I am trying to implement U-NET segmentation on Kaggle 2018 Nuclei segmentation data. The training data set contains images with masks in such a way that each image has multiple masks(not a single mask). The example illustrated in MATLAB U-NET image segmentation has images with corresponding masks(Traing dataset has two folders train images which contain training images and train masks which contain training masks). And all images has same size.
The Kaggle training dataset has 670 folders(There are 670 images), each folder has training image folder which contain single image and training mask folder which contain multiple masks for corresponding image and every image has different size. My questions are
1) How to prepare input database to be fed to U-NET architecture?
2)How to transform different sizes of image to implement U-NET Segmentation?
3)How to implement U-NET Segmentation when we have multiple masks corresponding to a single image?