def recognize(sentence):
# with Recognition(sentence) as recognize:
recognition = Recognition.Recognition(gpio)
recognition.answer(sentence.encode('utf-8'))
gpio.cleanup()
# print('Exiting..')
# time.sleep(2)
restart()
def main():
test = recognition.Recognition()
vc = voice.Voice()
name = test.getFromCam()
if (name != 'Unknown'):
vc.sayHello(str(name))
else:
test.RegisterNewPerson()
def snapshot(self):
# Get a frame from the video source
ret, frame = self.vid.get_frame()
if ret:
imageName = os.path.curdir + "\\images\\frame-" + time.strftime(
"%d-%m-%Y-%H-%M-%S") + ".jpg"
cv2.imwrite(imageName, cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))
# face recognition here
recognition.Recognition(os.path.curdir + "\\test\\" + self.knowImg,
imageName)
def process_image(self):
if self.path_to_source_file == '':
return
reconAlgorithm = recognition.Recognition(self.path_to_source_file)
recon_image = reconAlgorithm.new_path
found_image = reconAlgorithm.final_recon_path
self.load_pic_to_window_right(recon_image)
self.load_recon_image(found_image)
self.load_text_to_recon_info(reconAlgorithm.result)
import communication
import recognition
import threading
# import logging
haar_file_path = 'haarcascade_frontalface_default.xml'
SOURCE_IP = '127.0.0.1'
SOURCE_PORT = 5006
DESTINATION_IP = '127.0.0.1'
DESTINATION_PORT = 5005
connection = communication.Communication(SOURCE_IP, DESTINATION_IP,
SOURCE_PORT, DESTINATION_PORT)
connection.bind_socket()
face_recognition = recognition.Recognition(haar_file_path)
# log = logging.getLogger(__name__)
# LOG_FILENAME = 'local.log'
# logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG, format='%(asctime)s %(message)s')
def receive():
while True:
data, address = connection.receive_packet()
print(data, address)
command = ""
t = threading.Thread(target=receive)
t.daemon = True
t.start()
while command != 'q':