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Project description
Resonant GeoData Imagery
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 fromdjango-rgd
to configurelarge_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
Project details
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