def check_face_for_pickled(self, pickle_filename, classifier="haarcascade_frontalface_alt.xml"):
self.pickle_data = pickle.load(open(pickle_filename,"rb"))
i = 0
n = len(self.pickle_data)
for listingId in self.pickle_data:
print("Processing %d of %d images." % (i,n))
i = i + 1
self.imgGrabber.get_listing_image(listingId)
self.pickle_data[listingId]['face'] = find_face(self.imgGrabber.cvImage, True, listingId, classifier)
def check_for_faces(self, classifier="haarcascade_frontalface_alt.xml"):
n = len(self.listingIds)
i = 0
faces = 0
non_faces = 0
for listingId in self.listingIds:
if listingId not in self.listingStatistics:
self.listingStatistics[listingId] = {}
print("Processing %d of %d images." % (i,n))
i = i + 1
self.imgGrabber.get_listing_image(listingId)
self.listingStatistics[listingId]['face'] = find_face(self.imgGrabber.cvImage, True, listingId, classifier)
if self.listingStatistics[listingID]['face']:
faces += 1
else:
non_faces += 1
print("%d faces found, %d not found." % (faces, non_faces))
def face_recognition():
if request.method == 'POST':
if 'file' in request.files:
# Recebendo Variaveis
file = request.files.get('file')
idPerson = request.form.get('idPerson')
if idPerson == None :
return 'Campo idPerson Obrigatório'
roomId = request.form.get('roomId')
if roomId == None :
return 'Campo roomId Obrigatório'
url = "https://x29x40ex17.execute-api.sa-east-1.amazonaws.com/dev/room/participant"
# Criando Objeto para requisição
obj = {
"id" : idPerson,
"roomId" : roomId
}
headers = {
'Content-Type': 'application/json'
}
# Realizando Requisição para Lambda
response = requests.request("POST", url, headers=headers, json = obj)
person = json.loads(response.text)
print(person['name'])
# Chamando Aplicação de Reconhecimento Facial
if find_face(file) == 1:
name = face_rec(file, person)
if name == 'Unknown':
resp_data = "not register"
elif name == 'Not find':
resp_data = 'Not find any face'
else:
resp_data = "Register"
return name
