卷积神经网络的Helloworld例子

下面是keras官方的卷积神经网络在github上的例子。和原版的唯一区别是：mnist的数据因为在国外（由于访问外国网站的原因，报错Exception: URL fetch failure on https://s3.amazonaws.com/img-datasets/mnist.npz），可以像我一样，下载数据后，放在本地。

batch_size = 128 num_classes = 10 epochs = 12 # input image dimensions img_rows, img_cols = 28, 28 # the data, split between train and test sets #(x_train, y_train), (x_test, y_test) = mnist.load_data() #把原版的网上的数据下载到本地 path='D://tmp//mnist.npz' f = np.load(path) x_train, y_train = f['x_train'], f['y_train'] x_test, y_test = f['x_test'], f['y_test'] f.close() if K.image_data_format() == 'channels_first': x_train = x_train.reshape(x_train.shape[0], 1, img_rows, img_cols) x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols) input_shape = (1, img_rows, img_cols) else: x_train = x_train.reshape(x_train.shape[0], img_rows, img_cols, 1) x_test = x_test.reshape(x_test.shape[0], img_rows, img_cols, 1)

更多请见：https://blog.csdn.net/qq_43650923/article/details/100739553