text: Title: Train a region detector on the features from Visual Genome
  Body: This is a project in computer vision, rather than natural language processing. It is here because we have found this `RegionEmbedder` to be important for down-stream tasks that combine vision and language features.
  
  In AllenNLP, `RegionDetector`s take an image and predict "regions of interest". Each region is represented by some coordinates and a vector expressing the contents of the region.
  
  [Visual Genome](http://visualgenome.org) is a dataset containing millions of such regions. This task about training a new region detector on the Visual Genome dataset.
  
  Most of the meat of the model will not be implemented from scratch. Rather, we will use the components that `torchvision` gives us. Most of the work will be in writing a dataset reader that can read the visual genome features, and writing a model that is basically an adapter between the AllenNLP formats and the `torchvision` formats.
  
  This project has many moving parts, and will likely be a bit on the difficult side.