Quickstart: Search for images using the Bing Image Search REST API and Python

Use this quickstart to learn how to send search requests to the Bing Image Search API. This Python application sends a search query to the API, and displays the URL of the first image in the results. Although this application is written in Python, the API is a RESTful web service compatible with most programming languages.

Prerequisites

• Python 2.x or 3.x
• The Python Imaging Library (PIL)
• matplotlib

Create and initialize the application

1. Create a new Python file in your favorite IDE or editor, and import the following modules. Create a variable for your subscription key, search endpoint, and search term. For search_url, you can use the global endpoint in the following code, or use the custom subdomain endpoint displayed in the Azure portal for your resource.

   import requests
   import matplotlib.pyplot as plt
   from PIL import Image
   from io import BytesIO
   
   subscription_key = "your-subscription-key"
   search_url = "https://api.cognitive.microsoft.com/bing/v7.0/images/search"
   search_term = "puppies"
   

2. Add your subscription key to the Ocp-Apim-Subscription-Key header by creating a dictionary, and adding the key as a value.

   headers = {"Ocp-Apim-Subscription-Key" : subscription_key}
   

Create and send a search request

1. Create a dictionary for the search request's parameters. Add your search term to the q parameter. Set the license parameter to public to search for images in the public domain. Set the imageType to photo to search only for photos.

   params  = {"q": search_term, "license": "public", "imageType": "photo"}
   

2. Use the requests library to call the Bing Image Search API. Add your header and parameters to the request, and return the response as a JSON object. Get the URLs to several thumbnail images from the response's thumbnailUrl field.

   response = requests.get(search_url, headers=headers, params=params)
   response.raise_for_status()
   search_results = response.json()
   thumbnail_urls = [img["thumbnailUrl"] for img in search_results["value"][:16]]
   

View the response

1. Create a new figure with four columns and four rows by using the matplotlib library.

2. Iterate through the figure's rows and columns, and use the PIL library's Image.open() method to add an image thumbnail to each space.

3. Use plt.show() to draw the figure and display the images.

   f, axes = plt.subplots(4, 4)
   for i in range(4):
       for j in range(4):
           image_data = requests.get(thumbnail_urls[i+4*j])
           image_data.raise_for_status()
           image = Image.open(BytesIO(image_data.content))        
           axes[i][j].imshow(image)
           axes[i][j].axis("off")
   plt.show()
   

Example JSON response

Responses from the Bing Image Search API are returned as JSON. This sample response has been truncated to show a single result.

{
"_type":"Images",
"instrumentation":{
    "_type":"ResponseInstrumentation"
},
"readLink":"images\/search?q=tropical ocean",
"webSearchUrl":"https:\/\/www.bing.com\/images\/search?q=tropical ocean&FORM=OIIARP",
"totalEstimatedMatches":842,
"nextOffset":47,
"value":[
    {
        "webSearchUrl":"https:\/\/www.bing.com\/images\/search?view=detailv2&FORM=OIIRPO&q=tropical+ocean&id=8607ACDACB243BDEA7E1EF78127DA931E680E3A5&simid=608027248313960152",
        "name":"My Life in the Ocean | The greatest WordPress.com site in ...",
        "thumbnailUrl":"https:\/\/tse3.mm.bing.net\/th?id=OIP.fmwSKKmKpmZtJiBDps1kLAHaEo&pid=Api",
        "datePublished":"2017-11-03T08:51:00.0000000Z",
        "contentUrl":"https:\/\/mylifeintheocean.files.wordpress.com\/2012\/11\/tropical-ocean-wallpaper-1920x12003.jpg",
        "hostPageUrl":"https:\/\/mylifeintheocean.wordpress.com\/",
        "contentSize":"897388 B",
        "encodingFormat":"jpeg",
        "hostPageDisplayUrl":"https:\/\/mylifeintheocean.wordpress.com",
        "width":1920,
        "height":1200,
        "thumbnail":{
        "width":474,
        "height":296
        },
        "imageInsightsToken":"ccid_fmwSKKmK*mid_8607ACDACB243BDEA7E1EF78127DA931E680E3A5*simid_608027248313960152*thid_OIP.fmwSKKmKpmZtJiBDps1kLAHaEo",
        "insightsMetadata":{
        "recipeSourcesCount":0,
        "bestRepresentativeQuery":{
            "text":"Tropical Beaches Desktop Wallpaper",
            "displayText":"Tropical Beaches Desktop Wallpaper",
            "webSearchUrl":"https:\/\/www.bing.com\/images\/search?q=Tropical+Beaches+Desktop+Wallpaper&id=8607ACDACB243BDEA7E1EF78127DA931E680E3A5&FORM=IDBQDM"
        },
        "pagesIncludingCount":115,
        "availableSizesCount":44
        },
        "imageId":"8607ACDACB243BDEA7E1EF78127DA931E680E3A5",
        "accentColor":"0050B2"
    }]
}

Next steps

• What is the Bing Image Search API?
• Pricing details for the Bing Search APIs
• Azure AI services documentation
• Bing Image Search API reference