)

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

    # Only process every other frame of video to save time
    if process_this_frame:
        # Find all the faces and face encodings in the current frame of video
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)

        face_names = []
        for face_encoding in face_encodings:
            # See if the face is a match for the known face(s)
            #face_encoding = face_encoding.astype('float64')
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
            name = "Unknown"
            print(matches)
            # 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]
                print(first_match_index)
            face_names.append(name)

    process_this_frame = not process_this_frame


    # Display the results
    for (top, right, bottom, left), name in zip(face_locations, face_names):
        # Scale back up face locations since the frame we detected in was scaled to 1/4 size
        top *= 4
        right *= 4
        bottom *= 4
        left *= 4

        # 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()

总是提示： return np.linalg.norm(face_encodings - face_to_compare, axis=1)
TypeError: ufunc 'subtract' did not contain a loop with signature matching types dtype('S32') dtype('S32') dtype('S32')

这是什么鬼，转换了数据类型也没有用？？？

Answer 1

https://blog.csdn.net/u012005313/article/details/51567804