Detect labels in an image by using the Cloud Vision API

This quickstart steps you through the process of:

  • Creating a Cloud Storage bucket.
  • Uploading your image to Cloud Storage and making it public.
  • Making a request to the Vision API with that image.

These steps should take about 5 minutes to complete. You can store up to 5GB of data in Cloud Storage for free and make up to 1000 feature requests to the Vision API for free per month.

Before you begin

If you haven't done so already, set up your project and create a Google Cloud Storage bucket, as explained below.

Set up your project

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Google Cloud project.

  4. Enable the Cloud Vision API.

    Enable the API

  5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  6. Make sure that billing is enabled for your Google Cloud project.

  7. Enable the Cloud Vision API.

    Enable the API

Create a Cloud Storage bucket

  1. In the Google Cloud console, go to the Cloud Storage Buckets page.

    Go to Buckets page

  2. Click Create bucket.
  3. On the Create a bucket page, enter your bucket information. To go to the next step, click Continue.
    • For Name your bucket, enter a unique bucket name. Don't include sensitive information in the bucket name, because the bucket namespace is global and publicly visible.
    • For Choose where to store your data, do the following:
      • Select a Location type option.
      • Select a Location option.
    • For Choose a default storage class for your data, select the following: Standard.
    • For Choose how to control access to objects, select an Access control option.
    • For Advanced settings (optional), specify an encryption method, a retention policy, or bucket labels.
  4. Click Create.

Make a request to the Cloud Vision API service

  1. Download demo-img.jpg. (You may need to right-click the link.)

  2. Open the Cloud Storage Buckets page.

  3. Select the bucket you created in the previous section.

  4. Click Upload Files and select the demo-img.jpg file to upload from your local machine to your Cloud Storage bucket.

    The Upload files button.
    This is the image file that you just uploaded:
    Two women biking in Jakarta.
    Image credit: Rohiim Ariful on Unsplash.

  5. After the file is uploaded and appears in the Cloud Storage bucket, share the image publicly.

  6. In the Try this method section, complete the interactive API Explorer template by replacing cloud-samples-data/vision in the image.source.imageUri field with the name of the Cloud Storage bucket where you uploaded the demo-img.jpg file. The request body should look like the following:

    {
      "requests": [
        {
          "features": [
            {
              "type": "LABEL_DETECTION"
            }
          ],
          "image": {
            "source": {
              "imageUri": "gs://cloud-samples-data/vision/demo-img.jpg"
            }
          }
        }
      ]
    }

  7. Click Execute to send the request to the service. The JSON response appears above.

Congratulations! You've made your first images.annotate request to the Cloud Vision API service.

Clean up

To avoid unnecessary Google Cloud Platform charges, use the Google Cloud console to delete your Cloud Storage bucket (and your project) if you do not need them.

What's next

  • See a list of all feature types and their uses.
  • Get started with the Vision API in your language of choice by using a Vision API Client Library.
  • Use the How-to guides to learn more about specific features, see example annotations, and get annotations for an individual file or image.
  • Learn about batch image and file (PDF/TIFF/GIF) annotation.
  • Browse through a comprehensive list of client library code samples.