Dear all,
I am working on cavity segmentation problem. My data has only one class i.e., cavity. Initially, I am trying to fine tune baseline FCN segmentation model. By default, the model is trained on 21 classes, as shown in following figure.
In the paper cited in the FCN_ResNet50 documentation you can see that they use the PASCAL VOC 2011 dataset, which has 20 classes. They also mention that the 21st class would be the background.
So for your implementation I would try and use 2 different classes, one for the objects that you want to detect and one for the background.