Novice Level

Powering Google Cloud APIs with Cloud Functions

Pricing
30 minutes
  • 8 Learning Objectives

About this Hands-on Lab

One of the most powerful aspects of the Cloud Functions service is its flexibility while working with other Google Cloud services, including some of the most advanced APIs. Not only can your function be triggered by multiple sources, you can include multiple functions all in the app. This lab illustrates a perfect example of that flexibility. Here, we will take a photo that has been uploaded, examine it for text, extract any text that is found, translate that text into various languages, and then store those translations for easy retrieval. Sounds like a lot, doesn’t it? Well, as we’ll experience firsthand in this lab, Cloud Functions can handle it all.

Learning Objectives

Successfully complete this lab by achieving the following learning objectives:

Enable APIs and services.
  1. From the main Google Cloud console navigation, choose APIs & Services > Library.
  2. Search for Cloud Functions API, and enable the service, if necessary.
  3. Return to the API Library page, search for Cloud Vision API, and enable it, if necessary.
  4. Return to the API Library page, search for Cloud Translation API, and enable it, if necessary.
Create the required buckets.
  1. From the main navigation, go to Storage > Browser.
  2. Choose Create bucket.
  3. In the Name field, enter a unique name for the bucket to hold the incoming image and click Continue.
  4. From the Choose where to store your data options, choose Region and select us-east1 as the region.
  5. Leave the remaining values at their defaults, and click Create.
  6. Repeat steps 2–5 to create a bucket to hold the resulting translations.
Create the required Pub/Sub topics.
  1. From the main console navigation, go to Pub/Sub > Topics.
  2. Click Create Topic.
  3. In the dialog, enter the name acg-image-to-text-results for the topic.
  4. Leave the options at their defaults and Click Create Topic.
  5. Return to the main Pub/Sub page and repeat steps 2–4 to create another topic with the name acg-image-to-text-translation.
Retrieve files from repo and configure.
  1. Activate the Cloud Shell.

  2. From the Cloud Shell, issue the following command to clone the repository for this course:

    git clone https://github.com/linuxacademy/content-gc-functions-deepdive
  3. Change directory to the lab folder:
    cd content-gc-functions-deepdive/cloud-functions-apis-lab
  4. Expand the Projects panel by clicking the triangle next to the current project name.
  5. Copy the current project ID.
  6. Open the Cloud Shell Editor by clicking Open Editor.
  7. Navigate to the cloud-functions-apis-lab folder, and open main.py.
  8. In the main.py file, on line 29, change the PROJECT_ID value to match your project ID.
  9. On line 34, change the RESULT_BUCKET value to match the name of the bucket intended to hold your translation results.
  10. Save the file.
Create first function.
  1. Navigate to the Cloud Functions dashboard.
  2. Click Create function.
  3. Apply the following settings:
    • Name: ocr-extract
    • Region: us-east1
    • Trigger: Cloud Storage
    • Event Type: Finalize/Create
    • Bucket: Your storage bucket for incoming files
  4. Click Save and then Next.
    • Runtime: Python 3.9
    • Source code: Inline editor
  5. From the Cloud Shell Editor, select all of the main.py code, and copy it.
  6. In the main.py field of the function, paste the copied code.
  7. From the Cloud Shell Editor, open requirements.txt, and copy all.
  8. In the requirements.txt field of the function, paste the copied code.
  9. In the Entry Point field, enter process_image.
  10. Click Deploy.
Create second function.
  1. From the Cloud Functions dashboard, click the just-created function.
  2. Click Copy
  3. Apply the following settings:
    • Name: ocr-translate
    • Region: us-east1
    • Trigger: Cloud Pub/Sub
    • Topic: acg-image-to-text-translation
  4. Click Save and then Next.
    • Runtime: Python 3.9
    • Source code: Inline editor
  5. In the Entry Point field, enter translate_text.
  6. Click Deploy.
Create third function.
  1. From the Cloud Functions dashboard, click the just-created function.
  2. Click Copy
  3. Apply the following settings:
    • Name: ocr-save
    • Region: us-east1
    • Trigger: Cloud Pub/Sub
    • Topic: acg-image-to-text-results
  4. Click Save and then Next.
    • Runtime: Python 3.9
    • Source code: Inline editor
  5. In the Entry Point field, enter save_result.
  6. Click Deploy.
Test in Cloud Shell and review results.
  1. In the Cloud Shell, issue the following commands:
    cd images
ls
gsutil cp sign.png gs://<BUCKET_NAME>
gsutil cp menu.jpg gs://<BUCKET_NAME>
  2. From the console, navigate to Storage > Browser.
  3. Open your bucket that contains the translated results.
  4. Open any generated files.
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Additional Resources

Your company is expanding globally and needs a way to translate text in images into multiple languages. You’ve been given the job of working with Cloud Functions to automatically extract the text from an uploaded image, translate it into six different languages, and then store the results in Cloud Storage.

You’ll need to accomplish the following steps to complete your task:

  1. Enable APIs.
  2. Create Cloud Storage buckets.
  3. Create Cloud Pub/Sub topics.
  4. Create and deploy Cloud Functions.
  5. Upload image to initiate test.
  6. View results.

What are Hands-on Labs

Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.

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