add vignette
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Коммит
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^Meta$
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^doc$
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^misc$
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^\.vs$
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\.sln$
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Meta
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doc
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# History files
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.Rhistory
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.Rapp.history
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# Session Data files
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.RData
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# Example code in package build process
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*-Ex.R
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# Output files from R CMD build
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/*.tar.gz
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# Output files from R CMD check
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/*.Rcheck/
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# RStudio files
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.Rproj.user/
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# produced vignettes
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vignettes/*.html
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vignettes/*.pdf
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# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
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.httr-oauth
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# knitr and R markdown default cache directories
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/*_cache/
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/cache/
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# Temporary files created by R markdown
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*.utf8.md
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*.knit.md
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# Shiny token, see https://shiny.rstudio.com/articles/shinyapps.html
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rsconnect/
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misc/
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Package: AzureCognitive
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Title: Interface to Azure Cognitive Services
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Version: 0.1
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Version: 0.1.0
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Authors@R: c(
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person("Hong", "Ooi", , "hongooi@microsoft.com", role = c("aut", "cre")),
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person("Microsoft", role="cph")
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jsonlite,
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httr (>= 1.3),
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Suggests:
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knitr,
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testthat
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VignetteBuilder: knitr
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Roxygen: list(markdown=TRUE)
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RoxygenNote: 6.1.1
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@ -183,14 +183,6 @@ cognitive_error_message <- function(cont)
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}
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# kind - api
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# ComputerVision - vision/v2.0
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# Face - face/v1.0
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# LUIS - luis/v2.0
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# CustomVision.Training - customvision/v3.0
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# CustomVision.Prediction - customvision/v3.0
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# ContentModerator - contentmoderator/moderate/v1.0
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# Text - text/analytics/v2.0
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get_api_path <- function(type)
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{
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switch(type,
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A package to work with [Azure Cognitive Services](https://azure.microsoft.com/services/cognitive-services/). Both a Resource Manager interface and a client interface to the REST API are provided.
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The primary repo for this package is at https://github.com/Azure/AzureCognitive; please submit issues and PRs there. It is also mirrored at the Cloudyr org at https://github.com/cloudyr/AzureCognitive. You can install the development version of the package with `devtools::install_github("Azure/AzureCognitive")`.
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## Resource Manager interface
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AzureCognitive extends the class framework provided by [AzureRMR](https://github.com/Azure/AzureRMR) to support Cognitive Services. You can create, retrieve, update, and delete cognitive service resources by calling the corresponding methods for a resource group.
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---
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title: "Introduction to AzureCognitive"
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author: Hong Ooi
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output: rmarkdown::html_vignette
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vignette: >
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%\VignetteIndexEntry{Introduction}
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%\VignetteEngine{knitr::rmarkdown}
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%\VignetteEncoding{utf8}
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---
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AzureCognitive is a package for working with [Azure Cognitive Services](https://azure.microsoft.com/services/cognitive-services/). Both a Resource Manager interface and a client interface to the Cognitive Services REST API are provided. The aim is to provide a foundation that can be built on by other packages that will support specific services (Computer Vision, LUIS, etc).
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## Resource Manager interface
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AzureCognitive extends the class framework provided by [AzureRMR](https://github.com/Azure/AzureRMR) to support Cognitive Services. You can create, retrieve, update, and delete cognitive service resources by calling the corresponding methods for a resource group.
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```r
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az <- AzureRMR::get_azure_login()
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sub <- az$get_subscription("sub_id")
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rg <- sub$get_resource_group("rgname")
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# create a new Computer Vision service
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rg$create_cognitive_service("myvisionservice",
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service_type="ComputerVision", service_tier="S1")
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# retrieve it
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cogsvc <- rg$get_cognitive_service("myvisionservice")
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# list subscription keys
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cogsvc$list_keys()
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```
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## Client interface
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AzureCognitive implements basic functionality for communicating with the Cognitive Services REST API. The main functions are `cognitive_endpoint`, which creates an object representing the endpoint, and `call_cognitive_endpoint` to perform the REST calls.
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```r
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# getting the endpoint from the resource object
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endp <- cogsvc$get_endpoint()
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# or standalone (must provide subscription key or other means of authentication)
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endp <- cognitive_endpoint("https://myvisionservice.cognitiveservices.azure.com/",
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service_type="ComputerVision", key="key")
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# analyze an image
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img_link <- "https://news.microsoft.com/uploads/2014/09/billg1_print.jpg"
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call_cognitive_endpoint(endp,
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operation="analyze",
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body=list(url=img_link),
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options=list(details="celebrities"),
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http_verb="POST")
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```
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The latter call produces output like that below (truncated for brevity).
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```
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$categories
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$categories[[1]]
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$categories[[1]]$name
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[1] "people_"
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$categories[[1]]$score
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[1] 0.953125
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$categories[[1]]$detail
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$categories[[1]]$detail$celebrities
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$categories[[1]]$detail$celebrities[[1]]
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$categories[[1]]$detail$celebrities[[1]]$name
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[1] "Bill Gates"
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$categories[[1]]$detail$celebrities[[1]]$confidence
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[1] 0.9999552
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```
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