一个很简单的代码,只有32行
import tensorflow as tf
from tensorflow.keras.preprocessing.image import ImageDataGenerator
fashion = tf.keras.datasets.fashion_mnist
(x_train, y_train), (x_test, y_test) = fashion.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
x_train = x_train.reshape(x_train.shape[0], 28, 28, 1) # 给数据增加一个维度,使数据和网络结构匹配
image_gen_train = ImageDataGenerator(
rescale=1. / 1., # 如为图像,分母为255时,可归至0~1
rotation_range=45, # 随机45度旋转
width_shift_range=.15, # 宽度偏移
height_shift_range=.15, # 高度偏移
horizontal_flip=True, # 水平翻转
zoom_range=0.5 # 将图像随机缩放阈量50%
)
image_gen_train.fit(x_train)
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(128, activation='relu'),
tf.keras.layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),
metrics=['sparse_categorical_accuracy'])
model.fit(image_gen_train.flow(x_train, y_train, batch_size=32), epochs=5, validation_data=(x_test, y_test),
validation_freq=1)
model.summary()
但是运行后报错:
请问是为啥?
配置环境好像也没问题?用的Anacdoda的tensorflow环境