I am trying to build a deep learning model for Saliency analysis using caffe (I am using the python wrapper). But I am unable to understand how to generate the lmdb data structure for this purpose. I have gone through the Imagenet and mnist examples and I understand that I should generate labels in the format
You can approach this problem in two ways:
1. Using HDF5 data layer instead of LMDB. HDF5 is more flexible and can support labels the size of the image. You can see this answer for an example of constructing and using HDF5 input data layer.
2. You can have two LMDB input layers: one for the image and one for the label. Note that when you build the LMDB you must not use the
'shuffle' option in order to have the images and their labels in sync.