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The dataset has 19 classes, plus the background, the output of last layer should be 20 classes. But the pre-trained model produces a 19 channels output. Do the background just be ignored? But in the train code, the ignored-label is set to 0.
I am a little confused, please help!
The text was updated successfully, but these errors were encountered:
Hey, sorry for confusing you. The ignore-label of cityscapes is not 0 (is 255), I forgot to change it before I upload the training code. So when training, we will focus on the 0~18 classes and ignore the background (255), which means we don't want to learn how to recognize the background. Does that make sense to you?
The dataset has 19 classes, plus the background, the output of last layer should be 20 classes. But the pre-trained model produces a 19 channels output. Do the background just be ignored? But in the train code, the ignored-label is set to 0.
I am a little confused, please help!
The text was updated successfully, but these errors were encountered: