Django models and endpoints for working with large images -- tile serving

Related tags

Djangodjango-large-image
Overview

Django Large Image

Models and endpoints for working with large images in Django -- specifically geared towards geospatial tile serving.

DISCLAIMER: this is a work in progress and is currently in an experimental phase.

  • 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)

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)
Comments
  • EPSG and its effect on COG and Tiles Opacity

    EPSG and its effect on COG and Tiles Opacity

    Great work with the library.

    I have an issue with opacity/clarity of tiles, thumbnails and overall Geotiffs/COGs as well as COGs not getting tiled.

    Opacity Issue: When using the swagger API to get a thumbnail of an existing COG, if I include "EPSG:3857" on the request, I get a washed out image

    image

    However, if I omit the EPSG Code, I get a clear image thumbnail. I have tested with multiple COGs and raw GeoTiffs image

    In Django Admin, the same Geotiffs and COGs are also washed out image

    I have also used a separate Leaflet html page to access the /api/maps/{id}/{z}/{x}/{y}.png and I get the same washed out images

    <html>
  <head>
    <meta name="viewport" content="initial-scale=1.0, user-scalable=no" />
    <meta charset="utf-8" />
    <style>
      html,
      body {
        height: 100%;
        margin: 0;
        padding: 0;
      }
      #map {
        height: 100%;
      }
    </style>
    <link
      rel="stylesheet"
      href="https://unpkg.com/[email protected]/dist/leaflet.css"
      integrity="sha512-hoalWLoI8r4UszCkZ5kL8vayOGVae1oxXe/2A4AO6J9+580uKHDO3JdHb7NzwwzK5xr/Fs0W40kiNHxM9vyTtQ=="
      crossorigin=""
    />
    <script
      src="https://unpkg.com/[email protected]/dist/leaflet.js"
      integrity="sha512-BB3hKbKWOc9Ez/TAwyWxNXeoV9c1v6FIeYiBieIWkpLjauysF18NzgR1MBNBXf8/KABdlkX68nAhlwcDFLGPCQ=="
      crossorigin=""
    ></script>
  </head>
  <body>
    <div id="map"></div>
    <script>
      var map = L.map("map").setView(
        [-0.24511062205544606, 34.87011481076246],
        16
      );
      L.tileLayer("https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png", {
        attribution:
          '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors',
        maxZoom: 18,
      }).addTo(map);
      L.tileLayer(
        "http://localhost:8000/api/maps/1/tiles/{z}/{x}/{y}.png?projection=EPSG%3A3857",
        {
          attribution:
            '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors',
          maxZoom: 23,
          opacity: 1,
        }
      ).addTo(map);

    </script>
  </body>
</html>
    image

    However, in the above example, if I do not append the EPSG code on the url in html, then I get an error (no map rendered) and a 400 bad request image

    As for individual tiles, if I include the EPSG Code in the request body in swagger UI, i get a washed out tile image

    However, if I omit the EPSG code, I get a bad request error image

    An example COG metadata is

    {
  "geospatial": true,
  "levels": 8,
  "sizeX": 32465,
  "sizeY": 28586,
  "sourceLevels": 8,
  "sourceSizeX": 32465,
  "sourceSizeY": 28586,
  "tileWidth": 256,
  "tileHeight": 256,
  "bounds": {
    "ll": {
      "x": 34.85392278135806,
      "y": -0.23501171685313998
    },
    "ul": {
      "x": 34.85392278135806,
      "y": -0.2273338589976692
    },
    "lr": {
      "x": 34.86258419062559,
      "y": -0.23501171685313998
    },
    "ur": {
      "x": 34.86258419062559,
      "y": -0.2273338589976692
    },
    "srs": "EPSG:4326",
    "xmin": 34.85392278135806,
    "xmax": 34.86258419062559,
    "ymin": -0.23501171685313998,
    "ymax": -0.2273338589976692
  },
  "sourceBounds": {
    "ll": {
      "x": 34.85392278135806,
      "y": -0.23501171685313998
    },
    "ul": {
      "x": 34.85392278135806,
      "y": -0.2273338589976692
    },
    "lr": {
      "x": 34.86258419062559,
      "y": -0.23501171685313998
    },
    "ur": {
      "x": 34.86258419062559,
      "y": -0.2273338589976692
    },
    "srs": "+proj=longlat +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +no_defs",
    "xmin": 34.85392278135806,
    "xmax": 34.86258419062559,
    "ymin": -0.23501171685313998,
    "ymax": -0.2273338589976692
  },
  "bands": {
    "1": {
      "min": 55,
      "max": 255,
      "mean": 193.05740298087738,
      "stdev": 72.13546456636203,
      "units": "metre",
      "interpretation": "red",
      "maskband": 4
    },
    "2": {
      "min": 63,
      "max": 255,
      "mean": 194.14802446569178,
      "stdev": 70.6158617103163,
      "units": "metre",
      "interpretation": "green",
      "maskband": 4
    },
    "3": {
      "min": 41,
      "max": 255,
      "mean": 182.4484673790776,
      "stdev": 84.39825325395805,
      "units": "metre",
      "interpretation": "blue",
      "maskband": 4
    },
    "4": {
      "min": 0,
      "max": 255,
      "mean": 109.17366774465692,
      "stdev": 126.17604981162934,
      "units": "metre",
      "interpretation": "alpha"
    }
  },
  "magnification": null,
  "mm_x": 2.969893339423529,
  "mm_y": 2.969893339423529,
  "proj4": [
    "+proj=longlat +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +no_defs"
  ],
  "frames": false
}
    bug 
    opened by geoffreynyaga 7
  • Add back Base64 styling support

    Add back Base64 styling support

    This reverts commit 3c74b7f37a5d91f68048fe5a907eedb2ead734f0.

    Take the following style object:

    {
    "bands": [
        {
            "frame": 0,
            "palette": "#ffffff"
        },
        {
            "frame": 1,
            "palette": "#ffffff"
        },
        {
            "frame": 2,
            "palette": "#ffffff"
        },
        {
            "frame": 3,
            "palette": "#ffffff"
        },
        {
            "frame": 4,
            "palette": "#ffffff"
        },
        {
            "frame": 5,
            "palette": "#ffffff"
        },
        {
            "frame": 6,
            "palette": "#ffffff"
        },
        {
            "frame": 7,
            "palette": "#ffffff"
        },
        {
            "frame": 8,
            "palette": "#ffffff"
        },
        {
            "frame": 9,
            "palette": "#ffffff"
        },
        {
            "frame": 10,
            "palette": "#ffffff"
        },
        {
            "frame": 11,
            "palette": "#ffffff"
        }
    ]
}

    Base64 encoding of this object is smaller than the URI encoded version (and is so in all similar examples I have tried)

    JSON Stringify (length 397):

    {"bands":[{"frame":0,"palette":"#ffffff"},{"frame":1,"palette":"#ffffff"},{"frame":2,"palette":"#ffffff"},{"frame":3,"palette":"#ffffff"},{"frame":4,"palette":"#ffffff"},{"frame":5,"palette":"#ffffff"},{"frame":6,"palette":"#ffffff"},{"frame":7,"palette":"#ffffff"},{"frame":8,"palette":"#ffffff"},{"frame":9,"palette":"#ffffff"},{"frame":10,"palette":"#ffffff"},{"frame":11,"palette":"#ffffff"}]}

    Base64 (length 532):

    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

    encodeURIComponent (length 721):

    %7B%22bands%22%3A%5B%7B%22frame%22%3A0%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A1%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A2%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A3%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A4%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A5%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A6%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A7%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A8%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A9%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A10%2C%22palette%22%3A%22%23ffffff%22%7D%2C%7B%22frame%22%3A11%2C%22palette%22%3A%22%23ffffff%22%7D%5D%7D

    If syles get more complex, they may quickly approach the common limit of 1024 characters for query strings. Having support for Base64 will give users a little more wiggle room to make sure their styles don't exceed limits set by their web server.

    Related: https://github.com/atlascope/atlascope/pull/139#pullrequestreview-946184928

    opened by banesullivan 2
  • Use django cache with large-image

    Use django cache with large-image

    requires https://github.com/girder/large_image/pull/876

    resolves #2

    To do:

    • [x] add some sort of test that will validate that large-image is really using the Django cache
    opened by banesullivan 1
  • Use custom format handler and regroup endpoints

    Use custom format handler and regroup endpoints

    Resolves #22

    ~This is still a work in progress as these changes highlight an issue in drf-yasg I need to fully document/capture~ not addressing this

    This introduces breaking changes to the API endpoints:

    Endpoints are now grouped into info, data, and tiles subgroups.

    swagger

    I could implement a deprecated version of the API, but considering we're still in the early days and most projects are pinning versions. This shouldn't matter too much and I will do the migration manually

    opened by banesullivan 1
  • Add specification of color to UI palette choice

    Add specification of color to UI palette choice

    The palette UI currently only allows for the selection of an MPL colormap - modify this to support hex colors (and/or everything large-image can support)

    opened by banesullivan 1
  • Can we embed warnings/error in tile response body?

    Can we embed warnings/error in tile response body?

    Sometimes we get warnings like:

    Tiff image is missing many lower resolution levels (3).  It will be inefficient to read lower resolution tiles.

    ref https://sentry.io/organizations/django-large-image/issues/3131476233/?project=6272210&query=is%3Aunresolved

    and in the future, we may warn if an image is not a properly tiled COG or pyramidal tiff (see #4).

    It would be great if we could embed these warnings in the tile and/or metadata endpoint responses. While in many cases, these warnings will go unnoticed, in some of our custom applications we can monitor these and even create handlers to provide a toast to the user that says something along the lines of "Performance warning: -insert warning-"

    opened by banesullivan 1
  • Performance issues

    Performance issues

    I'm seeing significant poor performance on the production demo. This could be due to the images not being proper COGs or something odd with how files are being checked out, causing requests to not be parallel

    opened by banesullivan 1
  • FileExistsError with os.symlink

    FileExistsError with os.symlink

    https://github.com/girder/django-large-image/blob/43c9ef62d83c4d6f33d3b49cc41f2c678f296584/django_large_image/utilities.py#L137

    FileExistsError: [Errno 17] File exists: '/home/geoff/LargeImage/media/data/test.tif' -> '/tmp/django-large-image/file_cache/ImageFile-1/test.tif'
    bug 
    opened by banesullivan 0
  • Add renderers and format extension handling

    Add renderers and format extension handling

    Can we add renderers (see details at bottom) and remove the duplicate _png, _jpeg, and _tif variants of many of the endpoints so that they are one endpoint that accepts different formats? I know this is possible, but I haven't been able to get it working with DRF 😕

    For example, we have the thumbnail endpoint split as two endpoints:

    • /image-file/{id}/thumbnail.png
    • /image-file/{id}/thumbnail.jpeg

    Can we combine these to: /image-file/{id}/thumbnail.{format}

    Thus reducing the method shims for these endpoints like

    https://github.com/girder/django-large-image/blob/09ef6e823d78de9a304cebbba453cb4a46b53ac2/django_large_image/rest/data.py#L38

    and

    https://github.com/girder/django-large-image/blob/09ef6e823d78de9a304cebbba453cb4a46b53ac2/django_large_image/rest/data.py#L48

    So that we are only using

    https://github.com/girder/django-large-image/blob/09ef6e823d78de9a304cebbba453cb4a46b53ac2/django_large_image/rest/data.py#L25

    with the format argument.

    So far I have been unsuccessful in getting this to work. What's annoying is that the default .json and .api "formats" work for these endpoints, but I cannot add any custom formats/renderers like .png, .jpeg, or .tif

    from rest_framework.renderers import BaseRenderer as RFBaseRenderer


class BaseRenderer(RFBaseRenderer):
    render_style = 'binary'
    charset = None

    def render(self, data, media_type=None, renderer_context=None):
        return data


class PNGRenderer(BaseRenderer):
    media_type = 'image/png'
    format = 'png'


class JPEGRenderer(BaseRenderer):
    media_type = 'image/jpeg'
    format = 'jpeg'


class JPGRenderer(BaseRenderer):
    media_type = 'image/jpeg'
    format = 'jpg'


image_renderers = [PNGRenderer, JPEGRenderer, JPGRenderer]


class TifRenderer(BaseRenderer):
    media_type = 'image/jpeg'
    format = 'tif'


class TiffRenderer(BaseRenderer):
    media_type = 'image/jpeg'
    format = 'tiff'


image_data_renderers = image_renderers + [TifRenderer, TiffRenderer]
    opened by banesullivan 0
  • Change VSI failed logging to warning

    Change VSI failed logging to warning

    https://github.com/ResonantGeoData/django-large-image/blob/87b6175cb08aff01367ff264815c5891fe9c5411/django_large_image/rest/core.py#L86

    This is showing up as an error on Sentry. I should change this to a warning and perhaps more gracefully handle it to ensure only GDAL is used with this - might come with #11

    opened by banesullivan 0
  • Style min/max value of

    Style min/max value of "" is not valid; using "auto"

    https://sentry.io/organizations/django-large-image/issues/3126500235/?project=6272210&query=is%3Aunresolved

    Fix handling of empty min/max values in query parameters to avoid this warning

    opened by banesullivan 0
  • Add COG validation endpoint

    Add COG validation endpoint

    Large-image's GDAL source has a validateCOG method which should be wrapped into an endpoint to validate if an image is a COG

    https://girder.github.io/large_image/_build/large_image_source_gdal/large_image_source_gdal.html#large_image_source_gdal.GDALFileTileSource.validateCOG

    This will not be available/valid for all tile sources, so we will need a clever way to limit it to GDAL sources and error out when not a GDAL source

    opened by banesullivan 0
  • Set min/max help text to value range

    Set min/max help text to value range

    The min/max fields in the UI do not show the min/max range for each band and it can be tough to decipher what the value range is.

    It would be great if we could do two things:

    • Set the help text to include the actual min/max values for the selected band
    • When initially hitting the up/down arrows, it is incremented from the actual min/max values

    Screen Shot 2022-07-28 at 10 40 22 AM

    opened by banesullivan 0
  • `frames` in `/info/metadata` but not in `/tiles/metadata`

    `frames` in `/info/metadata` but not in `/tiles/metadata`

    See https://github.com/atlascope/atlascope/pull/173#issuecomment-1163453575

    Need to make sure the tiles_metadata endpoint is using the metadata wrapper in the tilesource module and not grabbing that directly from large_image

    opened by banesullivan 0
Releases(0.8.0)

  • 0.8.0(Jun 17, 2022)

    New Features

    Notable

    • Major UI overhaul
      • Copy metadata button
      • Modern UI styling
      • Advanced multi-band compositing with custom colors
    • Connects large-image's caching mechanisms to utilize the Django cache framework
      • Specify the named cache as the LARGE_IMAGE_CACHE_NAME, otherwise uses the 'default' cache
    • New tiffdump endpoint utilizing tifftools to extract information from Tiff files
    • Support for URI encoded styles in request URL parameters (documented in README)
    • Improved internal mechanisms for opening tile sources for easier overrides downstream
      • User can specify the source class to use through the source URL parameter
    • Better format handing for endpoints that serve image data (single endpoint where PNG, JPEG, or TIFF are specified for the desired format)

    Additional

    • Support max_width and max_height specification for generating thumbnails
    • Improvements to SSR template overriding
    • mypy type annotations throughout API
    • New TileMetadataSerializer for the tiles/metadata endpoint
    • Improved API error handling
    • Better OpenAPI RESTful arguments documentation

    Demos

    • Standalone Docker image demo app: https://github.com/girder/django-large-image/pkgs/container/django-large-image-demo
    • Usage with django-raster: https://github.com/ResonantGeoData/django-raster-demo
    • Noted support for GeoDjango's GDALRaster in README
    • Document how to convert Pyramidal Tiffs (COGs) with Celery tasks

    Deprecations & Changes

    • internal_metadata -> metadata_internal
    • Metadata endpoints are now under the info/ prefix
      • e.g., metadata -> info/metadata
    • Data endpoints are now under the data/ prefix
      • e.g., thumbnail.png -> data/thumbnail.(?P<fmt>png|jpg|jpeg)
    Source code(tar.gz)
    Source code(zip)

  • 0.4.0(Apr 10, 2022)

    This release has breaking changes

    There are now 4 ViewSet mixin classes for use with both detail and non-detail viewsets in DRF.

    The following are the provided mixin classes and their use case:

    • LargeImageMixin: for use with a standard, non-detail ViewSet. Users must implement get_path()
    • LargeImageDetailMixin: for use with a detail viewset like GenericViewSet. Users must implement get_path()
    • LargeImageFileDetailMixin: (most commonly used) for use with a detail viewset like GenericViewSet where the associated model has a FileField storing the image data.
    • LargeImageVSIFileDetailMixin: (geospatial) for use with a detail viewset like GenericViewSet where the associated model has a FileField storing the image data that is intended to be read with GDAL. This will access the data over GDAL's Virtual File System interface (a VSI path).

    Most users will want to use LargeImageFileDetailMixin

    Other changes:

    • Style parameters can now be included as a JSON blob in the request body following the format specified by large-image
    • The thumbnail, tile, and region endpoints now each have .png, .jpeg, and .tif variants where appropriate
    • DRF ValidationErrors are raised for user-caused API errors (return 400 status on endpoint)
    • More usage examples
    Source code(tar.gz)
    Source code(zip)

  • 0.2.4(Apr 2, 2022)

    django-large-image is here to solve your image tile serving needs in Django! Take a look at the README for some example implementations and give it a try in your project with image data.

    Highlights

    • Easy to use mixin interface
    • Rich set of RESTful endpoints to extract information from large image formats
    • Serve image tiles in the slippy maps standard (z/x/y.png)
    • Produce thumbnails of large images on the fly
    • Works with FileField interfaces
    • Works with URL files (through GDAL's VFS/VSI layer)
    • Included viewer for admin interface or server-rendered templates
    • OpenAPI documentation included

    admin

    Source code(tar.gz)
    Source code(zip)
Owner
Resonant GeoData
Geospatial data cataloging with Django
Resonant GeoData
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Developer-friendly asynchrony for Django

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Bootstrap 4 integration with Django.

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A set of high-level abstractions for Django forms

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This is a basic Todo Application API using Django Rest Framework

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