index.md

copyright	lastupdated
years 2015, 2018	2018-07-31

{:shortdesc: .shortdesc} {:new_window: target="_blank"} {:tip: .tip} {:pre: .pre} {:codeblock: .codeblock} {:screen: .screen} {:curl: #curl .ph data-hd-programlang='curl'} {:javascript: .ph data-hd-programlang='javascript'} {:java: .ph data-hd-programlang='java'} {:python: .ph data-hd-programlang='python'} {:swift: .ph data-hd-programlang='swift'} {:download: .download}

Getting started tutorial

This tutorial guides you through how to use some built-in classifiers in {{site.data.keyword.visualrecognitionfull}} Dedicated to classify an image. {: shortdesc}

Before you begin

{: #prerequisites}

You create your service instance of the {{site.data.keyword.visualrecognitionshort}} Dedicated service through {{site.data.keyword.Bluemix}}, so you need a free {{site.data.keyword.Bluemix_dedicated_notm}} account to get started.

1. Log into your {{site.data.keyword.Bluemix_dedicated_notm}} account.

2. After you log in, create your service instance from the {{site.data.keyword.visualrecognitionshort}} {: new_window} page in the Catalog.

3. The API uses HTTP basic authentication. If you already know your credentials for the {{site.data.keyword.visualrecognitionshort}} service, skip this step. For details about how to find your service credentials, see Service credentials for Watson services {: new_window}.

   Note: Service credentials (username and password) are different from your {{site.data.keyword.Bluemix_dedicated_notm}} account username and password.

Step 1: Classify an image

{: #classify}

The endpoint used in this tutorial might not be your service endpoint. Check your endpoint URL on the Service credentials page in your instance of the {{site.data.keyword.visualrecognitionshort}} Dedicated service on {{site.data.keyword.Bluemix_dedicated_notm}}. {: tip}

1. Download the sample fruitbowl.jpg image.

2. Issue the following command to upload the image and classify it against the General model:

   • Replace {username} and {password} with the service credentials you copied earlier.
   • Modify the location of the images_file to point to where you saved the image.
   • Replace the https . . . endpoint with your endpoint URL

   curl -X POST -u "{username}:{password}" --form "[email protected]" \ "https://gateway.yourenvironment.watsonplatform.net/visual-recognition/api/v3/classify?version=2016-05-20"

   {: pre}

   The response includes the General model or classifier (which uses the default classifier_id), the classes identified in the image, and a score for each class.

   {
     "images": [
       {
         "classifiers": [
           {
             "classifier_id": "default",
             "name": "default",
             "classes": [
               {
                 "class": "banana",
                 "score": 0.562,
                 "type_hierarchy": "/fruit/banana"
               },
               {
                 "class": "fruit",
                 "score": 0.788
               },
               {
                 "class": "diet (food)",
                 "score": 0.528,
                 "type_hierarchy": "/food/diet (food)"
               },
               {
                 "class": "food",
                 "score": 0.528
               },
               {
                 "class": "honeydew",
                 "score": 0.5,
                 "type_hierarchy": "/fruit/melon/honeydew"
               },
               {
                 "class": "melon",
                 "score": 0.501
               },
               {
                 "class": "olive color",
                 "score": 0.973
               },
               {
                 "class": "lemon yellow color",
                 "score": 0.789
               }
             ]
           }
         ],
         "image": "fruitbowl.jpg"
       }
     ],
     "images_processed": 1,
     "custom_classes": 0
   }

   {: codeblock}

   Confidence scores are in the range of 0 to 1, with a higher score indicating greater correlation. By default, the /v3/classify calls don't include classes with a score below 0.5.

Next steps

You have a basic understanding of how to use the built-in default classifier with {{site.data.keyword.visualrecognitionshort}} Dedicated. Now dive deeper:

• Learn more about how to build a custom classifier.
• Read about the API in the API reference {: new_window}.

Attributions

{: #attributions}

• Fruit basket {: new_window} by Flikr user Ryan Edwards-Crewe {: new_window} used under Creative Commons Attribution 2.0 license {: new_window}. No changes were made to this image.