📄➡️🎥 Pdf2Video — PDF to Video Generation Pipeline

#everything mentioned below is for the legacy project #(i made it as a personal project the rest modifications are similar and took in from my another project echo class )

Pdf2Video is a Python-based project that converts PDF documents into videos by extracting pages, generating visual frames, optionally adding audio, and stitching everything into a final video output.

This repository focuses on the media-generation side of the pipeline and complements larger video processing systems.

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🚀 What This Project Does

• Extracts pages from a PDF file
• Converts pages into image frames
• Generates audio (e.g., narration) for content
• Synchronizes frames and audio
• Stitches everything into a playable video
• Cleans up intermediate files

The end result is a video representation of a PDF document, suitable for demos, explainers, or content repurposing.

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🧠 High-Level Pipeline

PDF File
  ↓
PDF Extraction
  ↓
Frame Generation
  ↓
Audio Generation
  ↓
Video Stitching
  ↓
Final Video Output

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📂 Project Structure (Core Files)

• pdf_extract.py
  Extracts text and/or page images from the PDF.

• frame_generation.py
  Converts extracted PDF content into visual frames.

• generate_audio.py
  Generates audio tracks (e.g., narration or voice-over).

• generate_vedio.py
  Handles video generation from frames (filename typo retained).

• stitch_vedio_and_clean.py
  Merges video and audio, then removes temporary files.

• pipeline.py
  Orchestrates the full PDF → Video workflow.

• test.py / tests.py
  Local testing and experimentation scripts.

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🛠 Tech Stack

• Python
• FFmpeg
• PDF processing libraries
• Image processing utilities
• Audio generation tools (TTS or waveform-based)

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▶️ How to Run (Basic)

1️⃣ Install dependencies

pip install -r requirements.txt

2️⃣ Run the pipeline

python pipeline.py

3️⃣ Output

• Generated video will appear in the output directory (as defined in code)

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⚠️ Notes & Assumptions

• This is an experimental / MVP-style project
• Paths and configs may be hardcoded
• Error handling is minimal
• Designed for local execution

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🎯 Use Cases

• Converting slide-style PDFs into videos
• Generating explainer videos from documents
• Content repurposing (docs → media)
• Integration into larger video pipelines

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🔗 Related Work

This project can be integrated with:

• Async video processing backends
• Media normalization pipelines
• Streaming and playback services

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👨‍💻 Author

Built by Yashmit Vaish.

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📌 Future Improvements

• Better CLI interface
• Config-driven pipeline
• Audio/video sync enhancements
• Integration with job-based processing systems