Describe images with human-readable language

Computer Vision can analyze an image and generate a human-readable sentence that describes its contents. The algorithm actually returns several descriptions based on different visual features, and each description is given a confidence score. The final output is a list of descriptions ordered from highest to lowest confidence.

Image description example

The following JSON response illustrates what Computer Vision returns when describing the example image based on its visual features.

A black and white picture of buildings in Manhattan

    "description": {
        "tags": ["outdoor", "building", "photo", "city", "white", "black", "large", "sitting", "old", "water", "skyscraper", "many", "boat", "river", "group", "street", "people", "field", "tall", "bird", "standing"],
        "captions": [
                "text": "a black and white photo of a city",
                "confidence": 0.95301952483304808
                "text": "a black and white photo of a large city",
                "confidence": 0.94085190563213816
                "text": "a large white building in a city",
                "confidence": 0.93108362931954824
    "requestId": "b20bfc83-fb25-4b8d-a3f8-b2a1f084b159",
    "metadata": {
        "height": 300,
        "width": 239,
        "format": "Jpeg"

Use the API

The image description feature is part of the Analyze Image API. You can call this API through a native SDK or through REST calls. Include Description in the visualFeatures query parameter. Then, when you get the full JSON response, simply parse the string for the contents of the "description" section.

Next steps

Learn the related concepts of tagging images and categorizing images.