小编use*_*890的帖子

嗨,我是Keras的新手,有后端张量流.我已经构建了两个可能类的图像的训练和验证集; 我的网络必须以两个类是或否结束.我使用ImageDatagenerator从文件夹中读取图像并准备培训和验证集.最后,我得到了标题中描述的问题.我的猜测是ImageDatagenerator没有像我想的那样准备数据; 任何机构都可以向我解释如何解决它,这里是代码(谢谢):

# Data Preparation
# dimensions of our images.
img_width, img_height = 256, 256

#top_model_weights_path = 'bottleneck_fc_model.h5'
train_data_dir = 'data/train'
validation_data_dir = 'data/validation'
nb_train_samples = 2
nb_validation_samples = 2
epochs = 50
batch_size = 1
num_classes = 2

# prepare data augmentation configuration
train_datagen = ImageDataGenerator(
                                   rescale=1. / 255,
                                   shear_range=0.2,
                                   zoom_range=0.2,
                                   data_format=K.image_data_format(),
                                   horizontal_flip=True)

test_datagen = ImageDataGenerator(
                                  rescale=1. / 255,
                                  data_format=K.image_data_format())

train_generator = train_datagen.flow_from_directory(
                                                    train_data_dir,
                                                    target_size=(img_height, img_width),
                                                    batch_size=batch_size,
                                                    class_mode='binary')

validation_generator = test_datagen.flow_from_directory(
                                                        validation_data_dir,
                                                        target_size=(img_height, img_width),
                                                        batch_size=batch_size,
                                                        class_mode='binary')

# create …