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)
