A Rasterio plugin to visualize Cloud Optimized GeoTIFF in browser.
You can install rio-viz using pip
$ pip install rio-viz
with 3d feature
# 3d visualization features is optional
$ pip install -U pip
$ pip install rio-viz["mvt"]
Build from source
$ git clone https://github.com/developmentseed/rio-viz.git
$ cd rio-viz
$ pip install -e .
$ rio viz --help
Usage: rio viz [OPTIONS] SRC_PATH
Rasterio Viz cli.
Options:
--nodata NUMBER|nan Set nodata masking values for input dataset.
--minzoom INTEGER Overwrite minzoom
--maxzoom INTEGER Overwrite maxzoom
--port INTEGER Webserver port (default: 8080)
--host TEXT Webserver host url (default: 127.0.0.1)
--no-check Ignore COG validation
--reader TEXT rio-tiler Reader (BaseReader or AsyncBaseReader). Default is `rio_tiler.io.COGReader`
--layers TEXT limit to specific layers (only used for MultiBand and MultiBase Readers). (e.g --layers b1 --layers b2).
--server-only Launch API without opening the rio-viz web-page.
--config NAME=VALUE GDAL configuration options.
--help Show this message and exit.
rio-viz support multiple/custom reader as long they are subclass of rio_tiler.io.base.BaseReader
or rio_tiler.io.base.AsyncBaseReader
.
# Multi Files as Bands
$ rio viz "cog_band{2,3,4}.tif" --reader rio_viz.io.MultiFilesBandsReader
# Simple Mosaic
$ rio viz "tests/fixtures/mosaic_cog{1,2}.tif" --reader rio_viz.io.MosaicReader
# MultiBandReader
# Landsat 8 - rio-tiler-pds
# We use `--layers` to limit the number of bands
$ rio viz LC08_L1TP_013031_20130930_20170308_01_T1 \
--reader rio_tiler_pds.landsat.aws.landsat8.L8Reader \
--layers B1,B2 \
--config GDAL_DISABLE_READDIR_ON_OPEN=FALSE \
--config CPL_VSIL_CURL_ALLOWED_EXTENSIONS=".TIF,.ovr"
# MultiBaseReader
# We use `--layers` to limit the number of assets
rio viz https://earth-search.aws.element84.com/v0/collections/sentinel-s2-l2a-cogs/items/S2A_34SGA_20200318_0_L2A \
--reader rio_tiler.io.STACReader \
--layers B04,B03,B02
# aiocogeo
$ rio viz https://naipblobs.blob.core.windows.net/naip/v002/al/2019/al_60cm_2019/30087/m_3008701_ne_16_060_20191115.tif \
--reader aiocogeo.tiler.COGTiler
When launching rio-viz, the application will create a FastAPI application to access and read the data you want. By default the CLI will open a web-page for you to explore your file but you can use --server-only
option to ignore this.
$ rio viz my.tif --server-only
# In another console
$ curl http://127.0.0.1:8080/info | jq
{
"bounds": [6.608576517072109, 51.270642883468895, 11.649386808679436, 53.89267160832534],
"band_metadata": [...],
"band_descriptions": [...],
"dtype": "uint8",
"nodata_type": "Mask",
"colorinterp": [
"red",
"green",
"blue"
]
}
You can see the full API documentation over http://127.0.0.1:8080/docs
rio-viz supports Mapbox VectorTiles encoding from a raster array. This feature was added to visualize sparse data stored as raster but will also work for dense array. This is highly experimental and might be slow to render in certain browser and/or for big rasters.
Ready to use docker image can be found on Github registry.
docker run \
--volume "$PWD":/data \
--platform linux/amd64 \
--rm -it -p 8080:8080 ghcr.io/developmentseed/rio-viz:latest \
rio viz --host 0.0.0.0 /data/your-file.tif
Notes:
--platform linux/amd64
is only needed if you are using latest MacOS M1 machines--volume "$PWD":/data
is needed to mount your local directory to the docker image- rio-viz's option
--host 0.0.0.0
is required to access the web server
See CONTRIBUTING.md
Created by Development Seed
See CHANGES.md.
See LICENSE.txt