⚠️ The project is still in development. Please be patient and report any issues you encounter. ⚠️ The pdf summarization is still in development and will not work in the current version. However, you can create a .txt file in the root directory with the name kokoro_script.txt and add your text you want to display in the brainrot content.

Tired of boring PDFs? Want to inject some chaotic energy into your documents? PDF2BRAINROT is here to help! This script takes your standard PDF files and transforms them into dynamic, attention-grabbing "Brainrot" content.

What is "Brainrot Content"?

Think short, fast-paced, visually stimulating videos designed to grab attention and keep it.  PDF2BRAINROT leverages text-to-speech and dynamic video editing to convert your PDF's text into this engaging format. Imagine your PDF's content brought to life with:

• AI-powered Voiceover:  Using kokoro, your PDF's text is converted into an expressive audio voiceover.
• Timestamped Audio: whisper-timestamps adds precise timestamps to the audio, allowing for synchronized video editing.
• Dynamic Video Generation: moviepy combines the text, timestamped audio, and potentially other visual elements (you can customize this!) to create a "Brainrot" video.

Think:  Imagine excerpts from your PDF presented as fast-paced, captioned videos perfect for sharing on social media or grabbing attention in a digital age.

• PDF Text Extraction:  Efficiently extracts text content from PDF files using pymupdf.
• Text-to-Speech Conversion:  Generates natural-sounding audio voiceovers from the extracted text using kokoro.
• Audio Timestamping: Precisely timestamps the generated audio using whisper-timestamps for accurate synchronization in video editing.
• Brainrot Video Generation:  Utilizes moviepy to create dynamic videos incorporating the text, timestamped audio, and customizable visual elements (currently basic, but highly extensible!).
• Easy to Use: Simple command-line interface for quick conversion.
• Customizable (Future Potential): The script is designed to be extensible, allowing for future customization of video styles, visual elements, and "Brainrot" effects.

Get ready to unleash the Brainrot! Follow these steps to set up the script:

It's always a good idea to work in a virtual environment to keep your project dependencies isolated.

python -m venv venv
venv\Scripts\activate  # On Windows
# source venv/bin/activate # On Linux/macOS

This package requires ffmpeg to be installed on your system and its PATH variable to be set. You can download it from here.

Install the necessary Python libraries using pip. Make sure you are in your virtual environment.

pip install -r requirements.txt

If you have an NVIDIA GPU with CUDA cores, installing PyTorch with CUDA support can significantly speed up processing, especially if you expand the script to include more advanced features in the future.

• Check your CUDA Toolkit Version:  Find out which CUDA Toolkit version you have installed on your system.
• Visit the PyTorch Website: Go to the official PyTorch Get Started page.
• Select your Configuration: Choose your PyTorch version, operating system, package manager (pip), Python version, and CUDA version.
• Copy and Run the Installation Command: PyTorch will provide you with the correct pip3 install command.

Example for Windows with CUDA 11.8:

pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

You will need to use a custom font and specify your own brainrot content by replacing the following lines with your file paths:

BASE_VIDEO = "videoplayback.mp4"
FONT_PATH = "./Roboto-ExtraBold.ttf"

Transform your PDFs into Brainrot with a single command!

python pdf2brainrot.py --source <path_to_your_pdf_file>

• <path_to_your_pdf_file>: Replace this with the actual path to the PDF file you want to convert. For example: my_document.pdf or C:\Users\YourName\Documents\report.pdf

The script's execution time depends on the size and content of your PDF file. Larger files with more text will naturally take longer to process due to text extraction, audio generation, and video creation. For a PDF with about 200 lines of text, it will take approximately an hour to complete the full process.  Please be patient!

The script will generate a Brainrot video in the same directory as the script, named final_video_with_subs.mp4

We would like to extend our sincere gratitude to the following communities for providing the incredible tools and resources that made PDF2BRAINROT possible:

• The Kokoro Community: For developing kokoro, a fantastic tool for expressive text-to-speech generation. Your work is instrumental in bringing the voice to Brainrot content.
• The Whisper-Timestamps Community: For developing whisper-timestamps, a powerful tool that enables precise audio timestamping, ensuring better synchronization in video creation.
• The Python Community: For the rich and versatile Python ecosystem and the countless libraries that empower developers worldwide. PDF2BRAINROT is built upon the shoulders of giants in the Python community.

Thank you for your dedication and open-source contributions!

Want to contribute to PDF2BRAINROT?

We welcome contributions to make this script even more brainrotting! Here are some ways you can help:

• Suggest new features: Have ideas for making the videos more dynamic or adding more "Brainrot" effects? Let us know!
• Improve video styles: Experiment with different moviepy effects and video editing techniques to create even more engaging Brainrot visuals.
• Add support for more languages: Expanding language support for text extraction, text-to-speech, and speech recognition would be a valuable contribution.
• Bug fixes and code improvements: Found a bug or have a way to optimize the code? Pull requests are greatly appreciated!

If you encounter any issues, have questions about using the script, or just want to share your Brainrot creations, please feel free to reach out! You can:

• Open an issue on the project's GitHub repository (if applicable). [PDF2BRAINROT]
• Contact the script author directly at [[email protected]]

We are excited to see what Brainrot content you create and how you might contribute to this project!

Have fun creating some Brainrot! 😵‍💫🎉

✅ Replaced vosk with whisper-timestamps for more accurate audio timestamps
✅ Simplified installation and added instructions for using local Whisper models
✅ Improved clarity and formatting for better readability