Vincent Sarago (vincentsarago)

vincentsarago

Geek Repo

Company:@developmentseed

Location:Bretagne

Home Page:https://remotepixel.ca

Github PK Tool:Github PK Tool


Organizations
cogeotiff
developmentseed
rasterio
RemotePixel
sat-utils
stac-utils
tilery

Vincent Sarago's repositories

lambda-tiler

AWS Lambda + rio-tiler to serve tiles from any web hosted files

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lambda-pyskel

Create skeleton of a python AWS Lambda function

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cog-translator

ecs-watchbot-fargate example to create a simple/self-managed processing pipeline using ECS Fargate.

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gdal-http2-benchmark

GDAL 2.4 and HTTP2 benchmark

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terrain-tiler

Create a `serverless` tile server for Amazon's Terrain Public Dataset

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lambda-proxy-cache

A lambda-proxy plugin to add a caching layer

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simple-rio-lambda

a simple Python 3.6 AWS Lambda function with Rasterio created with Docker

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landsat-footprint

Create Landsat8 footprint from data and metadata

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memcached-sasl

Memcached docker image with simple login:password authentication mechanisms

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alpine-rasterio

Light Alpine OS docker images for rasterio (python 3)

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benchmark-vrt-datatype

Checking if mask data is fetched for different GDAL datatype and 1 or 3 bands dataset.

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lambda-tiler-cache

Add a cache layer in lambda-tiler

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rio-tiler-experiment

preview of rio-tiler future

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benchmark-img-gdal

benchmark image (map tile) creation using Rasterio (GDAL) or Pillow

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mangum

AWS Lambda & API Gateway support for ASGI

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pytest-benchmark

py.test fixture for benchmarking code

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python-binary-memcached

A pure python module (thread safe) to access memcached via it's binary protocol with SASL auth support.

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python-vtzero

Experimental Cython wrapper around vtzero

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rio-glui

Explore CloudOptimized geotiff on your browser using Mapbox GL JS

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rio-pansharpen

pansharpening landsat scenes

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rio-rgbify

Encoded arbitrary bit depth rasters in psuedo base-256

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rio-tiler-bench

Benchmark rio-tiler and GDAL

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rio-tiler-glob

A custom tile server for dataset stored as band per file

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solaris

CosmiQ Works Geospatial Machine Learning Analysis Toolkit

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Start-MAJA

Start-MAJA is a basic orchestrator to process whole time series of Sentinel-2 L1C products for a given tile, using the MAJA L2A processor, which detects clouds and shadows and performs an atmospheric correction. Start-MAJA works on Linux systems

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