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Detect labels in an image by using the command line

This page shows you how to send three feature detection and annotation requests to the Vision API using the REST interface and the curl command.

Vision API enables easy integration of Google vision recognition technologies into developer applications. You can send image data and desired feature types to the Vision API, which then returns a corresponding response based on the image attributes you are interested in. For more information about the feature types offered, see the List of all Vision API features.

Before you begin

  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. Install and initialize the Google Cloud CLI.
  3. Create or select a Google Cloud project.

    • Create a Cloud project:

      gcloud projects create PROJECT_ID
    • Select the Cloud project that you created:

      gcloud config set project PROJECT_ID
  4. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

  5. Enable the Vision API:

    gcloud services enable vision.googleapis.com
  6. Grant roles to your Google Account. Run the following command once for each of the following IAM roles: roles/storage.objectViewer

    gcloud projects add-iam-policy-binding PROJECT_ID --member="user:EMAIL_ADDRESS" --role=ROLE
    • Replace PROJECT_ID with your project ID.
    • Replace EMAIL_ADDRESS with your email address.
    • Replace ROLE with each individual role.
  7. Install and initialize the Google Cloud CLI.
  8. Create or select a Google Cloud project.

    • Create a Cloud project:

      gcloud projects create PROJECT_ID
    • Select the Cloud project that you created:

      gcloud config set project PROJECT_ID
  9. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

  10. Enable the Vision API:

    gcloud services enable vision.googleapis.com
  11. Grant roles to your Google Account. Run the following command once for each of the following IAM roles: roles/storage.objectViewer

    gcloud projects add-iam-policy-binding PROJECT_ID --member="user:EMAIL_ADDRESS" --role=ROLE
    • Replace PROJECT_ID with your project ID.
    • Replace EMAIL_ADDRESS with your email address.
    • Replace ROLE with each individual role.

Make an image annotation request

After completing the Before you begin steps you can use the Vision API to annotate an image file.

In this example you use curl to send a request to the Vision API using the following image:

Cloud Storage URI:

gs://cloud-samples-data/vision/using_curl/shanghai.jpeg

HTTPS URL:

https://console.cloud.google.com/storage/browser/cloud-samples-data/vision/using_curl/shanghai.jpeg

Shanghai street image.
Image credit: Steve Long on Unsplash.

Create the request JSON

The following request.json file demonstrates how to request three images:annotate features and limit the results in the response.

Create the JSON request file with the following text, and save it as a request.json plain text file in your working directory:

request.json

{
  "requests": [
    {
      "image": {
        "source": {
          "imageUri": "gs://cloud-samples-data/vision/using_curl/shanghai.jpeg"
        }
      },
      "features": [
        {
          "type": "LABEL_DETECTION",
          "maxResults": 3
        },
        {
          "type": "OBJECT_LOCALIZATION",
          "maxResults": 1
        },
        {
          "type": "TEXT_DETECTION",
          "maxResults": 1,
          "model": "builtin/latest"
        }
      ]
    }
  ]
}

Send the request

You use curl and the body content from request.json to send the request to the Vision API. Enter the following on your command line:

curl -X POST \
    -H "Authorization: Bearer "$(gcloud auth print-access-token) \
    -H "Content-Type: application/json; charset=utf-8" \
    https://vision.googleapis.com/v1/images:annotate -d @request.json

Interpret the response

You should see a JSON response similar to the one below.

The request JSON body specified maxResults for each annotation type. Consequently, you will see the following in the response JSON:

Label detection results

  1. description: "People", score: 0.950
  2. description: "Street", score: 0.891
  3. description: "Mode of transport", score: 0.890
Shanghai street image containing label detection results.
Image credit: Steve Long on Unsplash (annotations added).

Text detection results

  • text: 牛牛面馆\n
  • vertices: (x: 159, y: 212), (x: 947, y: 212), (x: 947, y: 354), (x: 159, y: 354 )
Shanghai street image containing text detection results.
Image credit: Steve Long on Unsplash (annotations added).

Object detection results

  • name: "Person", score: 0.944
  • normalized vertices: (x: 0.260, y: 0.468), (x: 0.407, y: 0.468), (x: 0.407, y: 0.895), (x: 0.260, y: 0.895)
Shanghai street image containing object detection results.
Image credit: Steve Long on Unsplash (annotations added).

Congratulations! You've sent your first request to the Vision API.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, delete the Cloud project with the resources.

Optional: Revoke credentials from the gcloud CLI.

gcloud auth revoke

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.
  • Browse more specific use cases on the community tutorials page.