Hugo Nicolau Barbosa de Gusmão hugonbgg

How small LLMs/AI Models Are Transforming Intelligent Systems

Understanding Small Models: How Compact AI Models Are Transforming Intelligent Systems
Strategic Applications: Where Small Models Excel
- 1. Input Processing and Enhancement
- 2. Privacy and Security Implementation
Domain-Specific Processing: Use Cases
- 1. Healthcare Domain
- 2. Legal Domain
3. Financial Services

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

	# install chromium, its driver, and selenium
	!apt update
	!apt install libu2f-udev libvulkan1
	!wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
	!dpkg -i google-chrome-stable_current_amd64.deb
	!wget https://edgedl.me.gvt1.com/edgedl/chrome/chrome-for-testing/118.0.5993.70/linux64/chromedriver-linux64.zip
	!unzip -j chromedriver-linux64.zip chromedriver-linux64/chromedriver -d /usr/local/bin/
	!pip install selenium chromedriver_autoinstaller

	# set options to be headless, ..

	<!DOCTYPE html>
	<html>
	<head>
	<meta charset='utf-8' />
	<title>Create a hover effect</title>
	<meta name='viewport' content='initial-scale=1,maximum-scale=1,user-scalable=no' />
	<script src='https://api.tiles.mapbox.com/mapbox-gl-js/v0.47.0/mapbox-gl.js'></script>
	<link href='https://api.tiles.mapbox.com/mapbox-gl-js/v0.47.0/mapbox-gl.css' rel='stylesheet' />
	<style>
	body { margin:0; padding:0; }

	/* This example is similar to the leaflet-layer-control.js example:
	* (https://gist.github.com/geog4046instructor/65f38124e3f56f11c9461b23335c0c92)
	* but this example only adds basemaps (tileLayer) to the control.
	*/

	// create a street map layer and add it to the map, making it the default basemap
	let streets = L.tileLayer( 'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png' ).addTo( map )

	// create a satellite imagery layer
	let satellite = L.tileLayer( 'https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}' )

	/*
	* This example shows how to add a layer list to a map where users can check and uncheck boxes to show and hide layers.
	* The code below is combined with the code to add geojson to a map, since those two things are often used together.
	* The code consists of five main parts:
	* 1. Create the basemap(s) and layer(s)
	* 2. Get geojson data and run a function to add it to a layer from step 1
	* 3. Create the function that will be run in step 2
	* 4. Create the list of layers that will appear in the control component
	* 5. Create the control component
	*/

	#!/usr/bin/env python3

	from io import BytesIO
	from os.path import abspath, dirname, join
	from zipfile import ZipFile

	from lxml.html import parse
	from requests import get

	baseurl = 'http://www1.caixa.gov.br/loterias/_arquivos/loterias/{product}'