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This Python script automates the creation of Pinterest-style post images by overlaying customizable text on randomly selected backgrounds from a specified folder. It reads text from a CSV file, supports threading for concurrent image generation, and offers options for text alignment, font selection, and color highlighting.

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Nafi7393/PINTEREST-POST-MAKER

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Pinterest Post Maker

This Python script generates Pinterest-style post images by overlaying text on background images. It utilizes threading for concurrent image generation and supports customization of text styling.

Requirements

  • Python 3.x
  • PIL (Python Imaging Library)
  • impact.ttf font file (or specify your own font)
  • Background images in the background_images folder
  • Input text lines in a CSV file (pin_text.csv)

Installation

  1. Clone the repository:

    git clone https://github.com/Nafi7393/PINTEREST-POST-MAKER.git
    cd PINTEREST-POST-MAKER
    
  2. Install dependencies:

    pip install pillow
    
  3. Place your background images in the background_images folder.

Usage

Modify pin_text.csv with your desired text lines. Then run the script to generate Pinterest-style images:

python main.py

Adjust parameters in main.py such as max_limit in fire_pins function for batch image generation.

Example Images

Example 1 Example 2 Example 2
Example 1 Example 1 Example 1

Customization

  • Text Styling: Modify text_color, font_path, base_font_size, and font_increase_size in PinMaker class for different text effects.
  • Backgrounds: Add or change background images in background_images folder to create diverse post styles.

Notes

  • Ensure the CSV file (pin_text.csv) is correctly formatted with each line of text in the first column.
  • The script uses threading for concurrent image processing, ensuring efficient batch image creation.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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This Python script automates the creation of Pinterest-style post images by overlaying customizable text on randomly selected backgrounds from a specified folder. It reads text from a CSV file, supports threading for concurrent image generation, and offers options for text alignment, font selection, and color highlighting.

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