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