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Mariano Gabriel
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process_meeting.py
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229
process_meeting.py
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#!/usr/bin/env python3
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"""
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Process meeting recordings to extract audio + screen content.
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Combines Whisper transcripts with OCR from screen shares.
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"""
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import argparse
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from pathlib import Path
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import sys
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import json
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import logging
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from meetus.frame_extractor import FrameExtractor
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from meetus.ocr_processor import OCRProcessor
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from meetus.transcript_merger import TranscriptMerger
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logger = logging.getLogger(__name__)
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def setup_logging(verbose: bool = False):
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"""
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Configure logging for the application.
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Args:
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verbose: If True, set DEBUG level, otherwise INFO
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"""
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level = logging.DEBUG if verbose else logging.INFO
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# Configure root logger
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logging.basicConfig(
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level=level,
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format='%(asctime)s - %(levelname)s - %(message)s',
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datefmt='%H:%M:%S'
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)
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# Suppress verbose output from libraries
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logging.getLogger('PIL').setLevel(logging.WARNING)
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logging.getLogger('easyocr').setLevel(logging.WARNING)
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logging.getLogger('paddleocr').setLevel(logging.WARNING)
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def main():
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parser = argparse.ArgumentParser(
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description="Extract screen content from meeting recordings and merge with transcripts",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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# Process video and extract frames only
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python process_meeting.py samples/meeting.mkv --extract-only
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# Process video with Whisper transcript
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python process_meeting.py samples/meeting.mkv --transcript meeting.json
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# Use scene detection instead of interval
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python process_meeting.py samples/meeting.mkv --scene-detection
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# Use different OCR engine
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python process_meeting.py samples/meeting.mkv --ocr-engine easyocr
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"""
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)
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parser.add_argument(
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'video',
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help='Path to video file'
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)
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parser.add_argument(
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'--transcript', '-t',
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help='Path to Whisper transcript (JSON or TXT)',
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default=None
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)
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parser.add_argument(
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'--output', '-o',
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help='Output file for enhanced transcript (default: <video>_enhanced.txt)',
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default=None
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)
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parser.add_argument(
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'--frames-dir',
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help='Directory to save extracted frames (default: frames/)',
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default='frames'
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)
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parser.add_argument(
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'--interval',
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type=int,
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help='Extract frame every N seconds (default: 5)',
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default=5
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)
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parser.add_argument(
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'--scene-detection',
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action='store_true',
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help='Use scene detection instead of interval extraction'
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)
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parser.add_argument(
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'--ocr-engine',
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choices=['tesseract', 'easyocr', 'paddleocr'],
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help='OCR engine to use (default: tesseract)',
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default='tesseract'
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)
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parser.add_argument(
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'--no-deduplicate',
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action='store_true',
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help='Disable text deduplication'
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)
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parser.add_argument(
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'--extract-only',
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action='store_true',
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help='Only extract frames and OCR, skip transcript merging'
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)
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parser.add_argument(
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'--format',
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choices=['detailed', 'compact'],
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help='Output format style (default: detailed)',
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default='detailed'
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)
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parser.add_argument(
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'--verbose', '-v',
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action='store_true',
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help='Enable verbose logging (DEBUG level)'
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)
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args = parser.parse_args()
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# Setup logging
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setup_logging(args.verbose)
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# Validate video path
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video_path = Path(args.video)
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if not video_path.exists():
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logger.error(f"Video file not found: {args.video}")
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sys.exit(1)
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# Set default output path
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if args.output is None:
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args.output = video_path.stem + '_enhanced.txt'
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logger.info("=" * 80)
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logger.info("MEETING PROCESSOR")
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logger.info("=" * 80)
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logger.info(f"Video: {video_path.name}")
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logger.info(f"OCR Engine: {args.ocr_engine}")
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logger.info(f"Frame extraction: {'Scene detection' if args.scene_detection else f'Every {args.interval}s'}")
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logger.info("=" * 80)
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# Step 1: Extract frames
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logger.info("Step 1: Extracting frames from video...")
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extractor = FrameExtractor(str(video_path), args.frames_dir)
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if args.scene_detection:
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frames_info = extractor.extract_scene_changes()
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else:
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frames_info = extractor.extract_by_interval(args.interval)
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if not frames_info:
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logger.error("No frames extracted")
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sys.exit(1)
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logger.info(f"✓ Extracted {len(frames_info)} frames")
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# Step 2: Run OCR on frames
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logger.info("Step 2: Running OCR on extracted frames...")
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try:
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ocr = OCRProcessor(engine=args.ocr_engine)
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screen_segments = ocr.process_frames(
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frames_info,
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deduplicate=not args.no_deduplicate
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)
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logger.info(f"✓ Processed {len(screen_segments)} frames with text content")
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except ImportError as e:
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logger.error(f"{e}")
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logger.error(f"To install {args.ocr_engine}:")
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logger.error(f" pip install {args.ocr_engine}")
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sys.exit(1)
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# Save OCR results as JSON
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ocr_output = video_path.stem + '_ocr.json'
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with open(ocr_output, 'w', encoding='utf-8') as f:
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json.dump(screen_segments, f, indent=2, ensure_ascii=False)
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logger.info(f"✓ Saved OCR results to: {ocr_output}")
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if args.extract_only:
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logger.info("Done! (extract-only mode)")
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return
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# Step 3: Merge with transcript (if provided)
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merger = TranscriptMerger()
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if args.transcript:
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logger.info("Step 3: Merging with Whisper transcript...")
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transcript_path = Path(args.transcript)
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if not transcript_path.exists():
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logger.warning(f"Transcript not found: {args.transcript}")
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logger.info("Proceeding with screen content only...")
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audio_segments = []
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else:
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audio_segments = merger.load_whisper_transcript(str(transcript_path))
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logger.info(f"✓ Loaded {len(audio_segments)} audio segments")
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else:
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logger.info("No transcript provided, using screen content only...")
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audio_segments = []
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# Merge and format
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merged = merger.merge_transcripts(audio_segments, screen_segments)
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formatted = merger.format_for_claude(merged, format_style=args.format)
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# Save output
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merger.save_transcript(formatted, args.output)
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logger.info("=" * 80)
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logger.info("✓ PROCESSING COMPLETE!")
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logger.info("=" * 80)
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logger.info(f"Enhanced transcript: {args.output}")
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logger.info(f"OCR data: {ocr_output}")
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logger.info(f"Frames: {args.frames_dir}/")
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logger.info("")
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logger.info("You can now use the enhanced transcript with Claude for summarization!")
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if __name__ == '__main__':
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main()
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