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Showing content from https://github.com/cloudyr/RoogleVision below:

cloudyr/RoogleVision: R Package for Image Recognition using Google Cloud Vision

R Package for Image Recognition, Object Detection, and OCR using the Google's Cloud Vision API

See the the R/shiny demo

and blog posts 1 and 2

Visit Google's developer console
sign in
create a project, enable billing and enable 'Google Cloud Vision API'
go to credentials, create OAuth 2.0 client ID: copy client_id and client_secret from JSON file.

require("RoogleVision")

### plugin your credentials
options("googleAuthR.client_id" = "xxx.apps.googleusercontent.com")
options("googleAuthR.client_secret" = "")

## use the fantastic Google Auth R package
### define scope!
options("googleAuthR.scopes.selected" = c("https://www.googleapis.com/auth/cloud-platform"))
googleAuthR::gar_auth()

############
#Basic: you can provide both, local as well as online images:
o <- getGoogleVisionResponse("brandlogos.png")
o <- getGoogleVisionResponse(imagePath="brandlogos.png", feature="LOGO_DETECTION", numResults=4)
getGoogleVisionResponse("https://media-cdn.tripadvisor.com/media/photo-s/02/6b/c2/19/filename-48842881-jpg.jpg", feature="LANDMARK_DETECTION")


### FEATURES
# with the parameter 'feature' you can define which type of analysis you want. Results differ by feature-type
# The default is set to 'LABEL_DETECTION' but you can choose one out of: FACE_DETECTION, LANDMARK_DETECTION, LOGO_DETECTION, LABEL_DETECTION, TEXT_DETECTION

This package is not yet on CRAN. To install the latest development version you can install from the cloudyr drat repository:

# latest stable version
install.packages("RoogleVision", repos = c(getOption("repos"), "http://cloudyr.github.io/drat"))

Or, to pull a potentially unstable version directly from GitHub:

if (!require("devtools")) {
    install.packages("ghit")
}
devtools::install_github("cloudyr/RoogleVision")

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