Need to visualize a rather large (gigabytes+) raster? This is for you.
Try it out below!
from localtileserver import get_leaflet_tile_layer, examples from ipyleaflet import Map # Create a TileClient from a raster file # client = TileClient('path/to/geo.tif') client = examples.get_san_francisco() # use example data # Create ipyleaflet TileLayer from that server t = get_leaflet_tile_layer(client) # Create ipyleaflet map, add tile layer, and display m = Map(center=client.center(), zoom=client.default_zoom) m.add_layer(t) m
A Python package for serving tiles from large raster files in
the Slippy Maps standard
(i.e., /zoom/x/y.png) for visualization in Jupyter with
Launch a demo on MyBinder
Under the hood, this is also a Flask blueprint/application for use as a standalone web app or in your own web deployments needing dynamic tile serving.
Launch a tile server for large geospatial images
View local or remote* raster files with
View rasters with CesiumJS with the built-in Flask web application
Extract regions of interest (ROIs) interactively
Use the example datasets to generate Digital Elevation Models
remote raster files should be pre-tiled Cloud Optimized GeoTiffs
TileClient class can be used to to launch a tile server in a background
thread which will serve raster imagery to a viewer (see
folium examples in 🚀 User Guide).
This tile server can efficiently deliver varying resolutions of your raster imagery to your viewer; it helps to have pre-tiled, Cloud Optimized GeoTIFFs (COG), but no wories if not as the backing library, large_image, will tile and cache for you when opening the raster.
🪢 Community Usage#
streamlit-geospatial: uses localtileserver’s flask-based remote tile server for viewing image tiles
remotetileserver: uses the core flask application to spin up a production ready tile server
Kaustav Mukherjee’s blog post: a user-created demonstration on how to get started with localtileserver