Google Images Scraper

Google Images Scraper is a Python tool designed to scrape high-resolution images from Google Images based on provided links. It now supports multi-threading for faster scraping. This tool overcomes the limitations of some browser extensions that only download image thumbnails.

Table of Contents

• Installation
• Usage
• Configuration
• Project Structure
• Contributing
• License

Installation

1. Clone the repository:

   git clone https://github.com/your-username/google-images-scraper.git

2. Navigate to the project directory:

   cd google-images-scraper

3. Create the environment:

   python -m venv .venv

4. Activate the Virtual Environment:

   # For Linux
   source .venv/bin/activate
   
   # For Windows
   
   # For Powershell
   .venv/Scripts/Activate.ps1
   # For Command Prompt
   .venv/Scripts/activate.bat

5. Install the required dependencies:

   pip install -r requirements.txt

Usage

1. Run the scraper by executing the following command:

   python main.py

   This script will fetch high-resolution images from Google Images based on the provided links using multi-threading for faster scraping.

Configuration

You can customize the behavior of the scraper by modifying the config.yaml file.

Email Configuration

• sender_email: The email address used for sending notifications.
• receiver_email: The email address to receive notifications.
• sender_email_password: The password for the sender's email account.
• send_email: Set True or False for sending emails.

Note: If you want to use the email notifications functionality with a Gmail account, it's recommended to generate an App Password instead of using your account password.

Search Queries

• search_queries: List of search queries to use when scraping Google Images. You can add or remove queries as needed.

Images Limit

• images_limit: Set the maximum number of images to download per category.

Project Info

• csv_downloads: Directory to store CSV files.
• image_downloads: Directory to store downloaded images.
• downloader.py: Contains class to download images using multi-threading.
• email_service.py: Provides functionality for email notifications (if needed).
• scraper.py: The main scraper class to initiate the scraping process with multi-threading.
• config.yaml: Configuration file to set up email and scraping parameters.
• link_saver.py: Handles saving image links.
• main.py: The main entry point for running the Google Images Scraper.

Getting Started

In main.py, an instance of the Scraper class is created as follows:

sc = Scraper(num_threads=5, show_ui=True)

• num_threads: You can customize the number of threads, which represents the total browser instances. More threads generally result in faster scraping, but it may increase resource usage. Adjust this value based on your system's capabilities and requirements.

• show_ui: The show_ui option determines whether Selenium runs in headless mode or not. When set to True, it shows the browser UI during scraping. When set to False, it runs Selenium in headless mode, which means the browser operates in the background without a visible UI. Choose the appropriate setting based on your preference and needs.

The rest of the process is straightforward:

5. Run the scraper by executing main.py:

   python main.py

6. The scraper will start fetching high-resolution images from Google Images based on the provided links and configurations, using the specified number of threads and UI visibility.

7. Monitor the scraping progress and any notifications sent via email, as configured in config.yaml.

Contributing

Contributions to Google Images Scraper are welcome and encouraged! To contribute, follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and test thoroughly.
4. Commit your changes with descriptive commit messages.
5. Push your changes to your fork.
6. Open a pull request, explaining the changes you've made.

License

This project is licensed under the MIT License.

Disclaimer

This program lets you download tons of images from Google Images. Please do not download or use any image that violates its copyright terms.