def __init__(self, CONFIG): try: self.conn = psycopg2.connect(host=CONFIG['db_host'], port=CONFIG['db_port'], database=CONFIG['db_name'], user=CONFIG['db_user'], password=CONFIG['db_password']) except Exception as e: print "Could not connect to the database" print e system.exit(2)
def exit(self, error): self.logout() system.exit(error, self.__colored)
def pong_received(data, address, udp_server): #print 'pong_received' if not (data == 'pong!' and address == ('127.0.0.1', 12345)): exit(1) reactor.stop()
target_size=(64, 64), batch_size=32, class_mode='binary') classifier.fit_generator(training_set, steps_per_epoch=(277 / 32), epochs=25, validation_data=test_set, validation_steps=(73 / 32)) # Part 3 - Making new predictions import numpy as np from keras.preprocessing import image test_image = image.load_img('dataset/single_prediction/pollen.jpg', target_size=(64, 64)) test_image = image.img_to_array(test_image) test_image = np.expand_dims(test_image, axis=0) result = classifier.predict(test_image) training_set.class_indices if result[0][0] == 1: prediction = 'pollen' else: prediction = 'nonpollen' print(prediction) import system as sys sys.exit()
def ping_received(data, address, udp_server): #print 'ping_received' if not (data == 'ping!' and address == ('127.0.0.1', 54321)): exit(1) udp_server.send_to('pong!', address)