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Resonant GeoData Imagery

PyPI

A submodule of Resonant GeoData for storing imagery supporting annotations and spatial reference.

Installation

Follow the instructions for the core django-rgd app first, then

pip install --find-links https://girder.github.io/large_image_wheels django-rgd-imagery

Add this app to your INSTALLED_APPS along with the core RGD app:

INSTALLED_APPS += [
    'django.contrib.gis',
    'rgd',
    'rgd_imagery',
]

Configurations

The RGD imagery submodule has an optional setting:

  • RGD_STAC_BROWSER_LIMIT: (default of 1000) limit the response of STAC collection queries. An exception will be raised if a collection is requested with more than this many items.
  • Use the MEMCACHE_* options from django-rgd to configure large_image for use with Memcached.

Models

This app adds quite a few additional models on top of the core app for storing image data

Management Commands

  • rgd_imagery_demo: populate the database with example image data (image sets, annotations, rasters, etc.).
  • rgd_imagery_landsat_rgb_s3: populate the database with example raster data of the RGB bands of Landsat 8 imagery hosted on a public S3 bucket.

Notable Features

  • STAC Item ingest/export for raster imagery
  • Image tile serving through large_image
  • Image annotation support
  • KWCOCO image archive and annotation ingest
  • Cloud Optimized GeoTIFF conversion utility
  • Extract ROIs from imagery in pixel and world coordinates

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