我从 github 存储库中获取了一个 python 程序，它使用 azure 面部 api 来识别面部。当我运行代码时，出现以下错误。 我不确定这是否是“face_api_url”中的错误..
Define the group name -> family
Traceback (most recent call last):
File "D:\python-azure-ai-face-recognition\face_recognition.py", line 126, in <module>
start()
File "D:\python-azure-ai-face-recognition\face_recognition.py", line 60, in start
list(map(lambda x: create_group(x), GROUPS))
File "D:\python-azure-ai-face-recognition\face_recognition.py", line 60, in <lambda>
list(map(lambda x: create_group(x), GROUPS))
^^^^^^^^^^^^^^^
File "D:\python-azure-ai-face-recognition\face_recognition.py", line 29, in create_group
face_client.person_group.create(person_group_id=group, name=group)
File "C:\Users\Rushika\AppData\Local\Programs\Python\Python311\Lib\site-packages\azure\cognitiveservices\vision\face\operations\_person_group_operations.py", line 121, in create
raise models.APIErrorException(self._deserialize, response)
azure.cognitiveservices.vision.face.models._models_py3.APIErrorException: (InvalidRequest) Invalid request has been sent.
我采用的代码如下。我导入了所有必要的库和所有内容。端点和密钥在 JSON 文件中提供。我唯一不确定的是“face_api_url”。我在网上找不到它的正确定义
import cv2
import requests
import time
import json
import glob
import sys
from azure.cognitiveservices.vision.face import FaceClient
from msrest.authentication import CognitiveServicesCredentials
# Variables
#path = 'D:\python-azure-ai-face-recognition\json_key.json'
credentials = json.load(open('./json_key.json'))
KEY = credentials['KEY']
ENDPOINT = credentials['ENDPOINT']
face_api_url = "https://eastusrushikafr.cognitiveservices.azure.com/face/v1.0/detect"
headers = {'Content-Type': 'application/octet-stream', 'Ocp-Apim-Subscription-Key': KEY}
params = {'detectionModel': 'detection_01', 'returnFaceId': 'true', 'returnFaceRectangle': 'true', 'returnFaceAttributes': 'age, gender, emotion'}
GROUPS = []
PEOPLE = []
ID = []
face_client = FaceClient(ENDPOINT, CognitiveServicesCredentials(KEY))
# Functions
def create_group(group):
face_client.person_group.create(person_group_id=group, name=group)
print('Created group {}'.format(group))
def create_person(person, group):
globals()[person] = face_client.person_group_person.create(group, person)
print('Person ID:', globals()[person].person_id)
ID.append(globals()[person].person_id)
photo_list = [file for file in glob.glob('*.jpg') if file.startswith(person)]
time.sleep(1)
for image in photo_list:
face_client.person_group_person.add_face_from_stream(
GROUPS[0], globals()[person].person_id, open(image, 'r+b'))
print('Included photo {}'.format(image))
time.sleep(1)
def train(group):
print('Starting training for {}'.format(group))
face_client.person_group.train(group)
while (True):
training_status = face_client.person_group.get_training_status(group)
print("Training status of {}: {}.".format(group, training_status.status))
if (training_status.status == 'succeeded'):
break
elif (training_status.status == 'failed'):
face_client.person_group.delete(person_group_id=group)
sys.exit('Training the person group has failed.')
time.sleep(5)
def start():
GROUPS.append(input('Define the group name -> ').lower())
list(map(lambda x: create_group(x), GROUPS))
people_list = []
person_name = None
while person_name != 'end':
person_name = input("Enter the name of the person to associate with the group '{}' or type 'end' to finish. -> ".format(GROUPS[0])).lower()
if person_name != 'end':
PEOPLE.append(person_name)
people_list.append(person_name)
if len(people_list) == 1:
print('{} has been added to the group {}'.format(PEOPLE[0], GROUPS[0]))
else:
last_name = people_list.pop()
names = ', '.join(people_list)
print('{} and {} have been added to the group {}'.format(names, last_name, GROUPS[0]))
list(map(lambda x: create_person(x, GROUPS[0]), PEOPLE))
list(map(lambda x: train(x), GROUPS))
cam = cv2.VideoCapture(0)
while True:
ret, frame = cam.read()
image = cv2.imencode('.jpg', frame)[1].tobytes()
response = requests.post(face_api_url, params=params, headers=headers, data=image)
response.raise_for_status()
faces = response.json()
face_ids = [face['faceId'] for face in faces]
global results
for face in face_ids:
results = face_client.face.identify(face_ids, GROUPS[0])
# Obtaining landmarks
for n, (face, person, id, name) in enumerate(zip(faces, results, ID, PEOPLE)):
rect = face['faceRectangle']
left, top = rect['left'], rect['top']
right = int(rect['width'] + left)
bottom = int(rect['height'] + top)
draw_rect = cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 3)
att = face['faceAttributes']
age = att['age']
if len(person.candidates) > 0 and str(person.candidates[0].person_id) == str(id):
print('Person for face ID {} is identified in {}.{}'.format(person.face_id, 'Frame', person.candidates[0].person_id))
draw_text = cv2.putText(frame, 'Name: {}'.format(name), (left, bottom + 50), cv2.FONT_HERSHEY_TRIPLEX, 0.5, (0, 0, 255), 1, cv2.LINE_AA)
faces[n]['name'] = str(name)
else:
draw_text = cv2.putText(frame, 'Name: Unknown', (left, bottom + 50), cv2.FONT_HERSHEY_TRIPLEX, 0.5, (0, 0, 255), 1, cv2.LINE_AA)
faces[n]['name'] = 'Unknown'
cv2.imshow('face_rect', draw_rect)
k = cv2.waitKey(1) & 0xFF # bitwise AND operation to get the last 8 bits
if k == 27:
print("Escape hit, closing...")
break
def end(group_name):
cv2.destroyAllWindows()
face_client.person_group.delete(person_group_id=group_name)
# Start the code
start()
# Stop and clean
end('group_name')
您收到此错误是因为 Face API 的许多功能都被锁定，除了访问受限的客户之外。
根据微软的说法： 人脸服务访问权限根据资格和使用标准进行限制，以支持我们的 Responsible AI 原则。您收到此错误是因为您尝试调用的内容现在限制了对它们的访问，因为您尚未被批准使用该功能。