Extract, Analyze, and Translate Text from Images with the Cloud ML APIs

Creating a Vision API request and calling the API with curl
Using the text detection (OCR) method of the Vision API
Using the Translation API to translate text from your image
Using the Natural Language API to analyze the text

1. Create an API key

Since you’ll be using curl to send a request to the Vision API, you’ll need to generate an API key to pass in your request URL.

To create an API key, navigate to: Navigation Menu > APIs & services > Credentials:

2. Upload an image to a Cloud Storage bucket

Creating a Cloud Storage bucket

There are two ways to send an image to the Vision API for image detection: by sending the API a base64 encoded image string, or passing it the URL of a file stored in Cloud Storage. For this lab you’ll create a Cloud Storage bucket to store your images.

Navigate to the Navigation menu > Cloud Storage browser in the Console.
Then click Create bucket.
Give your bucket a globally unique name and click on Choose how to control access to objects.
Uncheck the box for Enforce public access prevention on this bucket.
Choose Fine-grained under Access Control and click Create.

3. Create your Vision API request

student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ cat ocr-request.json
{
  "requests": [
      {
        "image": {
          "source": {
              "gcsImageUri": "gs://pradeep-gcp-cs/sign.jpg"
          }
        },
        "features": [
          {
            "type": "TEXT_DETECTION",
            "maxResults": 10
          }
        ]
      }
  ]
}
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$

4. Call the Vision API’s text detection method

curl -s -X POST -H "Content-Type: application/json" --data-binary @ocr-request.json  https://vision.googleapis.com/v1/images:annotate?key=${API_KEY}

student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ curl -s -X POST -H "Content-Type: application/json" --data-binary @ocr-request.json  https://vision.googleapis.com/v1/images:annotate?key=${API_KEY} -o ocr-response.json
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$

5. Sending text from the image to the Translation API

1_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ curl -s -X POST -H "Content-Type: application/json" --data-binary @ocr-request.json  https://vision.googleapis.com/v1/images:annotate?key=${API_KEY} -o ocr-response.json
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ vi translation-request.json
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ STR=$(jq .responses[0].textAnnotations[0].description ocr-response.json) && STR="${STR//\"}" && sed -i "s|your_text_here|$STR|g" translation-request.json
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ curl -s -X POST -H "Content-Type: application/json" --data-binary @translation-request.json https://translation.googleapis.com/language/translate/v2?key=${API_KEY} -o translation-response.json
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ cat translation-response.json
{
  "data": {
    "translations": [
      {
        "translatedText": "THE PUBLIC GOOD the dispatches For Obama, the mustard is from Dijon ATELINE",
        "detectedSourceLanguage": "fr"
      }
    ]
  }
}
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$

6. Analyzing the image’s text with the Natural Language API

student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ vi nl-request.json
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ STR=$(jq .data.translations[0].translatedText  translation-response.json) && STR="${STR//\"}" && sed -i "s|your_text_here|$STR|g" nl-request.json
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$ curl "https://language.googleapis.com/v1/documents:analyzeEntities?key=${API_KEY}" \
  -s -X POST -H "Content-Type: application/json" --data-binary @nl-request.json
{
  "entities": [
    {
      "name": "dispatches",
      "type": "OTHER",
      "metadata": {},
      "salience": 0.31229365,
      "mentions": [
        {
          "text": {
            "content": "dispatches",
            "beginOffset": 20
          },
          "type": "COMMON"
        }
      ]
    },
    {
      "name": "PUBLIC GOOD",
      "type": "OTHER",
      "metadata": {
        "mid": "/m/017bkk",
        "wikipedia_url": "https://en.wikipedia.org/wiki/Public_good_(economics)"
      },
      "salience": 0.27652362,
      "mentions": [
        {
          "text": {
            "content": "PUBLIC GOOD",
            "beginOffset": 4
          },
          "type": "PROPER"
        }
      ]
    },
    {
      "name": "Obama",
      "type": "PERSON",
      "metadata": {
        "mid": "/m/02mjmr",
        "wikipedia_url": "https://en.wikipedia.org/wiki/Barack_Obama"
      },
      "salience": 0.19338216,
      "mentions": [
        {
          "text": {
            "content": "Obama",
            "beginOffset": 35
          },
          "type": "PROPER"
        }
      ]
    },
    {
      "name": "mustard",
      "type": "OTHER",
      "metadata": {},
      "salience": 0.12168745,
      "mentions": [
        {
          "text": {
            "content": "mustard",
            "beginOffset": 46
          },
          "type": "COMMON"
        }
      ]
    },
    {
      "name": "Dijon ATELINE",
      "type": "OTHER",
      "metadata": {},
      "salience": 0.09611311,
      "mentions": [
        {
          "text": {
            "content": "Dijon ATELINE",
            "beginOffset": 62
          },
          "type": "PROPER"
        }
      ]
    }
  ],
  "language": "en"
}
student_01_c41e1c322859@cloudshell:~ (qwiklabs-gcp-04-ac2146a4cfe4)$