def detect_by_conditions(video, conditions, face_api=True):
cur = 0
faces_images = []
cap = cv2.VideoCapture(video)
success, frame = cap.read()
count = 0
while success:
if count % 3 == 0:
frame = imutils.resize(frame, width=WIDTH)
face_api_response = detect(frame) if face_api else 0
if face_api_response is not None and conditions[cur].check_face(frame, face_api_response):
if face_api_response != 0 and check_same_person(face_api_response['faceId']):
print_error('The same person already exists')
faces_images.append(frame)
cur += 1
if cur == len(conditions):
return faces_images
count += 1
success, frame = cap.read()
return None
def handle_photo(bot, update):
try:
new_file = bot.getFile(update.message['photo'][1]['file_id'])
new_file.download(
os.path.join('archive',
'img{0}_1.png'.format(str(update.message.chat_id))))
img = io.imread(
os.path.join('archive',
'img{0}_1.png'.format(str(update.message.chat_id))))
img = img[:, :, :3].copy()
char = api.detect(img)[0]
bot.sendMessage(
chat_id=update.message.chat_id,
text='Футболист - {0}\nСборная - {1}\nТочность - {2}'.format(
char['name'].split('.')[0], char['country'], char['mn']))
bot.sendPhoto(chat_id=update.message.chat_id,
photo=open(
os.path.join(os.path.join('teams', char['country']),
'_'.join(char['name'].split(" "))),
'rb'))
except Exception as e:
print(e)
bot.sendMessage(
chat_id=update.message.chat_id,
text=
"Произошла ошибка. Убедитесь, что на фотографии лицо видно четко.")
def simple_identify(video):
cap = cv2.VideoCapture(video)
success, frame = cap.read()
count = 0
faces_ids = []
while success:
if count % 5 == 0:
frame = imutils.resize(frame, width=WIDTH)
face_api_response = detect(frame)
if face_api_response is not None:
faces_ids += [face_api_response['faceId']]
if len(faces_ids) == 5:
break
count += 1
success, frame = cap.read()
if len(faces_ids) < 5:
print_error('The video does not follow requirements')
person_id = identify_person_id(faces_ids)
if person_id is None:
print_error('The person was not found')
return person_id
def detect_all(video):
faces_images = []
cap = cv2.VideoCapture(video)
success, frame = cap.read()
count = 0
while success:
if count % 5 == 0:
frame = imutils.resize(frame, width=WIDTH)
face_api_response = detect(frame)
if face_api_response is not None:
if check_same_person(face_api_response['faceId']):
print_error('The same person already exists')
faces_images.append(frame)
if len(faces_images) == 5:
return faces_images
count += 1
success, frame = cap.read()
return None
def detect_all(video):
faces_images = []
cap = cv2.VideoCapture(video)
success, frame = cap.read()
count = 0
while success:
if count % 5 == 0:
frame = imutils.resize(frame, width=WIDTH)
face_api_response = detect(frame)
if face_api_response is not None:
faces_images.append(frame)
if len(faces_images) == 5:
return faces_images
count += 1
success, frame = cap.read()
return None
def detect_by_conditions_in_any_order(video, conditions, face_api=True):
completed = 0
faces_images = []
cap = cv2.VideoCapture(video)
success, frame = cap.read()
while success:
frame = imutils.resize(frame, width=WIDTH)
face_api_response = detect(frame) if face_api else 0
if face_api_response is not None:
for condition in conditions:
if condition.check_face(frame, face_api_response):
faces_images.append(frame)
completed += 1
break
if completed == len(conditions):
return faces_images
success, frame = cap.read()
return None
def identify(video, actions):
cap = cv2.VideoCapture(video)
success, frame = cap.read()
actions = list(map(action_to_face_condition, actions))
count = 0
cur = 0
faces_ids = []
while success:
if count % 5 == 0:
frame = imutils.resize(frame, width=WIDTH)
face_api_response = detect(frame)
if face_api_response is not None and actions[cur].check(frame, face_api_response):
faces_ids += [face_api_response['faceId']]
cur += 1
if cur == len(actions):
break
count += 1
success, frame = cap.read()
if cur < len(actions):
print_error('The video does not follow requirements')
person_id = identify_person_id(faces_ids)
if person_id is None:
print_error('The person was not found')
return person_id
tY = tsize * desiredLeftEye
M[0, 2] += (tX - eyesCenter[0])
M[1, 2] += (tY - eyesCenter[1])
(w, h) = (tsize, tsize)
output = cv2.warpAffine(im, M, (w, h), flags=cv2.INTER_CUBIC)
crop.append(output)
return crop
#开启摄像头人脸检测
cap = cv2.VideoCapture(0)
while 1:
ret, frame = cap.read() #读取视频
frame = cv2.flip(frame, 1)
res = detect(frame)
# print('res',res,len(res))
if len(res) > 0:
#frame = puttext(frame,res)
crop_image = face_align(frame, res)
crop_image = np.array(crop_image)
#print(crop_image.shape)
#cv2.imshow('face',crop_image[0])
#cv2.imshow('face:',crop_image)
# frame = crop_image[0]
n, w, h, c = crop_image.shape
# for i in range(n-1):
# frame = np.concatenate([crop_image[i,:,:,:],crop_image[i+1,:,:,:]],axis=0)
if n == 1:
frame = crop_image[0]
import api
import GetReady
import voicecontrol as voice
group_id = "test"
if __name__ == '__main__':
print("-----------------进入人脸识别系统-------------")
voice.player("进入人脸识别系统")
image = GetReady.getIm()
# print(s)
# image = api.get_file_content(s)
imageType = "BASE64"
user = api.detect(image, imageType)
print(user)
print("他的年龄：", user['result']['face_list'][0]["age"])
if user['result']['face_list'][0]["gender"]['type'] == "male":
voice.player("看上去是一位" + str(user['result']['face_list'][0]["age"]) +
"岁的男士")
else:
voice.player("看上去是一位" + str(user['result']['face_list'][0]["age"]) +
"岁的女士")
print("正在注册你的信息....")
voice.player("正在注册你的信息....")
print("你的名字：")
voice.player("你的名字是：")
feedback = voice.my_record(1737)