rightAnswers = np.array([[0, 1]])
elif 6 < number < 16 or number == 17:
rightAnswers = np.array([[1, 1]])
elif number == 0 or number == 16:
rightAnswers = np.array([[0, 0]])
# print('rightAnswers = ', rightAnswers)
image = cv2.imread("dataset/test/" + str(number) + ".png",
0).flatten() / 255
if pro == 15 and i % 25 == 0:
ppi = np.vstack((ppi, n.train(image, rightAnswers).T))
plt.clf()
plt.xlabel(i * 17)
plt.plot(ppi)
plt.draw(
) # Должно быть это, а в итоге не это, приходится каждый раз открывать картинку
plt.pause(0.0000000000000000000001)
else:
n.train(image, rightAnswers)
plt.title('lr = ' + str(learning_rate))
plt.ioff()
plt.show()
for i in range(18):
image = cv2.imread("dataset/test/" + str(i) + ".png", 0).flatten() / 255
print(n.query(image))
np.save('./weights/example_1', n.synaptic_weight1)
np.save('./weights/example_2', n.synaptic_weight2)
from Network import NeuralNetwork
import cv2
import numpy as np
import matplotlib.pyplot as plt
n = NeuralNetwork(9, 5, 2, 0.3)
n.synaptic_weight1 = np.load('./weights/example_1.npy')
n.synaptic_weight2 = np.load('./weights/example_2.npy')
image = cv2.imread("dataset/test/test2.0.png", 0)
inputs = image.flatten()
inputs = np.asfarray(inputs / 255.0 * 0.99) + 0.01
answers = n.query(inputs)
print(str(answers[0]) + str(answers[1]))
plt.imshow(image)
plt.xlabel('test2.0.png')
plt.title(str(answers[0]) + ' -- ' + str(answers[1]))
plt.show()
for i in range(18):
image = cv2.imread("dataset/test/" + str(i) + ".png", 0)
inputs = image.flatten()
inputs = np.asfarray(inputs / 255.0 * 0.99) + 0.01
answers = n.query(inputs)
print(str(answers[0]) + str(answers[1]))
