基于keras的unet实现，在traingengerator和main程序中出现了step_per_epoch=2000和300的情况
myGene = trainGenerator(2,'data/membrane/train','image','label',data_gen_args,save_to_dir = None)
#得到一个生成器，以batch=2的速率无限生成增强后的数据，没有理解“以batch=2的速率无限生成增强后的数据”
#traingenerator中
myGene = trainGenerator(2,'data/membrane/train','image','label',data_gen_args,save_to_dir = None)
model = unet()
model_checkpoint = ModelCheckpoint('unet_membrane.hdf5', monitor='loss',verbose=1, save_best_only=True)
model.fit_generator(myGene,steps_per_epoch=2000,epochs=5,callbacks=[model_checkpoint])
#main中
myGene = trainGenerator(2,'data/membrane/train','image','label',data_gen_args,save_to_dir = None)
model = unet()
model_checkpoint = ModelCheckpoint('unet_membrane.hdf5', monitor='loss',verbose=1, save_best_only=True)
model.fit_generator(myGene,steps_per_epoch=300,epochs=1,callbacks=[model_checkpoint])