❮ Projects Raster Vision: Deep Neural Networks for Satellite and Aerial Imagery

At Azavea, we have been researching the use of convolutional neural networks for image segmentation, object detection and image classification on aerial and satellite imagery. We are building a framework for running deep learning tasks on imagery and other geospatial data types, called Raster Vision.

This project will utilize Raster Vision for preparing data for deep learning tasks, training models, evaluating model performance, and creating predictions.



In the beginning of the project you will prepare by:

  • Familiarization with Raster Vision
  • Review Deep Learning concepts such as CNNs, FCNs, ResNets, and U-Nets.

Coding Phase 1

In this phase, you will be using Raster Vision to accomplish tasks with known results.

  • Use Raster Vision to implement object detection, image classification and/or semantic segmentation tasks against known labeled datasets.
  • Reproducing state-of-the-art results contained in literature.
  • Document pain points of using Raster Vision in GitHub issues
  • Create documentation on Raster Vision usage

Coding Phase 2

In the second coding phase, you’ll make improvements to Raster Vision by adding capabilities:

  • Implement machine learning kernels (PyTorch, Caffe2, etc) in Raster Vision and compare model training times and evaluation metrics against runs of each implementation.
  • Implement any tasks that are not yet implemented (image segmentation, image classification, regression) for each o f the machine learning kernels.

Coding Phase 3

In the final phase, you’ll work through the usability issues discovered in Coding Phase 1, as well as document your experience in a blog post.

  • Improvements to Raster Vision based on usage
  • A blog post about the project.
  • Python programming experience
  • Familiarity with Numpy
  • Familiarity with Deep Learning concepts
  • Familiarity with Keras, TensorFlow, PyTorch, or similar a plus


Until next time

Summer 2018 session is closed

Applications for the Summer 2018 session of the Azavea Open Source Fellowship Program are now closed. Sign up for notifications about future opportunities.