ab84a26c3e
- Add main.py with complete CLI interface for strip photography extraction - Support both column mode (--xcolumn) and row mode (--yrow) extraction - Implement intelligent change detection to filter static frames - Add configurable threshold system for compression control - Include debug mode (--debug) with change analysis and graph generation - Generate threshold suggestions with compression statistics - Add matplotlib dependency for visualization features - Update README with comprehensive usage examples and feature documentation - Provide threshold selection guidelines and advanced usage patterns Features: * Automatic frame filtering based on visual changes * Debug visualization with change graphs and statistics * Configurable compression ratios from 10% to 95%+ * Support for various video formats via OpenCV * Statistical analysis of frame-to-frame changes * Threshold optimization recommendations
90 lines
3.5 KiB
Markdown
90 lines
3.5 KiB
Markdown
# Strip Photography / Slit Photography
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A digital implementation of **strip photography** (also called **slit photography**) that captures a two-dimensional image as a sequence of one-dimensional images over time.
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**How it works:**
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Strip photography records a moving scene over time using a camera that observes a narrow strip rather than the full field. This implementation simulates the technique by extracting the same line position from each video frame and assembling them into a composite image where:
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- One axis represents **space** (the slit/line being observed)
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- The other axis represents **time** (progression through video frames)
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**Visual effects:**
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- Moving objects appear as visible shapes in the final image
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- Stationary objects (like background) appear as horizontal/vertical stripes
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- Object width is inversely proportional to speed (faster = narrower, slower = wider)
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## Usage
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**Column Mode** - Extract vertical lines (columns) from each frame:
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```bash
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uv run main.py test1.mkv --xcolumn 100 --output test1_column.png
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```
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**Row Mode** - Extract horizontal lines (rows) from each frame:
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```bash
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uv run main.py test1.mkv --yrow 200 --output test1_row.png
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```
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**Debug Mode** - Analyze changes and generate threshold graph:
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```bash
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uv run main.py test1.mkv --xcolumn 100 --output analysis --debug
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```
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**Custom Threshold** - Control compression by setting change threshold:
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```bash
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uv run main.py test1.mkv --xcolumn 100 --output test1_column.png --threshold 0.01
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```
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## Configure
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We use uv to handle pip dependencies. Install with:
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```bash
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uv sync
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```
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## Output
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- **Column mode**: Extracts vertical line at x-coordinate from each frame
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- Output dimensions: `(source_height, total_frames, 3)`
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- Width = number of frames, Height = source video height
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- **Row mode**: Extracts horizontal line at y-coordinate from each frame
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- Output dimensions: `(total_frames, source_width, 3)`
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- Width = source video width, Height = number of frames
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Each column/row in the output represents one frame from the input video, showing motion over time.
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## Advanced Features
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### Change Detection & Compression
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The implementation includes intelligent change detection that discards frames with minimal visual changes, creating more compact outputs that focus on motion:
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- **Automatic filtering**: Only frames with significant changes are included
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- **Configurable threshold**: Use `--threshold` (0-1) to control sensitivity
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- **Compression stats**: Shows how many frames were kept vs. skipped
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### Debug Mode
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Use `--debug` to analyze your video and determine optimal threshold values:
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```bash
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uv run main.py video.mp4 --xcolumn 500 --output analysis --debug
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```
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This generates:
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- **Change graph**: Visual plot of frame-to-frame changes over time
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- **Statistics**: Mean, max, min, and standard deviation of changes
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- **Threshold suggestions**: Recommended values with compression ratios
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### Threshold Selection Guide
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- **0.001-0.005**: High sensitivity, keeps most motion (10-30% compression)
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- **0.005-0.02**: Medium sensitivity, good balance (30-70% compression)
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- **0.02-0.1**: Low sensitivity, only major changes (70-95% compression)
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- **>0.1**: Very low sensitivity, minimal frames (95%+ compression)
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### Examples with Compression
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Extract with 75% compression (recommended starting point):
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```bash
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uv run main.py video.mp4 --xcolumn 320 --output compressed.png --threshold 0.01
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```
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Maximum compression for detecting only major scene changes:
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```bash
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uv run main.py video.mp4 --xcolumn 320 --output minimal.png --threshold 0.05
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``` |