我的代码给了我一个我不理解的“ ValueError”
我研究了错误语句中的所有文件，并尝试正确访问模块的受保护成员。
import face_recognition
import cv2
import numpy as np
import numpy.core._multiarray_umath as pr
video_capture = cv2.VideoCapture(0)
image_of_person = face_recognition.load_image_file(
"/Users/mynameisjeff..../projects/projects/varish-project/known-face/varishdad1.jpg")
known_face_encodings: pr.ndarray = face_recognition.face_encodings(image_of_person)[0]
known_face_encodings = [
image_of_person,
]
known_face_names = [
"Barack Obama",
"Joe Biden"
]
# 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: List[Union[str, Any]] = []
for face_encoding in face_encodings:
# See if the face is a match for the known face(s)
print(face_encoding)
print("i am here4")
print(known_face_encodings)
print("i am here 5")
print(face_encodings)
print("i am here 6")
matches: list[Any] = face_recognition.compare_faces(known_face_encodings, face_encoding)
#list[Any] = face_recognition.compare_faces(known_face_encodings, face_encoding)
print("i m here7")
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)
print("i am here8")
print(face_distances)
best_match_index: pr.ndarray[int] = np.argmin(face_distances)
# noinspection PyTypeChecker
if matches[best_match_index]:
# noinspection PyTypeChecker
name = known_face_names[best_match_index]
face_names.append(name)
process_this_frame = not process_this_frame
# Display the results
top: int
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()
错误消息是
File "/Users/mynameisjeff..../projects/projects/varish-project/facerec3.py", line 78, in <module>
matches: list[Any] = face_recognition.compare_faces(known_face_encodings, face_encoding)
File "/Users/mynameisjeff..../anaconda3/lib/python3.7/site-packages/face_recognition/api.py", line 224, in compare_faces
return list(face_distance(known_face_encodings, face_encoding_to_check) <= tolerance)
File "/Users/mynameisjeff..../anaconda3/lib/python3.7/site-packages/face_recognition/api.py", line 74, in face_distance
return np.linalg.norm(face_encodings - face_to_compare, axis=1)
ValueError: operands could not be broadcast together with shapes (1,720,1080,3) (128,)
我的代码的预期结果是它将为我提供代码中名称之一的输出