updated readme
This commit is contained in:
Mariano Gabriel
76
README.md
76
README.md
@@ -46,25 +46,19 @@ For speaker diarization, you'll need a HuggingFace token with access to pyannote
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## Quick Start
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### Recommended: Embed Frames with Scene Detection
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### Recommended Usage
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```bash
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 10 --diarize
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```
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This will:
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1. Run Whisper transcription (audio → text)
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2. Extract frames at scene changes (smarter than fixed intervals)
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3. Embed frame references in the transcript for LLM analysis
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1. Run WhisperX transcription with speaker diarization
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2. Extract frames at scene changes (threshold 10 = moderately sensitive)
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3. Create an enhanced transcript with frame file references
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4. Save everything to `output/` folder
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### With Speaker Diarization (WhisperX)
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```bash
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python process_meeting.py samples/meeting.mkv --run-whisper --diarize --embed-images --scene-detection
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```
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This uses WhisperX to identify different speakers in the transcript.
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The `--embed-images` flag adds frame paths to the transcript (e.g., `Frame: frames/video_00257.jpg`), keeping the transcript small while frames stay in `frames/` folder for LLM access.
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### Re-run with Cached Results
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@@ -76,48 +70,38 @@ python process_meeting.py samples/meeting.mkv --embed-images
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# Skip only specific cached items
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python process_meeting.py samples/meeting.mkv --embed-images --skip-cache-frames
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python process_meeting.py samples/meeting.mkv --embed-images --skip-cache-whisper
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python process_meeting.py samples/meeting.mkv --embed-images --skip-cache-analysis
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# Force complete reprocessing
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --no-cache
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --diarize --no-cache
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```
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## Usage Examples
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### Scene Detection Options
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```bash
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# Default scene detection (threshold: 15)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection
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# Default threshold (15)
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --diarize
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# More sensitive (more frames captured, threshold: 5)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection --scene-threshold 5
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# More sensitive (more frames, threshold: 5)
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 5 --diarize
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# Less sensitive (fewer frames, threshold: 30)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection --scene-threshold 30
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 30 --diarize
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```
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### Fixed Interval Extraction (alternative to scene detection)
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```bash
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# Every 10 seconds
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --interval 10
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python process_meeting.py samples/meeting.mkv --embed-images --interval 10 --diarize
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# Every 3 seconds (more detailed)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --interval 3
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```
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### Frame Quality Options
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```bash
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# Default quality (80)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection
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# Lower quality for smaller files (60)
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection --embed-quality 60
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python process_meeting.py samples/meeting.mkv --embed-images --interval 3 --diarize
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```
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### Caching Examples
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```bash
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# First run - processes everything
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 10 --diarize
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# Iterate on scene threshold (reuse whisper transcript)
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 5 --skip-cache-frames --skip-cache-analysis
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@@ -126,17 +110,17 @@ python process_meeting.py samples/meeting.mkv --embed-images --scene-detection -
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python process_meeting.py samples/meeting.mkv --embed-images --skip-cache-whisper
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# Force complete reprocessing
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --no-cache
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --diarize --no-cache
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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 --run-whisper --embed-images --output-dir my_outputs/
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --diarize --output-dir my_outputs/
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```
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### Enable verbose logging
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```bash
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection --verbose
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --diarize --verbose
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```
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## Output Files
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@@ -175,24 +159,17 @@ This allows you to iterate on scene detection thresholds without re-running Whis
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### Complete Workflow (One Command!)
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```bash
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# Process everything in one step with scene detection
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection
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# With speaker diarization
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python process_meeting.py samples/meeting.mkv --run-whisper --diarize --embed-images --scene-detection
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 10 --diarize
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```
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### Typical Iterative Workflow
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```bash
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# First run - full processing
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python process_meeting.py samples/meeting.mkv --run-whisper --embed-images --scene-detection
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 10 --diarize
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# Adjust scene threshold (keeps cached whisper transcript)
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 10 --skip-cache-frames --skip-cache-analysis
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# Try different frame quality
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python process_meeting.py samples/meeting.mkv --embed-images --embed-quality 60 --skip-cache-frames --skip-cache-analysis
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python process_meeting.py samples/meeting.mkv --embed-images --scene-detection --scene-threshold 5 --skip-cache-frames --skip-cache-analysis
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```
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### Example Prompt for Claude
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@@ -223,11 +200,8 @@ usage: process_meeting.py [-h] [--transcript TRANSCRIPT] [--run-whisper]
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Main Options:
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video Path to video file
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--run-whisper Run Whisper transcription before processing
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--whisper-model Whisper model: tiny, base, small, medium, large (default: medium)
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--diarize Use WhisperX with speaker diarization
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--embed-images Embed frame references for LLM analysis (recommended)
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--embed-quality JPEG quality for frames (default: 80)
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--embed-images Add frame file references to transcript (recommended)
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Frame Extraction:
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--scene-detection Use FFmpeg scene detection (recommended)
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@@ -241,6 +215,8 @@ Caching:
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--skip-cache-analysis Re-run analysis only
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Other:
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--run-whisper Run Whisper (without diarization)
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--whisper-model Whisper model: tiny, base, small, medium, large (default: medium)
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--transcript, -t Path to existing Whisper transcript (JSON or TXT)
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--output, -o Output file for enhanced transcript
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--output-dir Directory for output files (default: output/)
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@@ -262,10 +238,6 @@ Other:
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- **Whisper** (`--run-whisper`): Standard transcription, fast
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- **WhisperX** (`--run-whisper --diarize`): Adds speaker identification, requires HuggingFace token
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### Frame Quality
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- Default quality (80) works well for most cases
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- Use `--embed-quality 60` for smaller files if storage is a concern
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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/screens change subtly
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