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	# Starter pipeline
	# Start with a minimal pipeline that you can customize to build and deploy your code.
	# Add steps that build, run tests, deploy, and more:
	# https://aka.ms/yaml

	variables:
	BuildConfiguration: Release
	FORCE_PUSH_NUGET: ${{ eq(variables['Build.SourceBranch'], 'refs/heads/develop') }}

	trigger:

	#!/bin/bash
	# Adicione um novo remote; pode chamá-lo de "upstream":

	git remote add upstream https://github.com/usuario/projeto.git

	# Obtenha todos os branches deste novo remote,
	# como o upstream/master por exemplo:

	git fetch upstream

	public static object GetValue(AttributeValue value) => GetString(value);

	private static object GetString(AttributeValue value) => !string.IsNullOrEmpty(value.S) ? value.S : GetNumber(value);

	private static object GetNumber(AttributeValue value) => !string.IsNullOrEmpty(value.N) ? value.N : GetObject(value);

	private static object GetObject(AttributeValue value)
	{
	if (value?.M?.Count > 0)
	{

	const float CONFIDENCE_LEVEL = 90;
	var count = 0;

	using(var source = new MemoryStream(image))
	{
	var request = new DetectFacesRequest { Image = new Image() { Bytes = source }, Attributes = new List<string> { "ALL" } };

	var response = await amazonRekognitionClient.DetectFacesAsync(request);

	foreach(var faceDetail in response.FaceDetails)

	foreach(var faceDetail in response.FaceDetails)
	{
	foreach(var emotion in faceDetail.Emotions)
	{
	if(emotion.Confidence > confidence) { Console.WriteLine($"this person may feel {emotion.Type}"); }
	}
	}

	var image1 = await File.ReadAllBytesAsync("path\\to\\source\\image");
	var image2 = await File.ReadAllBytesAsync("path\\to\\target\\image");

	const float SIMILARITY_THRESHOLD = 75;
	const float CONFIDENCE_LEVEL = 95;

	using(var source = new MemoryStream(image1))
	using(var target = new MemoryStream(image2))
	{
	var request = new CompareFacesRequest