Jing Zhang

It seems that the input shape has to be divided by 48, for example, (240,240,3) is ok, but (224,224,3) will have errors. Good luck. By the way, when I use...

hello, how to convert 30 predicted images into one tif image? Thanks.

Hello, I also have doubts about data augmentation. How can I know the exact number of augmented data or the rules of it? For example, my train data has 60...

`hist = model.fit_generator(trainGene, validation_data=validGene, validation_steps=3, steps_per_epoch=step_epoch, epochs=epochs, verbose=2, shuffle=True, callbacks=[model_checkpoint,tensorboard,history])` I solved the problem by writing this way. Hope helpful to someone.

`tensorboard = TensorBoard(log_dir='./logs', histogram_freq=0,write_graph=True, write_images=False) ` this is to define tensorboard,and you need to import relevant packages. `history = LossHistory() ` this is to define history, but LossHistory() is a...

> > `hist = model.fit_generator(trainGene, validation_data=validGene, validation_steps=3, steps_per_epoch=step_epoch, epochs=epochs, verbose=2, shuffle=True, callbacks=[model_checkpoint,tensorboard,history])` > > I solved the problem by writing this way. Hope helpful to someone. > > What does...

> > > > `hist = model.fit_generator(trainGene, validation_data=validGene, validation_steps=3, steps_per_epoch=step_epoch, epochs=epochs, verbose=2, shuffle=True, callbacks=[model_checkpoint,tensorboard,history])` > > > > I solved the problem by writing this way. Hope helpful to someone....

> > > > > > `hist = model.fit_generator(trainGene, validation_data=validGene, validation_steps=3, steps_per_epoch=step_epoch, epochs=epochs, verbose=2, shuffle=True, callbacks=[model_checkpoint,tensorboard,history])` > > > > > > I solved the problem by writing this way....

你好， 请问输出图像（256*256）和label图像（512*512）尺寸不一样，是如何计算loss function的？

Hello, in multi-class loss function? Do we need to do one-hot encoding?