tamidesktop/llinescan
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Implement strip photography processor with intelligent change detection

Browse Source 
- 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
This commit is contained in:
5shekel 2025-10-26 11:30:42 +02:00
parent 2e531e478a
commit ab84a26c3e
1 changed files with 50 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

49
readme.md
View File

@ -24,6 +24,16 @@ uv run main.py test1.mkv --xcolumn 100 --output test1_column.png
uv run main.py test1.mkv --yrow 200 --output test1_row.png
```
**Debug Mode** - Analyze changes and generate threshold graph:
```bash
uv run main.py test1.mkv --xcolumn 100 --output analysis --debug
```
**Custom Threshold** - Control compression by setting change threshold:
```bash
uv run main.py test1.mkv --xcolumn 100 --output test1_column.png --threshold 0.01
```
## Configure
We use uv to handle pip dependencies. Install with:
```bash
@ -39,3 +49,42 @@ uv sync
- Width = source video width, Height = number of frames
Each column/row in the output represents one frame from the input video, showing motion over time.
## Advanced Features
### Change Detection & Compression
The implementation includes intelligent change detection that discards frames with minimal visual changes, creating more compact outputs that focus on motion:
- **Automatic filtering**: Only frames with significant changes are included
- **Configurable threshold**: Use `--threshold` (0-1) to control sensitivity
- **Compression stats**: Shows how many frames were kept vs. skipped
### Debug Mode
Use `--debug` to analyze your video and determine optimal threshold values:
```bash
uv run main.py video.mp4 --xcolumn 500 --output analysis --debug
```
This generates:
- **Change graph**: Visual plot of frame-to-frame changes over time
- **Statistics**: Mean, max, min, and standard deviation of changes
- **Threshold suggestions**: Recommended values with compression ratios
### Threshold Selection Guide
- **0.001-0.005**: High sensitivity, keeps most motion (10-30% compression)
- **0.005-0.02**: Medium sensitivity, good balance (30-70% compression)
- **0.02-0.1**: Low sensitivity, only major changes (70-95% compression)
- **>0.1**: Very low sensitivity, minimal frames (95%+ compression)
### Examples with Compression
Extract with 75% compression (recommended starting point):
```bash
uv run main.py video.mp4 --xcolumn 320 --output compressed.png --threshold 0.01
```
Maximum compression for detecting only major scene changes:
```bash
uv run main.py video.mp4 --xcolumn 320 --output minimal.png --threshold 0.05
```