SatelliteFootprintDetection

April 18, 2022 · View on GitHub

This Project's aim is Footprint Detection of Buildings in High-Resolution Satellite Images by using instance segmentation.

Dataset Characteristics:

  • This open-source dataset includes 24 images (one per month) covering ~100 unique geographies. 
  • The dataset will comprise over 40,000 square kilometers of imagery and exhaustive polygon labels of building footprints in the imagery, totaling over 10 million individual annotations. 
  • The Data – ~100 locations, spread out across the globe and contains:

Dataset :

  • The Dataset is available for download on kaggle

  • The Dataset is available for download on AWS as a Public Dataset:

    Training Data

    • aws s3 cp s3://spacenet-dataset/spacenet/SN7_buildings/tarballs/SN7_buildings_train.tar.gz .
    • aws s3 cp s3://spacenet-dataset/spacenet/SN7_buildings/tarballs/SN7_buildings_train_csvs.tar.gz .

    Testing Data

    • aws s3 cp s3://spacenet-dataset/spacenet/SN7_buildings/tarballs/SN7_buildings_test_public.tar.gz . Align center:

Models:

The Models trained are stored in GoogleDrive

BLOG POST:

The Whole Project is documented in this Blog Post

Results

https://user-images.githubusercontent.com/44031169/159185584-08eb5679-e7ee-4c3c-b651-2639b851123e.mp4

IMAGE ALT TEXT HERE

Installation:


GIT:

.. code-block:: bash

  git clone https://github.com/PriyanK7n/SatFootprint
  cd SatFootprint
  pip install -r requirements.txt
  pip install -e .