# Image Pipeline

Modular Python framework for chaining image processing steps after Darktable export.

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.

## Requirements

- Python 3.11+
- [ImageMagick](https://imagemagick.org/) (`magick` or `convert` on PATH)

## Installation

```bash
cd /path/to/imagepipeline
pip install -e ".[dev]"
```

## Quick Start

Edit the input path in `pipelines/example_grayscale.py`, then run:

```bash
python pipelines/example_grayscale.py
```

Or from Python:

```python
from pathlib import Path
from imagepipeline import Pipeline

with Pipeline(name="my_run", input_dir=Path("/path/to/export")) as p:
    gray = p.step("imagemagick_grayscale", inputs="input")
    p.run()
```

## Output Structure

Each run creates a folder like `my_run_20260527143022/`:

```
my_run_20260527143022/
├── pipeline_manifest.json
├── input/                      # symlinks to source images
├── imagemagick_grayscale_01/
│   └── photo.jpg
└── ...
```

Step folders are named `{module_name}_{nn}` (two-digit counter per module name).

## Writing Pipelines

Pipelines are plain Python scripts. Reference previous steps via `StepRef` objects returned by `p.step()`:

```python
with Pipeline(name="colorsplash", input_dir=INPUT) as p:
    rembg_out = p.step("rembg", inputs="input")
    bw = p.step("imagemagick_grayscale", inputs="input")
    combined = p.step("composite", inputs=[bw, rembg_out], mode="foreground_over")
    p.step("darktable_style", inputs=combined, style="vintage.dtstyle")
    p.run()
```

- `"input"` refers to the original input directory
- Parameters are passed as kwargs and validated against each module's schema
- Multiple uses of the same module get separate numbered folders

## Adding Modules

See [docs/MODULE_DEVELOPMENT.md](docs/MODULE_DEVELOPMENT.md).

## Tests

```bash
pytest
```