add whisperx support
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@@ -32,13 +32,13 @@ def main():
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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# Embed images for LLM analysis (recommended - let LLM analyze actual frames)
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# Reference frames for LLM analysis (recommended - transcript includes frame paths)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection
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# Embed with custom quality (lower = smaller file size)
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# Adjust frame extraction quality (lower = smaller files)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --embed-quality 60 --scene-detection
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# Hybrid approach: OpenCV + OCR (extracts text, no images)
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# Hybrid approach: OpenCV + OCR (extracts text from frames)
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python process_meeting.py samples/meeting.mkv --run-whisper --use-hybrid --scene-detection
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# Hybrid + LLM cleanup (best for code formatting)
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@@ -183,12 +183,12 @@ Examples:
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parser.add_argument(
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'--embed-images',
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action='store_true',
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help='Embed frame images (as base64) in enhanced transcript for LLM analysis'
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help='Skip OCR/vision analysis and reference frame files directly (faster, lets LLM analyze images)'
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)
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parser.add_argument(
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'--embed-quality',
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type=int,
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help='JPEG quality for embedded images (default: 80, lower = smaller file)',
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help='JPEG quality for extracted frames (default: 80, lower = smaller files)',
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default=80
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)
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