12.2 azcv quick start
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We can immediately try some of the supported commands once the package has been configured. You do need to obtain an Azure Cognitive Services API key as setup with the configure command. You should then be able to copy any of the example commands below, and so paste them into a terminal and then run them on your Ubuntu command line. The examples are expanded upon through the following sections.
Identify the categorys of a photo of the Colosseum:
ml category azcv https://bit.ly/3lfNVG6
To identify landmarks within a photo of Singaporeβs Marina Bay Sands:
ml landmarks azcv https://bit.ly/3u3nwhW
To generate tags suitable for a photo of Australiaβs Uluru:
ml tags azcv https://bit.ly/3cqDonC
To identify any celebrities in an photo of faces:
ml celebrities azcv https://bit.ly/2OoC9xr
To identify the bounding boxes of objects within a photo of a skateboarder:
ml objects azcv https://bit.ly/3eFlaSe
To ocr handwritten text in a photo of a page:
ml ocr azcv https://bit.ly/2Op1qYk
To ocr a photo of street signs:
ml ocr azcv https://bit.ly/38F0FBj
To generate a thumbnail of a photo of Australiaβs Uluru:
ml thumbnail azcv https://bit.ly/3cqDonC
Identify any recognisable brands within a photo of a sweater:
ml brands azcv https://bit.ly/3qIKBo1
Identify the bounding boxes of faces within a photo:
ml faces azcv https://bit.ly/38GgwPP
What is the primary color within a photo:
ml color azcv https://bit.ly/3qHlAcY
The type of the image:
ml type azcv https://bit.ly/3bNGSBv
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