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Image Text Extract and Translation

Image-Text-Translator Application

Overview

An application that allows a user to upload an image containing text. The text will be extracted, and translated to any selected language.

E.g. A user wants to translate a meme in Ukrainian, to English.

It is built using:

  • Python Flask for the UI
  • Event driven functions for the backend
  • Google Cloud serverless components for hosting: i.e. Cloud Run and Cloud Functions
  • Google pre-built ML APIs for the extraction and translation

Repo Structure

└── image-text-translator
    ├── docs/
    |
    ├── infra-tf/               - Terraform for installing infra
    |
    ├── scripts/                - For environment setup and helper scripts
    |   ├── 00_image-text-translator-sa-setup.sh  - Initial sa setup
    |   ├── 01_env_setup.sh                       - Env setup - run with each new session
    |   └── 02_deployment_sa.sh                   - Deployment sa setup
    |
    ├── app/                    - The Application
    │   ├── ui_cr/                - Browser UI (Cloud Run)
    │   │   ├── static/             - Static content for frontend
    |   |   ├── templates/          - HTML templates for frontend
    |   |   ├── app.py              - The Flask application
    |   |   ├── requirements.txt    - The UI Python requirements
    |   |   ├── Dockerfile          - Dockerfile to build the Flask container
    |   |   └── .dockerignore       - Files to ignore in Dockerfile
    |   |
    │   └── backend_gcf/          - Backend (Cloud Function)
    │       ├── main.py             - The backend CF application
    │       └── requirements.txt    - The backend CF Python requirements
    |
    ├── testing/
    │   └── images/
    |
    ├── requirements.txt          - Python requirements for project local dev
    └── README.md                 - Repo README

Walkthrough and Detailed Guide

Check out my Medium blog, where I describe:

  • How the solution is architected
  • Design choices and rationale
  • A walkthrough of how you can do the same, end-to-end, including:
    • Dev environment setup (including Google Cloud SDK, VS Code, Cloud Code)
    • Service accounts and roles
    • Application Default Credentials (ADC)
    • The coding for the UI (Python, Flask, Jinja templates) and backend (Python)
    • How to test locally
    • How to deploy to Google Cloud (using Google Artifact Registry and Cloud Build)
  • Cost management tips
  • Performance tips

Todo

Some improvements I'll make soon...

  • Captcha
  • CI/CD
  • IaC