Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Towards Data Science.
random x_test = [] for i in range(64): x_test.append(get_input(img_path[random.randint(0,len(img_id))])) x_test = np.array(x_test) figure_Decoded = vae_2.predict(x_test.astype('float32')/127.5 -1, batch_size = b_size) figure_original = x_test[0] figure_decoded = (figure_Decoded[0]+1)/2 for i in