for i in range(len(self.R_layer)):
y = np.array(
[np.array([1]) if i == el else np.array([0]) for el in y_type])
errors = self.train_neuron(X, y, self.R_layer[i])
#print(errors)
print("Perceptron: training OK")
if __name__ == "__main__":
X = []
y = []
N = 20
for i in range(10):
I = ImageProc(N, "training/%d/" % i)
X += I.get_pictures()
y += [i] * N
P = Perceptron(2000)
start_training = time.time()
P.train_network(X, y)
print("Training complite in %fsec" %
round(time.time() - start_training, 4))
print("\nTesting results:")
N = 25
avg = 0
for i in range(10):
I = ImageProc(N, "testing/%d/" % i)
X = I.get_pictures()
