我使用CNN来分类多类图像，我正在使用带有Tensorflow后端的Keras
model = Sequential()
model.add(Conv2D(32, (3, 3), input_shape=(img_width, img_height, 3)))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(nb_filters2, (3, 3)))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Flatten())
model.add(Dense(256))
model.add(Activation("relu"))
model.add(Dropout(0.5))
model.add(Dense(classes_num, activation='softmax'))
model.compile(loss='categorical_crossentropy',
optimizer='rmsprop',
metrics=['accuracy'])
和适合的步骤：
train_datagen = ImageDataGenerator(
rescale=1. / 255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
test_datagen = ImageDataGenerator(rescale=1. / 255)
train_generator = train_datagen.flow_from_directory(
train_data_path,
target_size=(img_height, img_width),
batch_size=batch_size,
class_mode='categorical')
validation_generator = test_datagen.flow_from_directory(
validation_data_path,
target_size=(img_height, img_width),
batch_size=batch_size,
class_mode='categorical')
model.fit_generator(
train_generator,
samples_per_epoch=samples_per_epoch,
epochs=epochs,
validation_data=validation_generator,
callbacks=cbks,
validation_steps=validation_steps)
但是当它运行时，我遇到了这个错误：
ValueError: Error when checking target: expected dense_6 to have shape (3,) but got array with shape (9,)
我该如何修复我的代码？我的图片有3个 Channels