Frank Schwenk
79 lines
1.9 KiB
Markdown
79 lines
1.9 KiB
Markdown
# Image Pipeline
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Modular Python framework for chaining image processing steps after Darktable export.
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Each pipeline is a Python script that defines a DAG of processing steps. Every step writes its output to a numbered subfolder inside a timestamped run directory.
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## Requirements
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- Python 3.11+
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- [ImageMagick](https://imagemagick.org/) (`magick` or `convert` on PATH)
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## Installation
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```bash
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cd /path/to/imagepipeline
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pip install -e ".[dev]"
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```
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## Quick Start
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Edit the input path in `pipelines/example_grayscale.py`, then run:
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```bash
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python pipelines/example_grayscale.py
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```
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Or from Python:
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```python
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from pathlib import Path
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from imagepipeline import Pipeline
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with Pipeline(name="my_run", input_dir=Path("/path/to/export")) as p:
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gray = p.step("imagemagick_grayscale", inputs="input")
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p.run()
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```
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## Output Structure
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Each run creates a folder like `my_run_20260527143022/`:
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```
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my_run_20260527143022/
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├── pipeline_manifest.json
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├── input/ # symlinks to source images
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├── imagemagick_grayscale_01/
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│ └── photo.jpg
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└── ...
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```
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Step folders are named `{module_name}_{nn}` (two-digit counter per module name).
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## Writing Pipelines
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Pipelines are plain Python scripts. Reference previous steps via `StepRef` objects returned by `p.step()`:
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```python
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with Pipeline(name="colorsplash", input_dir=INPUT) as p:
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rembg_out = p.step("rembg", inputs="input")
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bw = p.step("imagemagick_grayscale", inputs="input")
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combined = p.step("composite", inputs=[bw, rembg_out], mode="foreground_over")
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p.step("darktable_style", inputs=combined, style="vintage.dtstyle")
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p.run()
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```
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- `"input"` refers to the original input directory
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- Parameters are passed as kwargs and validated against each module's schema
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- Multiple uses of the same module get separate numbered folders
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## Adding Modules
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See [docs/MODULE_DEVELOPMENT.md](docs/MODULE_DEVELOPMENT.md).
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## Tests
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```bash
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pytest
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```
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