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analyze-image.rb

analyze-image.rb

 
 

readme.md

readme.md

 
 

readme.md

Quickstart: Analyze a remote image using the REST API and Ruby in Computer Vision

In this quickstart, you analyze a remotely stored image to extract visual features by using Computer Vision's REST API. With the Analyze Image method, you can extract visual features based on image content.

If you don't have an Azure subscription, create a free account before you begin.

Prerequisites

Create and run the sample

To create and run the sample, do the following steps:

  1. Copy the following code into a text editor.
  2. Make the following changes in code where needed:
    1. Replace <key> with your key.
    2. Replace https://westcentralus.api.cognitive.microsoft.com/vision/v2.0/analyze with the endpoint URL for the Analyze Image method in the Azure region where you obtained your keys, if necessary.
    3. Optionally, replace the value of the language request parameter with a different language.
    4. Optionally, replace http://upload.wikimedia.org/wikipedia/commons/3/3c/Shaki_waterfall.jpg\ with the URL of a different image that you want to analyze.
  3. Save the code as a file with an .rb extension. For example, analyze-image.rb.
  4. Open a command prompt window.
  5. At the prompt, use the ruby command to run the sample. For example, ruby analyze-image.rb.
require 'net/http'

# You must use the same location in your REST call as you used to get your
# keys. For example, if you got your keys from westus,
# replace "westcentralus" in the URL below with "westus".
uri = URI('https://westcentralus.api.cognitive.microsoft.com/vision/v2.0/analyze')
uri.query = URI.encode_www_form({
    # Request parameters
    'visualFeatures' => 'Categories, Description',
    'details' => 'Landmarks',
    'language' => 'en'
})

request = Net::HTTP::Post.new(uri.request_uri)

# Request headers
# Replace <key> with your valid key.
request['Ocp-Apim-Subscription-Key'] = '<key>'
request['Content-Type'] = 'application/json'

request.body =
    "{\"url\": \"http://upload.wikimedia.org/wikipedia/commons/3/3c/Shaki_waterfall.jpg\"}"

response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
    http.request(request)
end

puts response.body

Examine the response

A successful response is returned in JSON. The sample parses and displays a successful response in the command prompt window, similar to the following example:

{
  "categories": [
    {
      "name": "abstract_",
      "score": 0.00390625
    },
    {
      "name": "people_",
      "score": 0.83984375,
      "detail": {
        "celebrities": [
          {
            "name": "Satya Nadella",
            "faceRectangle": {
              "left": 597,
              "top": 162,
              "width": 248,
              "height": 248
            },
            "confidence": 0.999028444
          }
        ]
      }
    }
  ],
  "adult": {
    "isAdultContent": false,
    "isRacyContent": false,
    "adultScore": 0.0934349000453949,
    "racyScore": 0.068613491952419281
  },
  "tags": [
    {
      "name": "person",
      "confidence": 0.98979085683822632
    },
    {
      "name": "man",
      "confidence": 0.94493889808654785
    },
    {
      "name": "outdoor",
      "confidence": 0.938492476940155
    },
    {
      "name": "window",
      "confidence": 0.89513939619064331
    }
  ],
  "description": {
    "tags": [
      "person",
      "man",
      "outdoor",
      "window",
      "glasses"
    ],
    "captions": [
      {
        "text": "Satya Nadella sitting on a bench",
        "confidence": 0.48293603002174407
      }
    ]
  },
  "requestId": "0dbec5ad-a3d3-4f7e-96b4-dfd57efe967d",
  "metadata": {
    "width": 1500,
    "height": 1000,
    "format": "Jpeg"
  },
  "faces": [
    {
      "age": 44,
      "gender": "Male",
      "faceRectangle": {
        "left": 593,
        "top": 160,
        "width": 250,
        "height": 250
      }
    }
  ],
  "color": {
    "dominantColorForeground": "Brown",
    "dominantColorBackground": "Brown",
    "dominantColors": [
      "Brown",
      "Black"
    ],
    "accentColor": "873B59",
    "isBWImg": false
  },
  "imageType": {
    "clipArtType": 0,
    "lineDrawingType": 0
  }
}