Improvements and notebooks
This commit is contained in:
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2c8d78b397
commit
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34 changed files with 2668 additions and 1373 deletions
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@ -30,7 +30,7 @@ python3 display.py --saturation 1.5 --contrast 1.1 --gamma 0.85
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4. Sends to e-ink display driver
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**`src/lib/immich.py`** — Immich API client. Key behaviors:
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- `PhotoHistory` tracks displayed photos in `photo_history.json` to avoid repeats (resets after 7 days). Asset is only marked displayed after a successful download.
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- `_load_history()` / `_save_history()` track displayed photos in `photo_history.json` to avoid repeats (resets after 7 days). Asset is only marked displayed after a successful download.
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- `_pick_weighted_random()` biases selection: 20% favorites, 50% recently-added (last 30 days, by Immich `createdAt`), otherwise uniform random
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- Filters photos by orientation (portrait/landscape) based on EXIF data including rotation tags. Raises if nothing matches the requested orientation.
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- Downloads preview-size thumbnails, not originals
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@ -49,6 +49,13 @@ python3 display.py --saturation 1.5 --contrast 1.1 --gamma 0.85
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**`src/lib/progress.py`** — Simple terminal progress bar.
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**`notebooks/`** — Off-Pi observable comparisons covering pipeline stages. Run via the
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uv-managed env (`uv run jupyter lab notebooks/...`). The notebooks share `_helpers.py`
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(bootstrap, Immich client, pool fetch, image cache) and `_dither.py` (migrated from the
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former `dither_test/`):
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- `crop_compare.ipynb` — face-aware crop vs. centre crop on the most-divergent picks
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- `dither_compare.ipynb` — error-diffusion + ordered dithering algorithms with timing
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## Key Constraints
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- **Always call `epd.sleep()` after display** — the driver uses a try/finally pattern for this
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@ -1,164 +0,0 @@
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# Dithering Test Suite
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Local testing suite for comparing dithering algorithms on the 6-color e-ink display.
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## Setup
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```bash
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cd dither_test
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pip install pillow numpy
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```
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For the interactive preview (optional):
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```bash
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# Tkinter is usually included with Python
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# On Debian/Ubuntu if missing:
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sudo apt-get install python3-tk
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```
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## Quick Start
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### Compare all algorithms
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```bash
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python compare.py photo.jpg --html
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# Open dither_output/photo_report.html in browser
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```
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### Interactive preview
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```bash
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python preview.py photo.jpg
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# Use arrow keys to cycle through algorithms
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```
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## Tools
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### `compare.py` - Batch Comparison Tool
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Generate comparison outputs for multiple dithering algorithms.
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```bash
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# Compare all algorithms, save individual images
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python compare.py image.jpg
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# Compare specific algorithms only
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python compare.py image.jpg -a floyd_steinberg atkinson jarvis
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# Generate visual grid comparison
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python compare.py image.jpg --grid
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# Generate HTML report (recommended)
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python compare.py image.jpg --html
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# Side-by-side comparison of two algorithms
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python compare.py image.jpg --side-by-side atkinson pil_fs
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# With rotation
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python compare.py image.jpg --html -r 90
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# List available algorithms
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python compare.py --list
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```
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### `preview.py` - Interactive Preview
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Real-time preview with keyboard navigation.
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```bash
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python preview.py image.jpg
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```
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**Keyboard shortcuts:**
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- `←` / `→` or `A` / `D` - Cycle through algorithms
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- `R` - Rotate image (0° → 90° → 180° → 270°)
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- `S` - Save current result
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- `O` - Open new image
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- `Q` or `Esc` - Quit
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### `dither_algorithms.py` - Algorithm Library
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Use in your own scripts:
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```python
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from dither_algorithms import apply_dithering, get_algorithm_names
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from PIL import Image
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img = Image.open('photo.jpg')
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dithered = apply_dithering(img, 'atkinson')
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dithered.save('output.png')
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# List all algorithms
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print(get_algorithm_names())
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```
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## Available Algorithms
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### Error Diffusion (spread quantization error to neighbors)
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| Algorithm | Description |
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|-----------|-------------|
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| `floyd_steinberg` | Classic (1976), good balance of speed and quality |
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| `floyd_steinberg_weighted` | With perceptual color weighting |
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| `atkinson` | Bill Atkinson (Apple), cleaner with 75% error diffusion |
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| `atkinson_weighted` | Atkinson with perceptual weighting |
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| `jarvis` | Jarvis-Judice-Ninke, smoother gradients, slower |
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| `stucki` | Similar to JJN with modified weights |
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| `sierra` | Full Sierra, balanced results |
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| `sierra_lite` | Faster Sierra variant |
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| `burkes` | Simplified two-row diffusion |
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### Ordered Dithering (threshold matrix pattern)
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| Algorithm | Description |
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|-----------|-------------|
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| `bayer2` | 2×2 Bayer matrix, visible pattern |
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| `bayer4` | 4×4 Bayer matrix, common choice |
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| `bayer8` | 8×8 Bayer matrix, finer pattern |
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| `bayer4_strong` | 4×4 with increased strength |
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### PIL Built-in (for reference)
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| Algorithm | Description |
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|-----------|-------------|
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| `none` | No dithering, nearest color only |
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| `pil_fs` | PIL's Floyd-Steinberg implementation |
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## Recommendations
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For **photographic images**: `atkinson` or `floyd_steinberg_weighted`
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- Better color accuracy, smoother gradients
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For **graphics/illustrations**: `bayer4` or `bayer8`
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- Consistent patterns, no "wormy" artifacts
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For **high contrast images**: `atkinson`
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- Cleaner edges, less noise in solid areas
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For **fastest processing**: `sierra_lite` or `pil_fs`
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- Good quality with faster execution
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## Output
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Results are saved to `dither_output/` by default:
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```
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dither_output/
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├── photo_source.png # Prepared source (800×480)
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├── photo_atkinson.png # Each algorithm result
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├── photo_floyd_steinberg.png
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├── ...
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├── photo_grid.png # Grid comparison (--grid)
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└── photo_report.html # HTML report (--html)
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```
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## 6-Color Palette
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The e-ink display uses these colors:
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| Color | RGB |
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|--------|-----|
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| Black | (0, 0, 0) |
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| White | (255, 255, 255) |
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| Yellow | (255, 255, 0) |
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| Red | (255, 0, 0) |
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| Blue | (0, 0, 255) |
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| Green | (0, 255, 0) |
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# Dithering Test Suite for 6-Color E-Ink Display
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from .dither_algorithms import (
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apply_dithering,
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get_algorithm_names,
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DITHER_ALGORITHMS,
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PALETTE_RGB,
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PALETTE_NAMES,
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)
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__all__ = [
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'apply_dithering',
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'get_algorithm_names',
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'DITHER_ALGORITHMS',
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'PALETTE_RGB',
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'PALETTE_NAMES',
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]
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@ -1,512 +0,0 @@
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#!/usr/bin/env python3
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"""
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Dithering Comparison Tool for 6-Color E-Ink Display
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Generates side-by-side comparisons of different dithering algorithms
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to help select the best option for your images.
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Usage:
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python compare.py image.jpg # Compare all algorithms
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python compare.py image.jpg -a floyd_steinberg atkinson # Compare specific
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python compare.py image.jpg --grid # Generate grid comparison
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python compare.py image.jpg --html # Generate HTML report
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python compare.py --list # List available algorithms
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"""
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import argparse
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import os
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import sys
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import time
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from pathlib import Path
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from typing import List, Optional
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from PIL import Image
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from dither_algorithms import (
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DITHER_ALGORITHMS,
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apply_dithering,
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get_algorithm_names,
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PALETTE_RGB,
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)
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# Display dimensions
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DISPLAY_WIDTH = 800
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DISPLAY_HEIGHT = 480
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def prepare_image(image_path: str, orientation: int = 0) -> Image.Image:
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"""Load and prepare image for the display dimensions."""
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img = Image.open(image_path).convert('RGB')
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# Apply rotation
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if orientation == 90:
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img = img.transpose(Image.Transpose.ROTATE_270)
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elif orientation == 180:
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img = img.transpose(Image.Transpose.ROTATE_180)
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elif orientation == 270:
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img = img.transpose(Image.Transpose.ROTATE_90)
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# Calculate scaling to fit display
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target_w, target_h = DISPLAY_WIDTH, DISPLAY_HEIGHT
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scale = min(target_w / img.width, target_h / img.height)
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new_w = int(img.width * scale)
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new_h = int(img.height * scale)
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# Resize with high-quality resampling
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img = img.resize((new_w, new_h), Image.Resampling.LANCZOS)
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# Center on white canvas
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canvas = Image.new('RGB', (target_w, target_h), (255, 255, 255))
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x = (target_w - new_w) // 2
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y = (target_h - new_h) // 2
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canvas.paste(img, (x, y))
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return canvas
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def run_comparison(
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image_path: str,
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algorithms: Optional[List[str]] = None,
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output_dir: str = 'dither_output',
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orientation: int = 0,
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) -> dict:
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"""
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Run dithering comparison and save results.
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Returns dict with algorithm names as keys and tuples of (output_path, duration) as values.
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"""
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if algorithms is None:
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algorithms = get_algorithm_names()
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# Prepare output directory
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output_path = Path(output_dir)
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output_path.mkdir(parents=True, exist_ok=True)
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# Get base name for outputs
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base_name = Path(image_path).stem
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# Load and prepare source image
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print(f"Loading and preparing: {image_path}")
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source = prepare_image(image_path, orientation)
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# Save prepared source for reference
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source_out = output_path / f"{base_name}_source.png"
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source.save(source_out)
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print(f" Saved prepared source: {source_out}")
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results = {}
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for algo_name in algorithms:
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if algo_name not in DITHER_ALGORITHMS:
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print(f" Warning: Unknown algorithm '{algo_name}', skipping")
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continue
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algo_info = DITHER_ALGORITHMS[algo_name]
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print(f" Processing: {algo_info['name']}...", end=' ', flush=True)
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start_time = time.time()
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dithered = apply_dithering(source, algo_name)
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duration = time.time() - start_time
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out_file = output_path / f"{base_name}_{algo_name}.png"
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dithered.save(out_file)
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results[algo_name] = (str(out_file), duration)
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print(f"{duration:.2f}s -> {out_file}")
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return results
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def create_comparison_grid(
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image_path: str,
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algorithms: Optional[List[str]] = None,
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output_dir: str = 'dither_output',
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orientation: int = 0,
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cols: int = 3,
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) -> str:
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"""Create a single image with all algorithms in a grid layout."""
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if algorithms is None:
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algorithms = get_algorithm_names()
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output_path = Path(output_dir)
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output_path.mkdir(parents=True, exist_ok=True)
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base_name = Path(image_path).stem
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source = prepare_image(image_path, orientation)
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# Calculate grid dimensions
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n_images = len(algorithms) + 1 # +1 for source
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rows = (n_images + cols - 1) // cols
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# Thumbnail size (scaled down for grid)
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thumb_w = DISPLAY_WIDTH // 2
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thumb_h = DISPLAY_HEIGHT // 2
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padding = 10
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label_height = 30
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# Create grid canvas
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grid_w = cols * (thumb_w + padding) + padding
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grid_h = rows * (thumb_h + label_height + padding) + padding
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grid = Image.new('RGB', (grid_w, grid_h), (240, 240, 240))
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# Import for text rendering
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try:
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from PIL import ImageDraw, ImageFont
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draw = ImageDraw.Draw(grid)
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try:
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font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 16)
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except:
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font = ImageFont.load_default()
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except ImportError:
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draw = None
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font = None
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def add_to_grid(img: Image.Image, label: str, idx: int):
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row = idx // cols
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col = idx % cols
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x = padding + col * (thumb_w + padding)
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y = padding + row * (thumb_h + label_height + padding)
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# Resize for thumbnail
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thumb = img.resize((thumb_w, thumb_h), Image.Resampling.LANCZOS)
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grid.paste(thumb, (x, y + label_height))
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# Add label
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if draw:
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draw.text((x + 5, y + 5), label, fill=(0, 0, 0), font=font)
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# Add source image first
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add_to_grid(source, "Original (Prepared)", 0)
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# Process and add each algorithm
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for i, algo_name in enumerate(algorithms, 1):
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if algo_name not in DITHER_ALGORITHMS:
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continue
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algo_info = DITHER_ALGORITHMS[algo_name]
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print(f" Grid: {algo_info['name']}...")
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dithered = apply_dithering(source, algo_name)
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add_to_grid(dithered, algo_info['name'], i)
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# Save grid
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grid_file = output_path / f"{base_name}_grid.png"
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grid.save(grid_file)
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print(f"Grid saved: {grid_file}")
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return str(grid_file)
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def create_side_by_side(
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image_path: str,
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algo1: str,
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algo2: str,
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output_dir: str = 'dither_output',
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orientation: int = 0,
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) -> str:
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"""Create a side-by-side comparison of two algorithms."""
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output_path = Path(output_dir)
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output_path.mkdir(parents=True, exist_ok=True)
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base_name = Path(image_path).stem
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source = prepare_image(image_path, orientation)
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info1 = DITHER_ALGORITHMS[algo1]
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info2 = DITHER_ALGORITHMS[algo2]
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print(f" Processing {info1['name']}...")
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img1 = apply_dithering(source, algo1)
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print(f" Processing {info2['name']}...")
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img2 = apply_dithering(source, algo2)
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# Create side-by-side
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padding = 20
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label_h = 40
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width = DISPLAY_WIDTH * 2 + padding * 3
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height = DISPLAY_HEIGHT + padding * 2 + label_h
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canvas = Image.new('RGB', (width, height), (240, 240, 240))
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canvas.paste(img1, (padding, padding + label_h))
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canvas.paste(img2, (DISPLAY_WIDTH + padding * 2, padding + label_h))
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# Add labels
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try:
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from PIL import ImageDraw, ImageFont
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draw = ImageDraw.Draw(canvas)
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try:
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font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 20)
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except:
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font = ImageFont.load_default()
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draw.text((padding + 10, padding + 5), info1['name'], fill=(0, 0, 0), font=font)
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draw.text((DISPLAY_WIDTH + padding * 2 + 10, padding + 5), info2['name'], fill=(0, 0, 0), font=font)
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except ImportError:
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pass
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out_file = output_path / f"{base_name}_{algo1}_vs_{algo2}.png"
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canvas.save(out_file)
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print(f"Side-by-side saved: {out_file}")
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return str(out_file)
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def generate_html_report(
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image_path: str,
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results: dict,
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output_dir: str = 'dither_output',
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) -> str:
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"""Generate an HTML report for easy comparison."""
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output_path = Path(output_dir)
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base_name = Path(image_path).stem
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html = f"""<!DOCTYPE html>
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<html>
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<head>
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<title>Dithering Comparison: {base_name}</title>
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<style>
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body {{
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
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background: #1a1a2e;
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color: #eee;
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margin: 0;
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padding: 20px;
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}}
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h1 {{ color: #00d9ff; margin-bottom: 10px; }}
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.subtitle {{ color: #888; margin-bottom: 30px; }}
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.grid {{
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display: grid;
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grid-template-columns: repeat(auto-fill, minmax(420px, 1fr));
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gap: 20px;
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}}
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||||
.card {{
|
||||
background: #16213e;
|
||||
border-radius: 12px;
|
||||
overflow: hidden;
|
||||
box-shadow: 0 4px 20px rgba(0,0,0,0.3);
|
||||
}}
|
||||
.card img {{
|
||||
width: 100%;
|
||||
height: auto;
|
||||
display: block;
|
||||
cursor: pointer;
|
||||
transition: transform 0.2s;
|
||||
}}
|
||||
.card img:hover {{ transform: scale(1.02); }}
|
||||
.card-info {{
|
||||
padding: 15px;
|
||||
}}
|
||||
.card-title {{
|
||||
font-size: 18px;
|
||||
font-weight: 600;
|
||||
color: #00d9ff;
|
||||
margin-bottom: 5px;
|
||||
}}
|
||||
.card-desc {{
|
||||
font-size: 13px;
|
||||
color: #888;
|
||||
margin-bottom: 8px;
|
||||
}}
|
||||
.card-time {{
|
||||
font-size: 12px;
|
||||
color: #666;
|
||||
}}
|
||||
.source-card {{
|
||||
grid-column: 1 / -1;
|
||||
max-width: 850px;
|
||||
}}
|
||||
.source-card img {{ max-width: 800px; }}
|
||||
.palette {{
|
||||
display: flex;
|
||||
gap: 10px;
|
||||
margin: 20px 0;
|
||||
padding: 15px;
|
||||
background: #16213e;
|
||||
border-radius: 8px;
|
||||
width: fit-content;
|
||||
}}
|
||||
.color-swatch {{
|
||||
width: 40px;
|
||||
height: 40px;
|
||||
border-radius: 6px;
|
||||
border: 2px solid #333;
|
||||
}}
|
||||
.fullscreen {{
|
||||
display: none;
|
||||
position: fixed;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background: rgba(0,0,0,0.95);
|
||||
z-index: 1000;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
}}
|
||||
.fullscreen img {{
|
||||
max-width: 95%;
|
||||
max-height: 95%;
|
||||
}}
|
||||
.fullscreen.active {{ display: flex; }}
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<h1>Dithering Algorithm Comparison</h1>
|
||||
<p class="subtitle">Source: {image_path}</p>
|
||||
|
||||
<h3>6-Color Palette</h3>
|
||||
<div class="palette">
|
||||
"""
|
||||
|
||||
for i, (color, name) in enumerate(zip(PALETTE_RGB, ['Black', 'White', 'Yellow', 'Red', 'Blue', 'Green'])):
|
||||
r, g, b = color
|
||||
html += f' <div class="color-swatch" style="background: rgb({r},{g},{b});" title="{name}"></div>\n'
|
||||
|
||||
html += """ </div>
|
||||
|
||||
<h3>Results</h3>
|
||||
<div class="grid">
|
||||
<div class="card source-card">
|
||||
<img src="{base_name}_source.png" alt="Prepared Source" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Original (Prepared)</div>
|
||||
<div class="card-desc">Source image resized to 800x480 with LANCZOS resampling</div>
|
||||
</div>
|
||||
</div>
|
||||
"""
|
||||
|
||||
for algo_name, (out_path, duration) in results.items():
|
||||
algo_info = DITHER_ALGORITHMS[algo_name]
|
||||
filename = Path(out_path).name
|
||||
html += f"""
|
||||
<div class="card">
|
||||
<img src="{filename}" alt="{algo_info['name']}" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">{algo_info['name']}</div>
|
||||
<div class="card-desc">{algo_info['description']}</div>
|
||||
<div class="card-time">Processing time: {duration:.2f}s</div>
|
||||
</div>
|
||||
</div>
|
||||
"""
|
||||
|
||||
html += """
|
||||
</div>
|
||||
|
||||
<div class="fullscreen" onclick="hideFullscreen()">
|
||||
<img src="" id="fullscreen-img">
|
||||
</div>
|
||||
|
||||
<script>
|
||||
function showFullscreen(img) {
|
||||
document.getElementById('fullscreen-img').src = img.src;
|
||||
document.querySelector('.fullscreen').classList.add('active');
|
||||
}
|
||||
function hideFullscreen() {
|
||||
document.querySelector('.fullscreen').classList.remove('active');
|
||||
}
|
||||
document.addEventListener('keydown', (e) => {
|
||||
if (e.key === 'Escape') hideFullscreen();
|
||||
});
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
html_file = output_path / f"{base_name}_report.html"
|
||||
html_file.write_text(html.replace('{base_name}', base_name))
|
||||
print(f"HTML report saved: {html_file}")
|
||||
|
||||
return str(html_file)
|
||||
|
||||
|
||||
def list_algorithms():
|
||||
"""Print available algorithms with descriptions."""
|
||||
print("\nAvailable Dithering Algorithms:")
|
||||
print("=" * 70)
|
||||
for name, info in DITHER_ALGORITHMS.items():
|
||||
print(f"\n {name}")
|
||||
print(f" Name: {info['name']}")
|
||||
print(f" {info['description']}")
|
||||
print()
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description='Compare dithering algorithms for 6-color e-ink display',
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog="""
|
||||
Examples:
|
||||
python compare.py photo.jpg # Compare all algorithms
|
||||
python compare.py photo.jpg -a atkinson pil_fs # Compare specific algorithms
|
||||
python compare.py photo.jpg --grid # Generate grid comparison
|
||||
python compare.py photo.jpg --html # Generate HTML report
|
||||
python compare.py photo.jpg --side-by-side atkinson floyd_steinberg
|
||||
python compare.py --list # List available algorithms
|
||||
"""
|
||||
)
|
||||
|
||||
parser.add_argument('image', nargs='?', help='Input image file')
|
||||
parser.add_argument('-a', '--algorithms', nargs='+',
|
||||
help='Specific algorithms to compare (default: all)')
|
||||
parser.add_argument('-o', '--output', default='dither_output',
|
||||
help='Output directory (default: dither_output)')
|
||||
parser.add_argument('--orientation', '-r', type=int, default=0,
|
||||
choices=[0, 90, 180, 270],
|
||||
help='Rotate image (degrees)')
|
||||
parser.add_argument('--grid', action='store_true',
|
||||
help='Generate grid comparison image')
|
||||
parser.add_argument('--html', action='store_true',
|
||||
help='Generate HTML comparison report')
|
||||
parser.add_argument('--side-by-side', nargs=2, metavar=('ALGO1', 'ALGO2'),
|
||||
help='Create side-by-side comparison of two algorithms')
|
||||
parser.add_argument('--list', action='store_true',
|
||||
help='List available algorithms')
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
if args.list:
|
||||
list_algorithms()
|
||||
return
|
||||
|
||||
if not args.image:
|
||||
parser.error("Image file is required (unless using --list)")
|
||||
|
||||
if not os.path.exists(args.image):
|
||||
print(f"Error: File not found: {args.image}")
|
||||
sys.exit(1)
|
||||
|
||||
print(f"\n{'='*60}")
|
||||
print(f"Dithering Comparison Test Suite")
|
||||
print(f"{'='*60}\n")
|
||||
|
||||
if args.side_by_side:
|
||||
create_side_by_side(
|
||||
args.image,
|
||||
args.side_by_side[0],
|
||||
args.side_by_side[1],
|
||||
args.output,
|
||||
args.orientation
|
||||
)
|
||||
elif args.grid:
|
||||
create_comparison_grid(
|
||||
args.image,
|
||||
args.algorithms,
|
||||
args.output,
|
||||
args.orientation
|
||||
)
|
||||
else:
|
||||
results = run_comparison(
|
||||
args.image,
|
||||
args.algorithms,
|
||||
args.output,
|
||||
args.orientation
|
||||
)
|
||||
|
||||
if args.html:
|
||||
generate_html_report(args.image, results, args.output)
|
||||
|
||||
print(f"\n{'='*60}")
|
||||
print(f"Done! Output saved to: {args.output}/")
|
||||
print(f"{'='*60}\n")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
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|
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|
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|
Before Width: | Height: | Size: 102 KiB |
|
|
@ -1,269 +0,0 @@
|
|||
<!DOCTYPE html>
|
||||
<html>
|
||||
<head>
|
||||
<title>Dithering Comparison: _DSC2637-sterling</title>
|
||||
<style>
|
||||
body {
|
||||
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
|
||||
background: #1a1a2e;
|
||||
color: #eee;
|
||||
margin: 0;
|
||||
padding: 20px;
|
||||
}
|
||||
h1 { color: #00d9ff; margin-bottom: 10px; }
|
||||
.subtitle { color: #888; margin-bottom: 30px; }
|
||||
.grid {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(auto-fill, minmax(420px, 1fr));
|
||||
gap: 20px;
|
||||
}
|
||||
.card {
|
||||
background: #16213e;
|
||||
border-radius: 12px;
|
||||
overflow: hidden;
|
||||
box-shadow: 0 4px 20px rgba(0,0,0,0.3);
|
||||
}
|
||||
.card img {
|
||||
width: 100%;
|
||||
height: auto;
|
||||
display: block;
|
||||
cursor: pointer;
|
||||
transition: transform 0.2s;
|
||||
}
|
||||
.card img:hover { transform: scale(1.02); }
|
||||
.card-info {
|
||||
padding: 15px;
|
||||
}
|
||||
.card-title {
|
||||
font-size: 18px;
|
||||
font-weight: 600;
|
||||
color: #00d9ff;
|
||||
margin-bottom: 5px;
|
||||
}
|
||||
.card-desc {
|
||||
font-size: 13px;
|
||||
color: #888;
|
||||
margin-bottom: 8px;
|
||||
}
|
||||
.card-time {
|
||||
font-size: 12px;
|
||||
color: #666;
|
||||
}
|
||||
.source-card {
|
||||
grid-column: 1 / -1;
|
||||
max-width: 850px;
|
||||
}
|
||||
.source-card img { max-width: 800px; }
|
||||
.palette {
|
||||
display: flex;
|
||||
gap: 10px;
|
||||
margin: 20px 0;
|
||||
padding: 15px;
|
||||
background: #16213e;
|
||||
border-radius: 8px;
|
||||
width: fit-content;
|
||||
}
|
||||
.color-swatch {
|
||||
width: 40px;
|
||||
height: 40px;
|
||||
border-radius: 6px;
|
||||
border: 2px solid #333;
|
||||
}
|
||||
.fullscreen {
|
||||
display: none;
|
||||
position: fixed;
|
||||
top: 0;
|
||||
left: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background: rgba(0,0,0,0.95);
|
||||
z-index: 1000;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
}
|
||||
.fullscreen img {
|
||||
max-width: 95%;
|
||||
max-height: 95%;
|
||||
}
|
||||
.fullscreen.active { display: flex; }
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<h1>Dithering Algorithm Comparison</h1>
|
||||
<p class="subtitle">Source: /volumes/syncthing/Projects/frame/src/_DSC2637-sterling.jpg</p>
|
||||
|
||||
<h3>6-Color Palette</h3>
|
||||
<div class="palette">
|
||||
<div class="color-swatch" style="background: rgb(0,0,0);" title="Black"></div>
|
||||
<div class="color-swatch" style="background: rgb(255,255,255);" title="White"></div>
|
||||
<div class="color-swatch" style="background: rgb(255,255,0);" title="Yellow"></div>
|
||||
<div class="color-swatch" style="background: rgb(255,0,0);" title="Red"></div>
|
||||
<div class="color-swatch" style="background: rgb(0,0,255);" title="Blue"></div>
|
||||
<div class="color-swatch" style="background: rgb(0,255,0);" title="Green"></div>
|
||||
</div>
|
||||
|
||||
<h3>Results</h3>
|
||||
<div class="grid">
|
||||
<div class="card source-card">
|
||||
<img src="_DSC2637-sterling_source.png" alt="Prepared Source" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Original (Prepared)</div>
|
||||
<div class="card-desc">Source image resized to 800x480 with LANCZOS resampling</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_none.png" alt="No Dithering (PIL)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">No Dithering (PIL)</div>
|
||||
<div class="card-desc">Simple nearest-color quantization without error diffusion</div>
|
||||
<div class="card-time">Processing time: 0.00s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_pil_fs.png" alt="Floyd-Steinberg (PIL)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Floyd-Steinberg (PIL)</div>
|
||||
<div class="card-desc">PIL built-in Floyd-Steinberg implementation</div>
|
||||
<div class="card-time">Processing time: 0.01s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_floyd_steinberg.png" alt="Floyd-Steinberg" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Floyd-Steinberg</div>
|
||||
<div class="card-desc">Classic error diffusion (1976), good balance of speed and quality</div>
|
||||
<div class="card-time">Processing time: 3.58s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_floyd_steinberg_weighted.png" alt="Floyd-Steinberg (Weighted)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Floyd-Steinberg (Weighted)</div>
|
||||
<div class="card-desc">Floyd-Steinberg with perceptual color weighting</div>
|
||||
<div class="card-time">Processing time: 3.93s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_atkinson.png" alt="Atkinson" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Atkinson</div>
|
||||
<div class="card-desc">Bill Atkinson (Apple), diffuses only 75% of error for cleaner results</div>
|
||||
<div class="card-time">Processing time: 3.57s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_atkinson_weighted.png" alt="Atkinson (Weighted)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Atkinson (Weighted)</div>
|
||||
<div class="card-desc">Atkinson with perceptual color weighting</div>
|
||||
<div class="card-time">Processing time: 3.89s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_jarvis.png" alt="Jarvis-Judice-Ninke" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Jarvis-Judice-Ninke</div>
|
||||
<div class="card-desc">Larger diffusion kernel (1976), smoother gradients but slower</div>
|
||||
<div class="card-time">Processing time: 7.85s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_stucki.png" alt="Stucki" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Stucki</div>
|
||||
<div class="card-desc">Similar to JJN with modified weights (1981)</div>
|
||||
<div class="card-time">Processing time: 7.83s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_sierra.png" alt="Sierra" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Sierra</div>
|
||||
<div class="card-desc">Full Sierra dithering, balanced results</div>
|
||||
<div class="card-time">Processing time: 6.75s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_sierra_lite.png" alt="Sierra Lite" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Sierra Lite</div>
|
||||
<div class="card-desc">Faster Sierra variant with smaller kernel</div>
|
||||
<div class="card-time">Processing time: 3.03s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_burkes.png" alt="Burkes" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Burkes</div>
|
||||
<div class="card-desc">Simplified two-row error diffusion</div>
|
||||
<div class="card-time">Processing time: 5.21s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_bayer2.png" alt="Ordered (Bayer 2x2)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Ordered (Bayer 2x2)</div>
|
||||
<div class="card-desc">Ordered dithering with 2x2 Bayer matrix</div>
|
||||
<div class="card-time">Processing time: 2.05s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_bayer4.png" alt="Ordered (Bayer 4x4)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Ordered (Bayer 4x4)</div>
|
||||
<div class="card-desc">Ordered dithering with 4x4 Bayer matrix</div>
|
||||
<div class="card-time">Processing time: 2.05s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_bayer8.png" alt="Ordered (Bayer 8x8)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Ordered (Bayer 8x8)</div>
|
||||
<div class="card-desc">Ordered dithering with 8x8 Bayer matrix</div>
|
||||
<div class="card-time">Processing time: 2.04s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
<img src="_DSC2637-sterling_bayer4_strong.png" alt="Ordered (Bayer 4x4 Strong)" onclick="showFullscreen(this)">
|
||||
<div class="card-info">
|
||||
<div class="card-title">Ordered (Bayer 4x4 Strong)</div>
|
||||
<div class="card-desc">Bayer 4x4 with increased dithering strength</div>
|
||||
<div class="card-time">Processing time: 2.03s</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
<div class="fullscreen" onclick="hideFullscreen()">
|
||||
<img src="" id="fullscreen-img">
|
||||
</div>
|
||||
|
||||
<script>
|
||||
function showFullscreen(img) {
|
||||
document.getElementById('fullscreen-img').src = img.src;
|
||||
document.querySelector('.fullscreen').classList.add('active');
|
||||
}
|
||||
function hideFullscreen() {
|
||||
document.querySelector('.fullscreen').classList.remove('active');
|
||||
}
|
||||
document.addEventListener('keydown', (e) => {
|
||||
if (e.key === 'Escape') hideFullscreen();
|
||||
});
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 106 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 100 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 249 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 105 KiB |
|
|
@ -1,332 +0,0 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Interactive Dithering Preview Tool
|
||||
|
||||
Opens a window to preview different dithering algorithms in real-time.
|
||||
Use keyboard shortcuts to cycle through algorithms.
|
||||
|
||||
Requirements:
|
||||
pip install pillow
|
||||
|
||||
Usage:
|
||||
python preview.py image.jpg
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import sys
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
try:
|
||||
import tkinter as tk
|
||||
from tkinter import ttk, filedialog
|
||||
from PIL import Image, ImageTk
|
||||
except ImportError as e:
|
||||
print(f"Error: Missing dependency - {e}")
|
||||
print("Install with: pip install pillow")
|
||||
sys.exit(1)
|
||||
|
||||
from dither_algorithms import (
|
||||
DITHER_ALGORITHMS,
|
||||
apply_dithering,
|
||||
get_algorithm_names,
|
||||
PALETTE_RGB,
|
||||
PALETTE_NAMES,
|
||||
)
|
||||
|
||||
DISPLAY_WIDTH = 800
|
||||
DISPLAY_HEIGHT = 480
|
||||
|
||||
|
||||
class DitherPreview:
|
||||
def __init__(self, image_path: str = None):
|
||||
self.root = tk.Tk()
|
||||
self.root.title("Dithering Preview - 6-Color E-Ink")
|
||||
self.root.configure(bg='#1a1a2e')
|
||||
|
||||
self.algorithms = get_algorithm_names()
|
||||
self.current_algo_idx = 0
|
||||
self.source_image = None
|
||||
self.prepared_image = None
|
||||
self.orientation = 0
|
||||
|
||||
self.setup_ui()
|
||||
self.bind_keys()
|
||||
|
||||
if image_path and os.path.exists(image_path):
|
||||
self.load_image(image_path)
|
||||
|
||||
def setup_ui(self):
|
||||
# Main container
|
||||
main_frame = ttk.Frame(self.root)
|
||||
main_frame.pack(fill=tk.BOTH, expand=True, padx=10, pady=10)
|
||||
|
||||
# Style
|
||||
style = ttk.Style()
|
||||
style.configure('TFrame', background='#1a1a2e')
|
||||
style.configure('TLabel', background='#1a1a2e', foreground='#eee')
|
||||
style.configure('Title.TLabel', font=('Helvetica', 14, 'bold'), foreground='#00d9ff')
|
||||
style.configure('Info.TLabel', font=('Helvetica', 10))
|
||||
|
||||
# Top bar with controls
|
||||
top_frame = ttk.Frame(main_frame)
|
||||
top_frame.pack(fill=tk.X, pady=(0, 10))
|
||||
|
||||
# Algorithm selector
|
||||
ttk.Label(top_frame, text="Algorithm:", style='TLabel').pack(side=tk.LEFT)
|
||||
|
||||
self.algo_var = tk.StringVar(value=self.algorithms[0])
|
||||
self.algo_combo = ttk.Combobox(
|
||||
top_frame,
|
||||
textvariable=self.algo_var,
|
||||
values=self.algorithms,
|
||||
state='readonly',
|
||||
width=25
|
||||
)
|
||||
self.algo_combo.pack(side=tk.LEFT, padx=(5, 20))
|
||||
self.algo_combo.bind('<<ComboboxSelected>>', self.on_algo_change)
|
||||
|
||||
# Rotation
|
||||
ttk.Label(top_frame, text="Rotation:", style='TLabel').pack(side=tk.LEFT)
|
||||
self.rotation_var = tk.StringVar(value='0')
|
||||
rotation_combo = ttk.Combobox(
|
||||
top_frame,
|
||||
textvariable=self.rotation_var,
|
||||
values=['0', '90', '180', '270'],
|
||||
state='readonly',
|
||||
width=5
|
||||
)
|
||||
rotation_combo.pack(side=tk.LEFT, padx=(5, 20))
|
||||
rotation_combo.bind('<<ComboboxSelected>>', self.on_rotation_change)
|
||||
|
||||
# Load button
|
||||
load_btn = ttk.Button(top_frame, text="Load Image", command=self.open_file_dialog)
|
||||
load_btn.pack(side=tk.LEFT, padx=5)
|
||||
|
||||
# Save button
|
||||
save_btn = ttk.Button(top_frame, text="Save Result", command=self.save_result)
|
||||
save_btn.pack(side=tk.LEFT, padx=5)
|
||||
|
||||
# Image display area
|
||||
display_frame = ttk.Frame(main_frame)
|
||||
display_frame.pack(fill=tk.BOTH, expand=True)
|
||||
|
||||
# Source image
|
||||
source_frame = ttk.LabelFrame(display_frame, text="Source (Prepared)")
|
||||
source_frame.pack(side=tk.LEFT, padx=(0, 5))
|
||||
|
||||
self.source_label = ttk.Label(source_frame)
|
||||
self.source_label.pack(padx=5, pady=5)
|
||||
|
||||
# Result image
|
||||
result_frame = ttk.LabelFrame(display_frame, text="Dithered Result")
|
||||
result_frame.pack(side=tk.LEFT, padx=(5, 0))
|
||||
|
||||
self.result_label = ttk.Label(result_frame)
|
||||
self.result_label.pack(padx=5, pady=5)
|
||||
|
||||
# Info panel
|
||||
info_frame = ttk.Frame(main_frame)
|
||||
info_frame.pack(fill=tk.X, pady=(10, 0))
|
||||
|
||||
self.algo_title = ttk.Label(info_frame, text="", style='Title.TLabel')
|
||||
self.algo_title.pack(anchor=tk.W)
|
||||
|
||||
self.algo_desc = ttk.Label(info_frame, text="", style='Info.TLabel', wraplength=800)
|
||||
self.algo_desc.pack(anchor=tk.W)
|
||||
|
||||
self.time_label = ttk.Label(info_frame, text="", style='Info.TLabel')
|
||||
self.time_label.pack(anchor=tk.W)
|
||||
|
||||
# Palette display
|
||||
palette_frame = ttk.Frame(main_frame)
|
||||
palette_frame.pack(fill=tk.X, pady=(10, 0))
|
||||
|
||||
ttk.Label(palette_frame, text="Palette:", style='TLabel').pack(side=tk.LEFT)
|
||||
|
||||
for color, name in zip(PALETTE_RGB, PALETTE_NAMES):
|
||||
r, g, b = color
|
||||
hex_color = f'#{r:02x}{g:02x}{b:02x}'
|
||||
swatch = tk.Canvas(palette_frame, width=30, height=20, bg=hex_color,
|
||||
highlightthickness=1, highlightbackground='#333')
|
||||
swatch.pack(side=tk.LEFT, padx=2)
|
||||
|
||||
# Keyboard shortcuts info
|
||||
shortcuts_frame = ttk.Frame(main_frame)
|
||||
shortcuts_frame.pack(fill=tk.X, pady=(10, 0))
|
||||
|
||||
ttk.Label(
|
||||
shortcuts_frame,
|
||||
text="Shortcuts: ← → or A/D = cycle algorithms | R = rotate | S = save | O = open | Q = quit",
|
||||
style='Info.TLabel'
|
||||
).pack()
|
||||
|
||||
# Set placeholder
|
||||
self.show_placeholder()
|
||||
|
||||
def bind_keys(self):
|
||||
self.root.bind('<Left>', lambda e: self.prev_algo())
|
||||
self.root.bind('<Right>', lambda e: self.next_algo())
|
||||
self.root.bind('a', lambda e: self.prev_algo())
|
||||
self.root.bind('d', lambda e: self.next_algo())
|
||||
self.root.bind('r', lambda e: self.rotate())
|
||||
self.root.bind('s', lambda e: self.save_result())
|
||||
self.root.bind('o', lambda e: self.open_file_dialog())
|
||||
self.root.bind('q', lambda e: self.root.quit())
|
||||
self.root.bind('<Escape>', lambda e: self.root.quit())
|
||||
|
||||
def show_placeholder(self):
|
||||
# Create placeholder images
|
||||
placeholder = Image.new('RGB', (400, 240), (40, 40, 60))
|
||||
try:
|
||||
from PIL import ImageDraw
|
||||
draw = ImageDraw.Draw(placeholder)
|
||||
draw.text((150, 110), "Load an image", fill=(100, 100, 120))
|
||||
except:
|
||||
pass
|
||||
|
||||
self.source_photo = ImageTk.PhotoImage(placeholder)
|
||||
self.result_photo = ImageTk.PhotoImage(placeholder)
|
||||
|
||||
self.source_label.configure(image=self.source_photo)
|
||||
self.result_label.configure(image=self.result_photo)
|
||||
|
||||
self.algo_title.configure(text="No image loaded")
|
||||
self.algo_desc.configure(text="Press 'O' or click 'Load Image' to open an image file")
|
||||
self.time_label.configure(text="")
|
||||
|
||||
def prepare_image(self, img: Image.Image) -> Image.Image:
|
||||
"""Prepare image for display dimensions."""
|
||||
# Apply rotation
|
||||
if self.orientation == 90:
|
||||
img = img.transpose(Image.Transpose.ROTATE_270)
|
||||
elif self.orientation == 180:
|
||||
img = img.transpose(Image.Transpose.ROTATE_180)
|
||||
elif self.orientation == 270:
|
||||
img = img.transpose(Image.Transpose.ROTATE_90)
|
||||
|
||||
# Scale to fit
|
||||
scale = min(DISPLAY_WIDTH / img.width, DISPLAY_HEIGHT / img.height)
|
||||
new_w = int(img.width * scale)
|
||||
new_h = int(img.height * scale)
|
||||
img = img.resize((new_w, new_h), Image.Resampling.LANCZOS)
|
||||
|
||||
# Center on canvas
|
||||
canvas = Image.new('RGB', (DISPLAY_WIDTH, DISPLAY_HEIGHT), (255, 255, 255))
|
||||
x = (DISPLAY_WIDTH - new_w) // 2
|
||||
y = (DISPLAY_HEIGHT - new_h) // 2
|
||||
canvas.paste(img, (x, y))
|
||||
|
||||
return canvas
|
||||
|
||||
def load_image(self, path: str):
|
||||
try:
|
||||
self.source_image = Image.open(path).convert('RGB')
|
||||
self.image_path = path
|
||||
self.root.title(f"Dithering Preview - {Path(path).name}")
|
||||
self.update_display()
|
||||
except Exception as e:
|
||||
print(f"Error loading image: {e}")
|
||||
|
||||
def update_display(self):
|
||||
if self.source_image is None:
|
||||
return
|
||||
|
||||
import time
|
||||
|
||||
# Prepare source image
|
||||
self.prepared_image = self.prepare_image(self.source_image)
|
||||
|
||||
# Create display-size version for preview (half size to fit window)
|
||||
preview_size = (DISPLAY_WIDTH // 2, DISPLAY_HEIGHT // 2)
|
||||
source_preview = self.prepared_image.resize(preview_size, Image.Resampling.LANCZOS)
|
||||
|
||||
# Apply dithering
|
||||
algo_name = self.algo_var.get()
|
||||
algo_info = DITHER_ALGORITHMS[algo_name]
|
||||
|
||||
start_time = time.time()
|
||||
dithered = apply_dithering(self.prepared_image, algo_name)
|
||||
duration = time.time() - start_time
|
||||
|
||||
self.dithered_result = dithered
|
||||
result_preview = dithered.resize(preview_size, Image.Resampling.LANCZOS)
|
||||
|
||||
# Update display
|
||||
self.source_photo = ImageTk.PhotoImage(source_preview)
|
||||
self.result_photo = ImageTk.PhotoImage(result_preview)
|
||||
|
||||
self.source_label.configure(image=self.source_photo)
|
||||
self.result_label.configure(image=self.result_photo)
|
||||
|
||||
self.algo_title.configure(text=algo_info['name'])
|
||||
self.algo_desc.configure(text=algo_info['description'])
|
||||
self.time_label.configure(text=f"Processing time: {duration:.2f}s")
|
||||
|
||||
def on_algo_change(self, event=None):
|
||||
self.current_algo_idx = self.algorithms.index(self.algo_var.get())
|
||||
self.update_display()
|
||||
|
||||
def on_rotation_change(self, event=None):
|
||||
self.orientation = int(self.rotation_var.get())
|
||||
self.update_display()
|
||||
|
||||
def next_algo(self):
|
||||
self.current_algo_idx = (self.current_algo_idx + 1) % len(self.algorithms)
|
||||
self.algo_var.set(self.algorithms[self.current_algo_idx])
|
||||
self.update_display()
|
||||
|
||||
def prev_algo(self):
|
||||
self.current_algo_idx = (self.current_algo_idx - 1) % len(self.algorithms)
|
||||
self.algo_var.set(self.algorithms[self.current_algo_idx])
|
||||
self.update_display()
|
||||
|
||||
def rotate(self):
|
||||
rotations = ['0', '90', '180', '270']
|
||||
current_idx = rotations.index(self.rotation_var.get())
|
||||
next_idx = (current_idx + 1) % 4
|
||||
self.rotation_var.set(rotations[next_idx])
|
||||
self.orientation = int(rotations[next_idx])
|
||||
self.update_display()
|
||||
|
||||
def open_file_dialog(self):
|
||||
filetypes = [
|
||||
('Image files', '*.jpg *.jpeg *.png *.bmp *.gif *.tiff'),
|
||||
('All files', '*.*')
|
||||
]
|
||||
path = filedialog.askopenfilename(filetypes=filetypes)
|
||||
if path:
|
||||
self.load_image(path)
|
||||
|
||||
def save_result(self):
|
||||
if not hasattr(self, 'dithered_result') or self.dithered_result is None:
|
||||
return
|
||||
|
||||
algo_name = self.algo_var.get()
|
||||
base_name = Path(self.image_path).stem if hasattr(self, 'image_path') else 'output'
|
||||
default_name = f"{base_name}_{algo_name}.png"
|
||||
|
||||
path = filedialog.asksaveasfilename(
|
||||
defaultextension='.png',
|
||||
initialfile=default_name,
|
||||
filetypes=[('PNG', '*.png'), ('BMP', '*.bmp'), ('JPEG', '*.jpg')]
|
||||
)
|
||||
if path:
|
||||
self.dithered_result.save(path)
|
||||
print(f"Saved: {path}")
|
||||
|
||||
def run(self):
|
||||
self.root.mainloop()
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description='Interactive dithering preview')
|
||||
parser.add_argument('image', nargs='?', help='Input image file')
|
||||
args = parser.parse_args()
|
||||
|
||||
app = DitherPreview(args.image)
|
||||
app.run()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
102
notebooks/_helpers.py
Normal file
102
notebooks/_helpers.py
Normal file
|
|
@ -0,0 +1,102 @@
|
|||
"""Shared helpers for the frame project notebooks.
|
||||
|
||||
Each notebook should call `bootstrap()` first — it puts `src/lib/` on the import
|
||||
path and stubs `waveshare_epd.epdconfig` so the production helpers can be
|
||||
imported without trying to claim GPIO pins.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import contextlib
|
||||
import io
|
||||
import os
|
||||
import random
|
||||
import sys
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from types import ModuleType
|
||||
from typing import Callable, Iterable
|
||||
|
||||
REPO = Path(__file__).resolve().parent.parent
|
||||
CACHE_DIR = Path(tempfile.gettempdir()) / "frame_notebook"
|
||||
|
||||
DEFAULT_PEOPLE = ("Me", "Ruby")
|
||||
DEFAULT_IMMICH_URL = "https://immich.schmelczer.dev"
|
||||
DEFAULT_IMMICH_API_KEY = "6crxVS1JLTJxsfGlzVhN2kefdL4EP7HPkkoMk9L6ZOE"
|
||||
|
||||
|
||||
def bootstrap() -> None:
|
||||
"""Make production lib + the migrated dither module importable, off-Pi safe."""
|
||||
for p in (REPO / "src" / "lib", REPO / "notebooks"):
|
||||
sp = str(p)
|
||||
if sp not in sys.path:
|
||||
sys.path.insert(0, sp)
|
||||
sys.modules.setdefault("waveshare_epd.epdconfig", ModuleType("waveshare_epd.epdconfig"))
|
||||
|
||||
|
||||
def immich_client():
|
||||
from immich import ImmichClient
|
||||
return ImmichClient(
|
||||
os.environ.get("IMMICH_URL", DEFAULT_IMMICH_URL),
|
||||
os.environ.get("IMMICH_API_KEY", DEFAULT_IMMICH_API_KEY),
|
||||
)
|
||||
|
||||
|
||||
def is_landscape(asset: dict) -> bool:
|
||||
exif = asset.get("exifInfo") or {}
|
||||
w, h = exif.get("exifImageWidth") or 0, exif.get("exifImageHeight") or 0
|
||||
if exif.get("orientation") in (6, 8, "6", "8"):
|
||||
w, h = h, w
|
||||
return w > h > 0
|
||||
|
||||
|
||||
def fetch_pool(client, names: Iterable[str] = DEFAULT_PEOPLE, pool_size: int = 500,
|
||||
seed: int = 7, filter_fn: Callable[[dict], bool] = is_landscape) -> list[dict]:
|
||||
person_ids = [pid for n in names if (pid := client.get_person_id(n))]
|
||||
if not person_ids:
|
||||
raise ValueError(f"no people found: {list(names)}")
|
||||
assets = client.search_assets_by_people(person_ids)
|
||||
filtered = [a for a in assets if filter_fn(a)]
|
||||
rng = random.Random(seed)
|
||||
return rng.sample(filtered, min(pool_size, len(filtered)))
|
||||
|
||||
|
||||
def download_image(client, asset: dict):
|
||||
"""Download (cached) and open as PIL RGB Image."""
|
||||
from PIL import Image
|
||||
CACHE_DIR.mkdir(exist_ok=True)
|
||||
dest = CACHE_DIR / f"{asset['id']}.jpg"
|
||||
if not dest.exists():
|
||||
client.download_asset(asset["id"], dest)
|
||||
return Image.open(dest).convert("RGB")
|
||||
|
||||
|
||||
@contextlib.contextmanager
|
||||
def silenced():
|
||||
"""Suppress the production code's print() chatter during batch loops."""
|
||||
with contextlib.redirect_stdout(io.StringIO()):
|
||||
yield
|
||||
|
||||
|
||||
def show_grid(rows: list[list], titles: list[list[str]], figsize_scale=(4.4, 3.0),
|
||||
suptitle: str | None = None):
|
||||
"""Render a 2-D image grid with matplotlib. `rows` is list-of-lists of PIL/np images."""
|
||||
import matplotlib.pyplot as plt
|
||||
n_rows, n_cols = len(rows), max(len(r) for r in rows)
|
||||
fig, axes = plt.subplots(n_rows, n_cols,
|
||||
figsize=(figsize_scale[0] * n_cols, figsize_scale[1] * n_rows))
|
||||
if n_rows == 1:
|
||||
axes = [axes] if n_cols == 1 else [list(axes)]
|
||||
elif n_cols == 1:
|
||||
axes = [[ax] for ax in axes]
|
||||
for i, (row, row_titles) in enumerate(zip(rows, titles)):
|
||||
for j in range(n_cols):
|
||||
ax = axes[i][j]
|
||||
if j < len(row) and row[j] is not None:
|
||||
ax.imshow(row[j])
|
||||
ax.set_title(row_titles[j], fontsize=10)
|
||||
ax.axis("off")
|
||||
if suptitle:
|
||||
fig.suptitle(suptitle, fontsize=12)
|
||||
plt.tight_layout()
|
||||
return fig
|
||||
308
notebooks/crop_compare.ipynb
Normal file
308
notebooks/crop_compare.ipynb
Normal file
File diff suppressed because one or more lines are too long
182
notebooks/dither_compare.ipynb
Normal file
182
notebooks/dither_compare.ipynb
Normal file
|
|
@ -0,0 +1,182 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Dithering algorithm comparison\n",
|
||||
"\n",
|
||||
"Migrated from `dither_test/`. The 6-colour ACeP palette can only show Black, White, Yellow,\n",
|
||||
"Red, Blue, Green — so the dithering algorithm choice has a big effect on perceived image\n",
|
||||
"quality. This notebook applies a curated set of error-diffusion and ordered-dithering\n",
|
||||
"algorithms to a few real photos from Immich and shows them side-by-side, with timing.\n",
|
||||
"\n",
|
||||
"Production uses Atkinson with perceptual weighting (`atkinson_weighted` is the closest\n",
|
||||
"match — the actual production version is numba-JIT'd, equivalent to `atkinson_fast`). This\n",
|
||||
"notebook is the place to evaluate alternatives if you want to switch.\n",
|
||||
"\n",
|
||||
"Algorithm taxonomy:\n",
|
||||
"- **Error diffusion** (`floyd_steinberg`, `atkinson`, `jarvis`, `stucki`, `sierra`,\n",
|
||||
" `sierra_lite`, `burkes`) — quantise pixels left-to-right, push the rounding error onto\n",
|
||||
" unprocessed neighbours.\n",
|
||||
"- **Ordered** (`bayer4`, `bayer8`, `bayer4_strong`) — add a deterministic threshold pattern\n",
|
||||
" before quantising. No error spreading; pattern is independent of content.\n",
|
||||
"- **PIL built-ins** (`pil_fs`, `pil_none`) — for reference."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import sys\n",
|
||||
"sys.path.insert(0, '.')\n",
|
||||
"from _helpers import bootstrap, immich_client, fetch_pool, download_image, silenced, show_grid\n",
|
||||
"bootstrap()\n",
|
||||
"\n",
|
||||
"import time\n",
|
||||
"import numpy as np\n",
|
||||
"from PIL import Image\n",
|
||||
"from waveshare_epd.epd7in3e import EPD_WIDTH, EPD_HEIGHT, _crop_center\n",
|
||||
"from _dither import DITHER_ALGORITHMS, apply_dithering, PALETTE_RGB, PALETTE_NAMES\n",
|
||||
"\n",
|
||||
"# Pure-Python algorithms run at ~30s per 800x480 image; keep a curated subset by default.\n",
|
||||
"# Toggle SHOW_ALL = True to run everything (will take several minutes).\n",
|
||||
"DEFAULT_ALGOS = ['atkinson_fast', 'atkinson', 'atkinson_weighted',\n",
|
||||
" 'floyd_steinberg', 'floyd_steinberg_weighted',\n",
|
||||
" 'jarvis', 'sierra_lite', 'burkes',\n",
|
||||
" 'bayer4', 'bayer8', 'pil_fs', 'none']\n",
|
||||
"SHOW_ALL = False\n",
|
||||
"ALGOS = list(DITHER_ALGORITHMS.keys()) if SHOW_ALL else DEFAULT_ALGOS\n",
|
||||
"\n",
|
||||
"N_PHOTOS = 2 # one image cycle per photo\n",
|
||||
"SEED = 11"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"client = immich_client()\n",
|
||||
"pool_assets = fetch_pool(client, pool_size=20, seed=SEED)\n",
|
||||
"\n",
|
||||
"with silenced():\n",
|
||||
" sources = []\n",
|
||||
" for asset in pool_assets[:N_PHOTOS]:\n",
|
||||
" img = download_image(client, asset)\n",
|
||||
" sources.append((asset, _crop_center(img, EPD_WIDTH, EPD_HEIGHT)))\n",
|
||||
"\n",
|
||||
"for asset, _ in sources:\n",
|
||||
" print(asset.get('originalFileName') or asset['id'])\n",
|
||||
"\n",
|
||||
"# Render the 6-colour palette as a tiny banner so the colour budget is visible.\n",
|
||||
"swatch_h = 60\n",
|
||||
"swatch_w = 60\n",
|
||||
"palette_strip = np.zeros((swatch_h, swatch_w * len(PALETTE_RGB), 3), dtype=np.uint8)\n",
|
||||
"for i, rgb in enumerate(PALETTE_RGB):\n",
|
||||
" palette_strip[:, i * swatch_w:(i + 1) * swatch_w] = rgb\n",
|
||||
"Image.fromarray(palette_strip)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"results = [] # list of dict per (photo, algo)\n",
|
||||
"for asset, source in sources:\n",
|
||||
" name = asset.get('originalFileName') or asset['id']\n",
|
||||
" print(f'[{name}]')\n",
|
||||
" photo_results = []\n",
|
||||
" for algo in ALGOS:\n",
|
||||
" info = DITHER_ALGORITHMS[algo]\n",
|
||||
" t0 = time.perf_counter()\n",
|
||||
" out = apply_dithering(source, algo)\n",
|
||||
" dt = time.perf_counter() - t0\n",
|
||||
" photo_results.append({'algo': algo, 'name': info['name'], 'image': out, 'duration': dt})\n",
|
||||
" print(f' {info[\"name\"]:32s} {dt:6.2f}s')\n",
|
||||
" results.append({'asset': asset, 'source': source, 'algos': photo_results})"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# One grid per photo: original + every algorithm.\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"for entry in results:\n",
|
||||
" panels = [entry['source']] + [r['image'] for r in entry['algos']]\n",
|
||||
" titles = ['original (cropped)'] + [f\"{r['name']}\\n{r['duration']:.2f}s\" for r in entry['algos']]\n",
|
||||
" cols = 4\n",
|
||||
" rows = (len(panels) + cols - 1) // cols\n",
|
||||
" fig, axes = plt.subplots(rows, cols, figsize=(5.0 * cols, 3.2 * rows))\n",
|
||||
" axes = np.atleast_2d(axes)\n",
|
||||
" name = entry['asset'].get('originalFileName') or entry['asset']['id']\n",
|
||||
" fig.suptitle(name, fontsize=12)\n",
|
||||
" for k in range(rows * cols):\n",
|
||||
" ax = axes[k // cols][k % cols]\n",
|
||||
" if k < len(panels):\n",
|
||||
" ax.imshow(panels[k])\n",
|
||||
" ax.set_title(titles[k], fontsize=10)\n",
|
||||
" ax.axis('off')\n",
|
||||
" plt.tight_layout()\n",
|
||||
" plt.show()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Per-algorithm summary across both photos: mean runtime + a single representative panel.\n",
|
||||
"from collections import defaultdict\n",
|
||||
"import matplotlib.pyplot as plt\n",
|
||||
"\n",
|
||||
"agg = defaultdict(list)\n",
|
||||
"for entry in results:\n",
|
||||
" for r in entry['algos']:\n",
|
||||
" agg[r['algo']].append(r['duration'])\n",
|
||||
"\n",
|
||||
"print(f\"{'algorithm':32s} {'avg time':>9s} description\")\n",
|
||||
"for algo in ALGOS:\n",
|
||||
" info = DITHER_ALGORITHMS[algo]\n",
|
||||
" avg = np.mean(agg[algo])\n",
|
||||
" print(f\"{info['name']:32s} {avg:>8.2f}s {info['description']}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Picking an algorithm\n",
|
||||
"\n",
|
||||
"- **Photographs** — `atkinson_fast` (production), `atkinson_weighted`, or\n",
|
||||
" `floyd_steinberg_weighted`. Atkinson loses some detail (only diffuses 6/8 of the error)\n",
|
||||
" but gives cleaner edges; FS preserves detail at the cost of more visible noise.\n",
|
||||
"- **Graphics / illustrations / posters** — `bayer4` or `bayer8`. The pattern is regular\n",
|
||||
" (no \"wormy\" artifacts) and well-suited to large flat regions.\n",
|
||||
"- **Speed-critical paths** — `atkinson_fast` (numba-JIT). Pure-Python error-diffusion\n",
|
||||
" algorithms are ~150× slower than the JIT'd version on this resolution.\n",
|
||||
"\n",
|
||||
"The `none` row (PIL nearest-colour) shows what happens with no dithering at all — useful as\n",
|
||||
"a baseline to confirm the dithering is buying you something.\n",
|
||||
"\n",
|
||||
"**To compare more algorithms** set `SHOW_ALL = True` in the setup cell. Expect several\n",
|
||||
"minutes of CPU time per photo for the slow pure-Python implementations."
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"},
|
||||
"language_info": {"name": "python"}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
21
pyproject.toml
Normal file
21
pyproject.toml
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
[project]
|
||||
name = "frame"
|
||||
version = "0.1.0"
|
||||
description = "E-ink photo frame for Raspberry Pi Zero 2W"
|
||||
requires-python = ">=3.11,<3.14"
|
||||
dependencies = [
|
||||
"numpy>=1.26",
|
||||
"pillow>=10",
|
||||
"opencv-python>=4.8",
|
||||
"numba>=0.60",
|
||||
]
|
||||
|
||||
[dependency-groups]
|
||||
notebook = [
|
||||
"matplotlib>=3.8",
|
||||
"jupyterlab>=4.2",
|
||||
"ipykernel>=6.29",
|
||||
]
|
||||
|
||||
[tool.uv]
|
||||
default-groups = ["notebook"]
|
||||
|
|
@ -12,6 +12,7 @@ sys.path.append(str(Path(__file__).parent / "lib"))
|
|||
from immich import ImmichClient, get_random_photo_of_people, get_random_photo_from_album
|
||||
from homeassistant import HomeAssistantClient
|
||||
from overlay import format_age, format_location
|
||||
from crop import face_aware_crop
|
||||
# waveshare_epd is imported lazily after the lock — its epdconfig claims
|
||||
# GPIO pins at import time, so two overlapping invocations would both crash
|
||||
# on "GPIO busy" before reaching the flock below.
|
||||
|
|
@ -21,7 +22,7 @@ IMMICH_API_KEY = os.environ.get("IMMICH_API_KEY", "6crxVS1JLTJxsfGlzVhN2kefdL4EP
|
|||
|
||||
HA_URL = os.environ.get("HA_URL", "https://homeassistant.schmelczer.dev")
|
||||
HA_TOKEN = os.environ.get("HA_TOKEN", "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJmZjk3OTNmOWMzOWU0YjdmYmRjYTc5YmJkMTUyODcyNSIsImlhdCI6MTc2OTIwMjg1NCwiZXhwIjoyMDg0NTYyODU0fQ.IiL_1vTrGMlOoPMksN6lAopE0aInlY_wRnL4Jc-CeBs")
|
||||
HA_PRESENCE_ENTITIES = ["person.andras", "person.ruby"]
|
||||
HA_PRESENCE = {"Andras": "person.andras", "Ruby": "person.ruby"}
|
||||
|
||||
|
||||
def main() -> None:
|
||||
|
|
@ -47,12 +48,12 @@ def main() -> None:
|
|||
|
||||
now = datetime.now()
|
||||
print(f"Time: {now.strftime('%H:%M')}")
|
||||
if 0 <= now.hour < 7:
|
||||
if now.hour < 7:
|
||||
print("Night time, skipping")
|
||||
sys.exit(0)
|
||||
|
||||
ha = HomeAssistantClient(HA_URL, HA_TOKEN)
|
||||
home = [e.split(".")[-1].title() for e in HA_PRESENCE_ENTITIES if ha.is_person_home(e)]
|
||||
home = [name for name, eid in HA_PRESENCE.items() if ha.is_person_home(eid)]
|
||||
if not home:
|
||||
print("No one home, skipping")
|
||||
sys.exit(0)
|
||||
|
|
@ -77,6 +78,10 @@ def main() -> None:
|
|||
try:
|
||||
epd.init()
|
||||
img = Image.open(image_path).convert("RGB")
|
||||
faces = client.get_asset_faces(asset["id"])
|
||||
print(f"Faces: {len(faces)}")
|
||||
target_w, target_h = (480, 800) if args.orientation in (90, 270) else (800, 480)
|
||||
img = face_aware_crop(img, target_w, target_h, faces)
|
||||
if args.orientation:
|
||||
img = img.rotate(args.orientation, expand=True)
|
||||
buf = epd.getbuffer(img, saturation=args.saturation, contrast=args.contrast,
|
||||
|
|
|
|||
69
src/lib/crop.py
Normal file
69
src/lib/crop.py
Normal file
|
|
@ -0,0 +1,69 @@
|
|||
"""Resize-to-cover then crop, biased toward Immich-detected face boxes."""
|
||||
|
||||
import math
|
||||
|
||||
from PIL import Image
|
||||
|
||||
# Face boxes end at the hairline; extend each box upward by this fraction of
|
||||
# its own height so the fit-check considers the head, not just the face.
|
||||
HEAD_EXTENSION = 0.4
|
||||
|
||||
|
||||
def face_aware_crop(image: Image.Image, target_w: int, target_h: int,
|
||||
faces: list[dict]) -> Image.Image:
|
||||
"""Resize to cover (target_w, target_h), then crop to keep faces in frame.
|
||||
|
||||
Each face dict has imageWidth/imageHeight (the coord-space dims) and
|
||||
boundingBoxX1/Y1/X2/Y2. Per axis: if every (head-extended) face fits in
|
||||
the crop we centre on the joint span so all faces are included with hair
|
||||
clearance on top. If the span doesn't fit, we fall back to the
|
||||
area-weighted centroid of the unextended boxes — that biases toward the
|
||||
biggest, presumably foreground, face. Plain center crop when no faces.
|
||||
"""
|
||||
img_w, img_h = image.size
|
||||
img_aspect = img_w / img_h
|
||||
target_aspect = target_w / target_h
|
||||
if img_aspect < target_aspect:
|
||||
new_w = target_w
|
||||
new_h = math.ceil(target_w / img_aspect)
|
||||
else:
|
||||
new_w = math.ceil(target_h * img_aspect)
|
||||
new_h = target_h
|
||||
|
||||
resized = image.resize((new_w, new_h), Image.LANCZOS)
|
||||
|
||||
cx, cy = new_w / 2, new_h / 2
|
||||
if faces:
|
||||
boxes = []
|
||||
for f in faces:
|
||||
sx = new_w / (f.get("imageWidth") or img_w)
|
||||
sy = new_h / (f.get("imageHeight") or img_h)
|
||||
x1 = f["boundingBoxX1"] * sx
|
||||
y1 = f["boundingBoxY1"] * sy
|
||||
x2 = f["boundingBoxX2"] * sx
|
||||
y2 = f["boundingBoxY2"] * sy
|
||||
area = max(0.0, (x2 - x1) * (y2 - y1))
|
||||
boxes.append((x1, y1, x2, y2, area))
|
||||
|
||||
x_lo = min(b[0] for b in boxes)
|
||||
x_hi = max(b[2] for b in boxes)
|
||||
if x_hi - x_lo <= target_w:
|
||||
cx = (x_lo + x_hi) / 2
|
||||
else:
|
||||
cx = _weighted_center(boxes, 0, 2)
|
||||
|
||||
y_lo_ext = min(b[1] - (b[3] - b[1]) * HEAD_EXTENSION for b in boxes)
|
||||
y_hi = max(b[3] for b in boxes)
|
||||
if y_hi - y_lo_ext <= target_h:
|
||||
cy = (y_lo_ext + y_hi) / 2
|
||||
else:
|
||||
cy = _weighted_center(boxes, 1, 3)
|
||||
|
||||
x_off = max(0, min(int(cx - target_w / 2), new_w - target_w))
|
||||
y_off = max(0, min(int(cy - target_h / 2), new_h - target_h))
|
||||
return resized.crop((x_off, y_off, x_off + target_w, y_off + target_h))
|
||||
|
||||
|
||||
def _weighted_center(boxes: list[tuple], lo: int, hi: int) -> float:
|
||||
total = sum(b[4] for b in boxes) or 1.0
|
||||
return sum((b[lo] + b[hi]) / 2 * b[4] for b in boxes) / total
|
||||
|
|
@ -16,11 +16,11 @@ CACHE_DIR = Path(tempfile.gettempdir()) / "frame_cache"
|
|||
|
||||
def _cache_get(key: str) -> list[dict] | None:
|
||||
path = CACHE_DIR / f"{key}.json"
|
||||
if not path.exists() or time.time() - path.stat().st_mtime > 3600:
|
||||
return None
|
||||
try:
|
||||
if time.time() - path.stat().st_mtime > 3600:
|
||||
return None
|
||||
return json.loads(path.read_text())
|
||||
except (json.JSONDecodeError, OSError):
|
||||
except (FileNotFoundError, json.JSONDecodeError, OSError):
|
||||
return None
|
||||
|
||||
|
||||
|
|
@ -29,45 +29,26 @@ def _cache_set(key: str, value: list[dict]) -> None:
|
|||
(CACHE_DIR / f"{key}.json").write_text(json.dumps(value))
|
||||
|
||||
|
||||
class PhotoHistory:
|
||||
"""Track displayed photos to avoid repeats. Clears after 7 days."""
|
||||
def _load_history() -> tuple[set[str], datetime]:
|
||||
"""Load (displayed, created_at). Resets if missing/corrupt or older than 7 days."""
|
||||
try:
|
||||
data = json.loads(HISTORY_FILE.read_text())
|
||||
created_at = datetime.fromisoformat(data["created_at"])
|
||||
if created_at.tzinfo is None:
|
||||
created_at = created_at.replace(tzinfo=timezone.utc)
|
||||
if datetime.now(timezone.utc) - created_at <= timedelta(days=7):
|
||||
return set(data.get("displayed", [])), created_at
|
||||
print("Photo history expired (>7 days), clearing...")
|
||||
except (FileNotFoundError, json.JSONDecodeError, ValueError, KeyError):
|
||||
pass
|
||||
return set(), datetime.now(timezone.utc)
|
||||
|
||||
def __init__(self, path: Path = HISTORY_FILE):
|
||||
self.path = path
|
||||
self.displayed: set[str] = set()
|
||||
self.created_at = datetime.now(timezone.utc)
|
||||
self._load()
|
||||
|
||||
def _load(self) -> None:
|
||||
if not self.path.exists():
|
||||
self._save()
|
||||
return
|
||||
try:
|
||||
data = json.loads(self.path.read_text())
|
||||
self.created_at = datetime.fromisoformat(data["created_at"])
|
||||
if self.created_at.tzinfo is None:
|
||||
self.created_at = self.created_at.replace(tzinfo=timezone.utc)
|
||||
if datetime.now(timezone.utc) - self.created_at > timedelta(days=7):
|
||||
print("Photo history expired (>7 days), clearing...")
|
||||
self.created_at = datetime.now(timezone.utc)
|
||||
self._save()
|
||||
else:
|
||||
self.displayed = set(data.get("displayed", []))
|
||||
except (json.JSONDecodeError, ValueError, KeyError):
|
||||
self._save()
|
||||
|
||||
def _save(self) -> None:
|
||||
self.path.write_text(json.dumps({
|
||||
"created_at": self.created_at.isoformat(),
|
||||
"displayed": list(self.displayed),
|
||||
}, indent=2))
|
||||
|
||||
def mark_displayed(self, asset_id: str) -> None:
|
||||
self.displayed.add(asset_id)
|
||||
self._save()
|
||||
|
||||
def filter_new(self, assets: list[dict]) -> list[dict]:
|
||||
return [a for a in assets if a.get("id") not in self.displayed]
|
||||
def _save_history(displayed: set[str], created_at: datetime) -> None:
|
||||
HISTORY_FILE.write_text(json.dumps({
|
||||
"created_at": created_at.isoformat(),
|
||||
"displayed": sorted(displayed),
|
||||
}, indent=2))
|
||||
|
||||
|
||||
@dataclass
|
||||
|
|
@ -79,14 +60,13 @@ class ImmichClient:
|
|||
self.base_url = self.base_url.rstrip("/")
|
||||
|
||||
def _request(self, method: str, endpoint: str, data: dict | None = None) -> dict:
|
||||
url = f"{self.base_url}/api/{endpoint.lstrip('/')}"
|
||||
headers = {"x-api-key": self.api_key}
|
||||
body = None
|
||||
if data is not None:
|
||||
headers["Content-Type"] = "application/json"
|
||||
body = json.dumps(data).encode()
|
||||
|
||||
req = Request(url, data=body, headers=headers, method=method)
|
||||
req = Request(f"{self.base_url}/api{endpoint}", data=body, headers=headers, method=method)
|
||||
with urlopen_with_retry(req, timeout=30) as resp:
|
||||
return json.loads(resp.read().decode())
|
||||
|
||||
|
|
@ -105,16 +85,15 @@ class ImmichClient:
|
|||
items = []
|
||||
page = 1
|
||||
while True:
|
||||
result = self._request("POST", "/search/metadata", {
|
||||
assets = self._request("POST", "/search/metadata", {
|
||||
"personIds": person_ids,
|
||||
"size": 250,
|
||||
"page": page,
|
||||
"type": "IMAGE",
|
||||
"withExif": True,
|
||||
})
|
||||
batch = result.get("assets", {}).get("items", [])
|
||||
items.extend(batch)
|
||||
if not batch or not result.get("assets", {}).get("nextPage"):
|
||||
}).get("assets", {})
|
||||
items.extend(assets.get("items", []))
|
||||
if not assets.get("nextPage"):
|
||||
break
|
||||
page += 1
|
||||
_cache_set(key, items)
|
||||
|
|
@ -127,6 +106,19 @@ class ImmichClient:
|
|||
dest.write_bytes(resp.read())
|
||||
return dest
|
||||
|
||||
def get_asset_faces(self, asset_id: str) -> list[dict]:
|
||||
"""Face boxes for people assigned on this asset.
|
||||
|
||||
Each face has imageWidth, imageHeight, boundingBoxX1/Y1/X2/Y2.
|
||||
Unassigned faces are skipped — they're often false positives (posters,
|
||||
reflections) and shouldn't drag the crop off the real subjects.
|
||||
"""
|
||||
asset = self._request("GET", f"/assets/{asset_id}")
|
||||
faces = []
|
||||
for person in asset.get("people") or []:
|
||||
faces.extend(person.get("faces") or [])
|
||||
return faces
|
||||
|
||||
def get_album_id(self, name: str) -> str | None:
|
||||
for album in self._request("GET", "/albums"):
|
||||
if album["albumName"].lower() == name.lower():
|
||||
|
|
@ -159,8 +151,35 @@ def _filter_by_orientation(assets: list[dict], portrait: bool) -> list[dict]:
|
|||
return out
|
||||
|
||||
|
||||
def _on_this_day_candidates(assets: list[dict]) -> list[dict]:
|
||||
"""Photos taken on today's month-day in past years, with a ±3-day fallback."""
|
||||
today = datetime.now(timezone.utc).date()
|
||||
dated = []
|
||||
for a in assets:
|
||||
exif = a.get("exifInfo") or {}
|
||||
date_str = exif.get("dateTimeOriginal") or a.get("fileCreatedAt")
|
||||
if not date_str:
|
||||
continue
|
||||
try:
|
||||
dt = datetime.fromisoformat(date_str.replace("Z", "+00:00")).date()
|
||||
except (ValueError, AttributeError):
|
||||
continue
|
||||
if dt.year < today.year:
|
||||
dated.append((a, dt))
|
||||
|
||||
exact = [a for a, dt in dated if (dt.month, dt.day) == (today.month, today.day)]
|
||||
if exact:
|
||||
return exact
|
||||
|
||||
nearby_md = set()
|
||||
for offset in range(-3, 4):
|
||||
d = today + timedelta(days=offset)
|
||||
nearby_md.add((d.month, d.day))
|
||||
return [a for a, dt in dated if (dt.month, dt.day) in nearby_md]
|
||||
|
||||
|
||||
def _pick_weighted_random(assets: list[dict]) -> dict:
|
||||
"""Pick random asset, biased towards favorites and recently added photos."""
|
||||
"""Pick random asset, biased towards on-this-day memories, favorites, and recents."""
|
||||
cutoff = datetime.now(timezone.utc) - timedelta(days=30)
|
||||
favorites = [a for a in assets if a.get("isFavorite")]
|
||||
recent = []
|
||||
|
|
@ -170,10 +189,18 @@ def _pick_weighted_random(assets: list[dict]) -> dict:
|
|||
recent.append(a)
|
||||
except (ValueError, AttributeError):
|
||||
pass
|
||||
on_this_day = _on_this_day_candidates(assets)
|
||||
|
||||
candidates = [(favorites, 0.2), (recent, 0.4), (assets, 0.4)]
|
||||
pools, weights = zip(*[(p, w) for p, w in candidates if p])
|
||||
pool = random.choices(pools, weights=weights)[0]
|
||||
candidates = [
|
||||
("on this day", on_this_day, 0.10),
|
||||
("favorites", favorites, 0.18),
|
||||
("recent", recent, 0.36),
|
||||
("all", assets, 0.36),
|
||||
]
|
||||
active = [(label, pool, w) for label, pool, w in candidates if pool]
|
||||
print("Pool sizes: " + ", ".join(f"{label}={len(pool)}" for label, pool, _ in active))
|
||||
label, pool, _ = random.choices(active, weights=[w for _, _, w in active])[0]
|
||||
print(f"Picked pool: {label} ({len(pool)} candidates)")
|
||||
return random.choice(pool)
|
||||
|
||||
|
||||
|
|
@ -184,8 +211,8 @@ def _pick_and_download(client: ImmichClient, assets: list[dict],
|
|||
if not filtered:
|
||||
raise ValueError(f"No {'portrait' if portrait else 'landscape'} photos in {source_label}")
|
||||
|
||||
history = PhotoHistory()
|
||||
candidates = history.filter_new(filtered)
|
||||
displayed, created_at = _load_history()
|
||||
candidates = [a for a in filtered if a.get("id") not in displayed]
|
||||
if not candidates:
|
||||
print(f"All {len(filtered)} photos shown, picking from full list")
|
||||
candidates = filtered
|
||||
|
|
@ -195,7 +222,8 @@ def _pick_and_download(client: ImmichClient, assets: list[dict],
|
|||
asset = _pick_weighted_random(candidates)
|
||||
dest = Path(tempfile.gettempdir()) / "immich_photo.jpg"
|
||||
path = client.download_asset(asset["id"], dest)
|
||||
history.mark_displayed(asset["id"])
|
||||
displayed.add(asset["id"])
|
||||
_save_history(displayed, created_at)
|
||||
return path, asset
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -3,17 +3,13 @@ import time
|
|||
from urllib.error import URLError
|
||||
from urllib.request import Request, urlopen
|
||||
|
||||
RETRY_DELAYS = (3, 10)
|
||||
|
||||
|
||||
def urlopen_with_retry(req: Request, timeout: int = 30):
|
||||
"""urlopen wrapper that retries transient network failures."""
|
||||
last_err: Exception | None = None
|
||||
for attempt in range(len(RETRY_DELAYS) + 1):
|
||||
"""urlopen wrapper that retries transient network failures (3s, 10s backoff)."""
|
||||
for delay in (3, 10, None):
|
||||
try:
|
||||
return urlopen(req, timeout=timeout)
|
||||
except (URLError, TimeoutError) as e:
|
||||
last_err = e
|
||||
if attempt < len(RETRY_DELAYS):
|
||||
time.sleep(RETRY_DELAYS[attempt])
|
||||
raise last_err
|
||||
except (URLError, TimeoutError):
|
||||
if delay is None:
|
||||
raise
|
||||
time.sleep(delay)
|
||||
|
|
|
|||
|
|
@ -52,7 +52,9 @@ def format_age(asset: dict) -> str | None:
|
|||
for n, unit in ((365, "year"), (30, "month"), (7, "week")):
|
||||
if days >= n:
|
||||
count = max(1, days // n)
|
||||
return f"{count} {unit}{'s' if count > 1 else ''} ago"
|
||||
if count == 1:
|
||||
return f"Last {unit}"
|
||||
return f"{count} {unit}s ago"
|
||||
|
||||
|
||||
def format_location(asset: dict) -> str | None:
|
||||
|
|
|
|||
|
|
@ -159,23 +159,20 @@ class EPD:
|
|||
epdconfig.digital_write(self.reset_pin, 1)
|
||||
epdconfig.delay_ms(20)
|
||||
|
||||
def send_command(self, command):
|
||||
epdconfig.digital_write(self.dc_pin, 0)
|
||||
def _spi(self, dc: int, payload, batch: bool = False):
|
||||
epdconfig.digital_write(self.dc_pin, dc)
|
||||
epdconfig.digital_write(self.cs_pin, 0)
|
||||
epdconfig.spi_writebyte([command])
|
||||
(epdconfig.spi_writebyte2 if batch else epdconfig.spi_writebyte)(payload)
|
||||
epdconfig.digital_write(self.cs_pin, 1)
|
||||
|
||||
def send_command(self, command):
|
||||
self._spi(0, [command])
|
||||
|
||||
def send_data(self, data):
|
||||
epdconfig.digital_write(self.dc_pin, 1)
|
||||
epdconfig.digital_write(self.cs_pin, 0)
|
||||
epdconfig.spi_writebyte([data])
|
||||
epdconfig.digital_write(self.cs_pin, 1)
|
||||
self._spi(1, [data])
|
||||
|
||||
def send_data2(self, data):
|
||||
epdconfig.digital_write(self.dc_pin, 1)
|
||||
epdconfig.digital_write(self.cs_pin, 0)
|
||||
epdconfig.spi_writebyte2(data)
|
||||
epdconfig.digital_write(self.cs_pin, 1)
|
||||
self._spi(1, data, batch=True)
|
||||
|
||||
def wait_busy(self):
|
||||
while epdconfig.digital_read(self.busy_pin) == 0:
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue