data = np.append(gatos,perros, 0)
lbls = np.append(lbl_gatos,lbl_perros, 0)
test_data = np.append(test_gatos, test_perros, 0)
test_lbls = np.append(lbl_test_gatos, lbl_test_perros, 0)
#print(lbls.shape)
brain.load_hyperparam("hyper_dogs_cats_MEGA.npz")
es,ps = [],[]
try:
#brain.stochastic_gradient_descent(data[:-50], lbls[:-50], 1000000)
es, ps = brain.SGD(data, lbls, mini_batch_size=500, epochs=100, test_imgs = test_data, test_lbls = test_lbls)
plt.plot(es,ps)
plt.show()
#pass
except KeyboardInterrupt:
print("Entrenamiento detenido")
finally:
brain.imprimir_precision(data, lbls)
brain.imprimir_precision(test_data, test_lbls, debug = True)
brain.save_hyperparam("hyper_dogs_cats_MEGA.npz")
posibilidades = ("perro", "gato")
