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Mariano Gabriel
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README.md
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README.md
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# Meeting Processor
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Extract screen content from meeting recordings and merge with Whisper transcripts for better Claude summarization.
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## Overview
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This tool enhances meeting transcripts by combining:
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- **Audio transcription** (from Whisper)
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- **Screen content** (OCR from screen shares)
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The result is a rich, timestamped transcript that provides full context for AI summarization.
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## Installation
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### 1. System Dependencies
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**Tesseract OCR** (recommended):
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```bash
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# Ubuntu/Debian
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sudo apt-get install tesseract-ocr
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# macOS
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brew install tesseract
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# Arch Linux
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sudo pacman -S tesseract
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```
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**FFmpeg** (for scene detection):
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```bash
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# Ubuntu/Debian
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sudo apt-get install ffmpeg
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# macOS
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brew install ffmpeg
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```
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### 2. Python Dependencies
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```bash
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pip install -r requirements.txt
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```
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### 3. Optional: Install Alternative OCR Engines
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```bash
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# EasyOCR (better for rotated/handwritten text)
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pip install easyocr
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# PaddleOCR (better for code/terminal screens)
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pip install paddleocr
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```
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## Quick Start
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### Basic Usage (Screen Content Only)
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```bash
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python process_meeting.py samples/meeting.mkv
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```
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This will:
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1. Extract frames every 5 seconds
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2. Run OCR to extract screen text
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3. Save enhanced transcript to `meeting_enhanced.txt`
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### With Whisper Transcript
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First, generate a Whisper transcript:
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```bash
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whisper samples/meeting.mkv --model base --output_format json
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```
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Then process with screen content:
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```bash
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python process_meeting.py samples/meeting.mkv --transcript samples/meeting.json
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```
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## Usage Examples
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### Extract frames at different intervals
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```bash
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# Every 10 seconds
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python process_meeting.py samples/meeting.mkv --interval 10
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# Every 3 seconds (more detailed)
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python process_meeting.py samples/meeting.mkv --interval 3
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```
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### Use scene detection (smarter, fewer frames)
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```bash
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python process_meeting.py samples/meeting.mkv --scene-detection
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```
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### Use different OCR engines
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```bash
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# EasyOCR (good for varied layouts)
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python process_meeting.py samples/meeting.mkv --ocr-engine easyocr
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# PaddleOCR (good for code/terminal)
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python process_meeting.py samples/meeting.mkv --ocr-engine paddleocr
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```
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### Extract frames only (no merging)
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```bash
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python process_meeting.py samples/meeting.mkv --extract-only
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```
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### Custom output location
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```bash
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python process_meeting.py samples/meeting.mkv --output my_meeting.txt --frames-dir my_frames/
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```
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### Enable verbose logging
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```bash
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# Show detailed debug information
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python process_meeting.py samples/meeting.mkv --verbose
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# Short form
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python process_meeting.py samples/meeting.mkv -v
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```
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## Output Files
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After processing, you'll get:
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- **`<video>_enhanced.txt`** - Enhanced transcript ready for Claude
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- **`<video>_ocr.json`** - Raw OCR data with timestamps
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- **`frames/`** - Extracted video frames (JPG files)
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## Workflow for Meeting Analysis
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### Complete Workflow
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```bash
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# 1. Extract audio and transcribe with Whisper
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whisper samples/alo-intro1.mkv --model base --output_format json
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# 2. Process video to extract screen content
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python process_meeting.py samples/alo-intro1.mkv \
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--transcript samples/alo-intro1.json \
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--scene-detection
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# 3. Use the enhanced transcript with Claude
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# Copy the content from alo-intro1_enhanced.txt and paste into Claude
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```
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### Example Prompt for Claude
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```
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Please summarize this meeting transcript. Pay special attention to:
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1. Key decisions made
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2. Action items
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3. Technical details shown on screen
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4. Any metrics or data presented
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[Paste enhanced transcript here]
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```
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## Command Reference
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```
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usage: process_meeting.py [-h] [--transcript TRANSCRIPT] [--output OUTPUT]
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[--frames-dir FRAMES_DIR] [--interval INTERVAL]
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[--scene-detection]
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[--ocr-engine {tesseract,easyocr,paddleocr}]
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[--no-deduplicate] [--extract-only]
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[--format {detailed,compact}] [--verbose]
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video
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Options:
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video Path to video file
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--transcript, -t Path to Whisper transcript (JSON or TXT)
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--output, -o Output file for enhanced transcript
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--frames-dir Directory to save extracted frames (default: frames/)
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--interval Extract frame every N seconds (default: 5)
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--scene-detection Use scene detection instead of interval extraction
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--ocr-engine OCR engine: tesseract, easyocr, paddleocr (default: tesseract)
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--no-deduplicate Disable text deduplication
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--extract-only Only extract frames and OCR, skip transcript merging
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--format Output format: detailed or compact (default: detailed)
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--verbose, -v Enable verbose logging (DEBUG level)
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```
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## Tips for Best Results
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### Scene Detection vs Interval
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- **Scene detection**: Better for presentations with distinct slides. More efficient.
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- **Interval extraction**: Better for continuous screen sharing (coding, browsing). More thorough.
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### OCR Engine Selection
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- **Tesseract**: Best for clean slides, documents, presentations. Fast and lightweight.
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- **EasyOCR**: Better for handwriting, rotated text, or varied fonts.
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- **PaddleOCR**: Excellent for code, terminal outputs, and mixed languages.
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### Deduplication
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- Enabled by default - removes similar consecutive frames
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- Disable with `--no-deduplicate` if slides change subtly
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## Troubleshooting
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### "pytesseract not installed"
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```bash
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pip install pytesseract
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sudo apt-get install tesseract-ocr # Don't forget system package!
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```
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### "No frames extracted"
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- Check video file is valid: `ffmpeg -i video.mkv`
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- Try lower interval: `--interval 3`
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- Check disk space in frames directory
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### Poor OCR quality
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- Try different OCR engine
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- Check if video resolution is sufficient
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- Use `--no-deduplicate` to keep more frames
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### Scene detection not working
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- Fallback to interval extraction automatically
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- Ensure FFmpeg is installed
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- Try manual interval: `--interval 5`
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## Project Structure
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```
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meetus/
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├── meetus/ # Main package
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│ ├── __init__.py
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│ ├── frame_extractor.py # Video frame extraction
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│ ├── ocr_processor.py # OCR processing
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│ └── transcript_merger.py # Transcript merging
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├── process_meeting.py # Main CLI script
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├── requirements.txt # Python dependencies
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└── README.md # This file
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```
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## License
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For personal use.
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