Dua Lipa sues Samsung for $15m, alleging her photo has been selling its TVs without permission since 2025

Introduction

In this tutorial, you'll learn how to use Python to search for and identify unauthorized use of your photos online. This is a practical skill for anyone who wants to protect their intellectual property, especially if you're a public figure, content creator, or business owner. We'll walk through how to build a simple web scraper that can search for your images across the internet using Google's image search API, and how to analyze the results to identify potential copyright violations.

Prerequisites

Before starting this tutorial, you'll need:

• A computer with internet access
• Python 3.6 or higher installed
• Basic understanding of Python syntax
• Google account (for API access)

Step-by-step Instructions

Step 1: Set Up Your Python Environment

First, you'll need to install the required Python packages. Open your terminal or command prompt and run:

pip install google-images-search requests

This installs the necessary libraries to search for images and make HTTP requests. The google-images-search package is crucial because it provides an interface to Google's image search API, which will allow us to find where your photos might be appearing online.

Step 2: Get Your Google API Credentials

Next, you'll need to create a Google Cloud project to access the Custom Search API:

1. Visit Google Cloud Console
2. Create a new project or select an existing one
3. Enable the Custom Search API
4. Create credentials (API key) for your project

Once you have your API key, you'll need to create a Custom Search Engine:

1. Go to Google Custom Search Engine
2. Create a new search engine
3. Set it to search the entire web
4. Copy the search engine ID

This setup is necessary because we'll use Google's Custom Search API to programmatically search for your images, which is more reliable than scraping directly from Google's search results page.

Step 3: Create Your Python Script

Create a new file called image_monitor.py and add the following code:

from google_images_search import GoogleImagesSearch
import os

# Replace with your own API credentials
API_KEY = 'YOUR_API_KEY_HERE'
SEARCH_ENGINE_ID = 'YOUR_SEARCH_ENGINE_ID_HERE'

# Configuration for image search
config = {
    'key': API_KEY,
    'search_engine_id': SEARCH_ENGINE_ID,
    'num': 10,  # Number of results to return
    'safe': 'high',  # Safe search level
    'fileType': 'jpg|png',  # Filter for image types
    'rights': 'cc_publicdomain|cc_attribute|cc_sharealike|cc_noncommercial|cc_nonderived'  # Filter by usage rights
}

gis = GoogleImagesSearch(config['key'], config['search_engine_id'])

This code initializes the Google Images Search library with your API credentials. The configuration sets parameters for how many results to return, what type of images to search for, and how to filter results based on usage rights. This is the foundation of our monitoring system.

Step 4: Define Your Search Parameters

Now, add the following code to define what you're searching for:

# Define what to search for (replace with your own image name or description)
search_params = {
    'q': 'Dua Lipa',  # Search term
    'num': 10,
    'safe': 'high',
    'fileType': 'jpg|png',
    'rights': 'cc_publicdomain|cc_attribute|cc_sharealike|cc_noncommercial|cc_nonderived'
}

gis.search(search_params=search_params)

# Print results
for image in gis.results():
    print(f"Title: {image.title}")
    print(f"URL: {image.url}")
    print(f"Thumbnail: {image.thumbnail}")
    print("---")

This section defines the search parameters. In our example, we're searching for 'Dua Lipa', but you can modify this to search for your own name, logo, or specific image description. The results will show the title, URL, and thumbnail of each image found.

Step 5: Save Results to a File

Let's enhance our script to save the search results to a file for later review:

import json

# Save results to a JSON file
results = []
for image in gis.results():
    results.append({
        'title': image.title,
        'url': image.url,
        'thumbnail': image.thumbnail
    })

# Save to file
with open('search_results.json', 'w') as f:
    json.dump(results, f, indent=4)

print("Results saved to search_results.json")

Saving the results to a JSON file allows you to review the findings later and compare them against your own photo collection. This is especially useful if you're monitoring for unauthorized use of your images, as you can easily identify potential copyright violations.

Step 6: Run Your Script

Save your Python script and run it using:

python image_monitor.py

If everything is set up correctly, you should see output showing the search results and a new file called search_results.json in your directory. This file contains all the images found online that match your search criteria.

Summary

In this tutorial, you've learned how to create a simple Python script that can search for images online using Google's Custom Search API. This is a valuable tool for protecting your intellectual property, whether you're a public figure like Dua Lipa or a business owner looking to monitor unauthorized use of your branding. By running regular searches, you can identify when your photos appear on websites or product pages without permission, allowing you to take appropriate action. Remember to regularly update your search parameters and check results to stay ahead of potential copyright violations.