Solving "Use Machine Learning APIs on Google Cloud: Challenge Lab" — A Complete Guide

Introduction This challenge lab tests your ability to build an end-to-end pipeline that extracts text from images using the Cloud Vision API , translates it with the Cloud Translation API , and loads the results into BigQuery . Unlike guided labs, you're expected to fill in the blanks of a partially written Python script and configure IAM permissions yourself. Let's walk through every task with clear explanations of why each step matters. The Architecture The pipeline works like this: A Python script reads image files from a Cloud Storage bucket Each image is sent to the Cloud Vision API for text detection The extracted text is saved back to Cloud Storage as a .txt file If the text is not in Japanese ( locale != 'ja' ), it's sent to the Translation API to get a Japanese translation All results (original text, locale, translation) are uploaded to a BigQuery table. Task 1: Configure a Service Account Why a Service Account? The Python script needs programmatic access to Vision API, Transl