def __init__(self):
super(Cognitive, self).__init__()
self.api = cognitive_face
file_path = Utilities.absolute_path(__file__, 'secret.json')
with open(file_path) as data_file:
data = json.load(data_file)
KEY = data['secret']
self.api.Key.set(KEY)
def speak(alias):
sounds_dir = Utilities.voices_path()
save_dir = Utilities.absolute_path(sounds_dir, alias + '.mp3')
if os.path.exists(save_dir) is True:
# print save_dir
pygame.mixer.init(44100, -16, 2, 2048)
pygame.mixer.music.load(save_dir)
pygame.mixer.music.play()
time.sleep(1.05)
def __init__(self, camera):
"""Initialization
Args:
camera (int): index of camera to use
"""
self.cascade_file = Utilities.absolute_path(__file__, 'cascade.xml')
self.face_cascade = cv2.CascadeClassifier(self.cascade_file)
self.video_capture = cv2.VideoCapture(camera)
self.video_capture.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 640)
self.video_capture.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 480)
self.faces_captured = 1
def start_capturing(self, is_register):
"""Start the camera, look for faces and write to file when faces are captured
Args:
is_register (bool): determine if the session is
registering or identifying
If this argument is true then camera will capture 3
photos of user. Otherwise, only 1 photo is captured
"""
if is_register is False:
self.faces_captured = DEFAULT_FACES - 1
while self.faces_captured < DEFAULT_FACES:
# Read frame from video capture
return_code, frame = self.video_capture.read()
# Use Haar cascade to detect faces in captured frame
faces = self.face_cascade.detectMultiScale(
cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY),
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30),
flags=cv2.cv.CV_HAAR_SCALE_IMAGE
)
# Looping through captured faces and write to file
for (x, y, w, h) in faces:
# All captured images will be saved in tmp folder in
# core/face_recognizer
filePath = Utilities.absolute_path(
__file__, 'tmp/face%d.jpg' % self.faces_captured)
self.faces_captured += 1
cv2.imwrite(filePath, frame)
if is_register:
# Sleep 2 seconds so user can change face orientation
time.sleep(2)
break
if cv2.waitKey(1) & 0xFF == ord('q'):
self.stop_capturing()
break
# cv2.imshow('Video', frame)
self.stop_capturing()
def register(group, alias):
data_path = Utilities.absolute_path(Utilities.train_data_path(), alias)
with open(os.path.join(data_path, 'name.txt'), 'r') as file:
name = file.read()
person = group.person_with_name(name)
person.alias = alias
create_voice_thread = threading.Thread(
name="create_voice",
target=Person.__create_voice,
args=(name, alias))
person.save()
save_faces_thread = threading.Thread(name="save_faces",
target=Person.__save_faces,
args=(person, data_path))
processes = ProcessParallel(create_voice_thread, save_faces_thread)
processes.fork_threads()
processes.start_all()
# Wait until all threads are done
processes.join_all()
def create_voice(text, alias):
sounds_dir = Utilities.voices_path()
save_dir = Utilities.absolute_path(sounds_dir, alias + '.mp3')
if os.path.exists(save_dir) is False:
headers = {
'Content-Type': 'application/json',
'api_key': 'b5db987b5a944ff78097d435a5a564dc'
}
try:
response = requests.request(
'POST',
'http://api.openfpt.vn/text2speech/v3',
headers=headers,
data=text
)
if response.status_code not in (200, 202):
print response.status_code
if response.text:
result = response.json()
if result['async']:
wget.download(result['async'], save_dir)
except Exception as e:
print e