12.2 azcv quick start


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 Singapore’s Marina Bay Sands:

ml landmarks azcv https://bit.ly/3u3nwhW

To generate tags suitable for a photo of Australia’s 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 Australia’s 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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