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Project description
django-large-image
Created by Kitware, Inc.
django-large-image
is an abstraction of large-image
for use with django-rest-framework
providing view mixins for endpoints to
work with large images in Django -- specifically geared towards geospatial and
medical image tile serving.
DISCLAIMER: this is a work in progress and is currently in an experimental phase.
RGB Raster | Colormapped Raster Band |
---|---|
Swagger Documentation | Tiles Endpoint |
---|---|
Overview
This package ports Kitware's large-image to Django by providing a set of abstract, mixin API view classes that will handle tile serving, fetching metadata from images, and extracting regions of interest.
django-large-image
is an optionally installable Django app with
a few classes that can be mixed into a Django project (or application)'s
drf-based views to provide tile serving endpoints out of the box. Notably,
django-large-image
is designed to work specifically with FileFeild
interfaces with development being tailored to Kitware's
S3FileField
. We are working
to also support GeoDjango's GDALRaster
in the future
This package ships with pre-made HTML templates for rendering geospatial image tiles with CesiumJS and non-geospatial image tiles with GeoJS.
Features
Rich set of RESTful endpoints to extract information from large image formats:
- Image metadata (
/metadata
,/internal_metadata
) - Tile serving (
/tiles/{z}/{x}/{y}.png?projection=EPSG:3857
) - Region extraction (
/region.tif?left=v&right=v&top=v&bottom=v
) - Image thumbnails (
/thumbnail
) - Individual pixels (
/pixel?left=v&top=v
) - Band histograms (
/histogram
)
Support for general FileFeild's or File URLs
- Supports django's FileFeild
- Supports
S3FileField
- Supports GDAL's Virtual File System for
s3://
,ftp://
, etc. URLs
Miscellaneous:
- caching - tile sources are cached for rapid file re-opening
- tiles and thumbnails are cached to prevent recreating these data on multiple requests
- Easily extensible SSR templates for tile viewing with CesiumJS and GeoJS
- OpenAPI documentation in swagger
Installation
Out of the box, django-large-image
only depends of the core large-image
module, but you will need a large-image-source-*
module in order for this
to work. Most of our users probably want to work with geospatial images so we
will focus on the large-image-source-gdal
case, but it is worth noting that
large-image
has source modules for a wide variety of image formats
(e.g., medical image formats for microscopy).
See large-image
's
installation instructions for more details.
Tip: installing GDAL is notoriously difficult, so at Kitware we provide
pre-built Python wheels with the GDAL binary bundled for easily installation in
production environments. To install our GDAL wheel, use: pip install --find-links https://girder.github.io/large_image_wheels GDAL
pip install \
--find-links https://girder.github.io/large_image_wheels \
django-large-image \
large-image-source-gdal
Usage
Simply import and mixin the LargeImageView
class to your existing
django-rest-framework
viewsets and specify the FILE_FIELD_NAME
as the
string name of the FileField
in which your image data are saved.
from django_large_image.rest import LargeImageView
class MyModelViewset(viewsets.GenericViewSet, LargeImageView):
... # configuration for your model's viewset
FILE_FIELD_NAME = 'field_name'
And that's it!
Example Code
To use the mixin classes provided here, create a model, serializer, and view in your Django project like so:
models.py
---
from django.db import models
from rest_framework import serializers
class ImageFile(models.Model):
name = models.TextField()
file = models.FileField()
class ImageFileSerializer(serializers.ModelSerializer):
class Meta:
model = ImageFile
fields = '__all__'
admin.py
---
from django.contrib import admin
from example.core.models import ImageFile
@admin.register(ImageFile)
class ImageFileAdmin(admin.ModelAdmin):
list_display = ('pk', 'name')
Then create the viewset, mixing in the django-large-image
view class:
viewsets.py
---
from example.core import models
from rest_framework import mixins, viewsets
from django_large_image.rest import LargeImageView
class ImageFileDetailView(
mixins.ListModelMixin,
viewsets.GenericViewSet,
LargeImageView,
):
queryset = models.ImageFile.objects.all()
serializer_class = models.ImageFileSerializer
# for `django-large-image`: the name of the image FileField on your model
FILE_FIELD_NAME = 'file'
Then register the URLs:
urls.py
---
from django.urls import path
from example.core.viewsets import ImageFileDetailView
from rest_framework.routers import SimpleRouter
router = SimpleRouter(trailing_slash=False)
router.register(r'api/large-image', ImageFileDetailView, basename='image-file')
urlpatterns = [
path('', include('django_large_image.urls')), # Some additional diagnostic URLs from django-large-image
] + router.urls
Please note the example Django project in the project/
directory of this
repository that shows how to use django-large-image
.
Work Plan
Our primary goal is to get through phases 1 and 2, focusing on tile serving of large geospatial images specifically in Cloud Optimized GeoTiff (COG) format.
Phase 1
- Abstract API View classes that can be mixed-in downstream to expose all available endpoints
- endpoints for metadata (/tiles, /tiles/internal_metadata)
- endpoints for serving tiles (/tiles/zxy, /tiles/fzxy)
- cache management - tile sources should be cached so that we don't open a file for each tile
- endpoint for regions
- endpoint for thumbnails
- thumbnail caching
- endpoint for individual pixels
- endpoint for histograms
- some diagnostic and settings endpoints (list available sources, set whether to automatically use large_images and the size of small images that can be used)
- Support for django's FileFeild
- Support for S3FileField
- Ship an easily extensible SSR template for tile viewing with CesiumJS
- Support for using file URLs with GDAL's VSI
- Provide OpenAPI documentation in swagger
Phase 2
- Handle band/component selection styling for tile serving and thumbnails
- e.g., use channels 3,7,5 for Red Green Blue
- endable linear/discrete color modes
- Tie large-image's caching into Django's cache (might require upstream work in large-image)
- Provide some sort of endpoint to check if an image is a valid COG
- Create a secondary app with celery tasks for converting images to COG
- Refactor/prototpye RGD's ChecksumFile model as a FieldFile subclass
- Support GeoDjango's
GDALRaster
Phase 3 and onward
Incorporate more features from large-image.
Things that would require implementing tasks with celery:
- ability to convert images via large_image_converter
- async endpoint for regions
Things I'm unsure about:
- endpoints for associated images
- ability to precache thumbnails (the thumbnail jobs endpoints)
- endpoints for serving tiles in deepzoom format
Things I think should be implemented downstream:
- endpoint or method to make / unmake a Django file field into a large_image item
- fuse-like ability to access filefields as os-level files (until implemented, s3 files will need to be pulled locally to serve them, which is inefficient)
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