Garret glw

## geo_interface.rst

      
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                sgillies
                / geo_interface.rst
            
            
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                A Python Protocol for Geospatial Data
              
          
    Author: Sean Gillies Version: 1.0
Abstract

This document describes a GeoJSON-like protocol for geo-spatial (GIS) vector data.
Introduction


## installation.md

      
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                hallahan
                / installation.md
            
            
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                SpatialServer Installation Instructions
              
          
    Preliminary Packages

Make sure you have done sudo apt-get update and sudo apt-get upgrade on your fresh install. This guide is geared toward Ubuntu 14.04 LTS (Trusty Tahr). Most of the guide will work for earlier versions of Ubuntu with some slight changes, but 14.04 is advised.
Enable the root user

sudo cp /home/ubuntu/.ssh/authorized_keys /root/.ssh/

  
## Lidar_walkthrough.md

      
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                YKCzoli
                / Lidar_walkthrough.md
            
            
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                Lidar_walkthrough
              
          
    Processing LiDAR to extract building heights

Walk through

Detailed walk through of building extraction using postgis
First lets pull a data layer from of openstreetmap. You can do this any which way you’d like, as there are a variety of methods for pulling openstreetmap data from their database. Check the [wiki] (http://wiki.openstreetmap.org/wiki/Downloading_data) for a comprehensive list. My favourite method thus far is pulling the data straight into QGIS using the open layers plugin. For those who may want to explore this method, check [this tutorial] (http://www.qgistutorials.com/en/docs/downloading_osm_data.html). For building extraction you only need building footprints, and include the building tags. Not all polygons are of type building in OSM, so we can download all the polygons, and then filter the layer for only polygons tagged as buildings.
LiDAR data was pulled from USGS via the Earth Explorer site.
[Here] (http://earthobservatory.nasa.gov/blogs/ele

  
## README.md

      
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                clhenrick
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                PostgreSQL & PostGIS cheatsheet (a work in progress)
              
          
    PostgreSQL & PostGIS Cheatsheet

This is a collection of information on PostgreSQL and PostGIS for what I tend to use most often.
TOC


Installing Postgres & PostGIS
Using Postgres on the command line: PSQL
Importing Data into Postgres
Exporting Data from Postgres
Joining Tables


## postgisOSM-LAS.md

      
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                patriciogonzalezvivo
                / postgisOSM-LAS.md
            
            
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                Loading OSM and LIDar to PostGIS 
              
          
    This tutorial is partialy based on Yuriy’s Czoli article ‘Processing LiDAR to extract building heights’.
Install PostGIS

On Mac OSX


Install Postgres, PostGIS and OSM-PostGIS tools

brew install postgis 


## index.html

<!DOCTYPE html>
<html>
<head>
<meta charset=utf-8 />
<title>WaterHex</title>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no' />
<script src='https://api.tiles.mapbox.com/mapbox.js/v1.6.2/mapbox.js'></script>
<link href='https://www.mapbox.com/base/latest/base.css' rel='stylesheet' />
<link href='https://api.tiles.mapbox.com/mapbox.js/v1.6.2/mapbox.css' rel='stylesheet' />

## .block
license: mit

## dlib and face_recognition on raspberry pi.md

      
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                ageitgey
                / dlib and face_recognition on raspberry pi.md
            
            
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              April 17, 2024 17:40
            
          
    Install dlib and face_recognition on a Raspberry Pi

Instructions tested with a Raspberry Pi 2 with an 8GB memory card. Probably also works fine on a Raspberry Pi 3.
Steps

Download the latest Raspbian Jessie Light image. Earlier versions of Raspbian won't work.
Write it to a memory card using Etcher, put the memory card in the RPi and boot it up.

  
## graphql_example.py
# An example to get the remaining rate limit using the Github GraphQL API.

import requests

headers = {"Authorization": "Bearer YOUR API KEY"}


def run_query(query): # A simple function to use requests.post to make the API call. Note the json= section.
    request = requests.post('https://api.github.com/graphql', json={'query': query}, headers=headers)
    if request.status_code == 200:

## boto3_digitalocean.py
import logging
import urllib.request
import boto3
from settings import OBJECT_STORAGE_KEY, OBJECT_STORAGE_SECRET, OBJECT_STORAGE_REGION, OBJECT_STORAGE_BUCKET

logger = logging.getLogger(__name__)

s3config = {
    "region_name": OBJECT_STORAGE_REGION,
    "endpoint_url": "https://{}.digitaloceanspaces.com".format(OBJECT_STORAGE_REGION),

	<!DOCTYPE html>
	<html>
	<head>
	<meta charset=utf-8 />
	<title>WaterHex</title>
	<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no' />
	<script src='https://api.tiles.mapbox.com/mapbox.js/v1.6.2/mapbox.js'></script>
	<link href='https://www.mapbox.com/base/latest/base.css' rel='stylesheet' />
	<link href='https://api.tiles.mapbox.com/mapbox.js/v1.6.2/mapbox.css' rel='stylesheet' />
	# An example to get the remaining rate limit using the Github GraphQL API.

	import requests

	headers = {"Authorization": "Bearer YOUR API KEY"}


	def run_query(query): # A simple function to use requests.post to make the API call. Note the json= section.
	request = requests.post('https://api.github.com/graphql', json={'query': query}, headers=headers)
	if request.status_code == 200:
	import logging
	import urllib.request
	import boto3
	from settings import OBJECT_STORAGE_KEY, OBJECT_STORAGE_SECRET, OBJECT_STORAGE_REGION, OBJECT_STORAGE_BUCKET

	logger = logging.getLogger(__name__)

	s3config = {
	"region_name": OBJECT_STORAGE_REGION,
	"endpoint_url": "https://{}.digitaloceanspaces.com".format(OBJECT_STORAGE_REGION),