Automatization around Siril (https://siril.org/) for deep sky astrophotography.

What is it?

Poto-Siril is a CLI tool to automate the pre-processing of astrophotography images on top of Siril.

Poto-Siril aims to overcome the repetitive and tedious work when pre-processing multiple layers before compositing an (L)RGB image (e.g. narrowband filters with a monochrome camera or a color camera with dual-band filters).

It works out of the box with images captured by a ZWO ASIAIR device or with any fit files that follow the same file naming convention and directory structure (more support to come, help is welcomed 👋).

Workflow 🚀

The essence of Poto-Siril is about:

• Organizing the raw data by grouping the multiple light sequences together in small groups (of the same filter, bulb, gain, etc...) tagged with the appropriate flats, darks, and biases.
• Running Siril script(s) on each group of lights to retrieve the calibrated lights, following:

Calibrated\_Light = \frac{Light\_Frame - Dark\_Frame}{Flat\_Frame}

• Stacking the calibrated lights to get a master light for each layer/filter.

In detail

• Easy import of lights and flats from night session(s) and search for associated darks and biases in a bank folder Import one or several night sessions (e.g. lights and flats from Autorun or Plan mode with ASIAIR) and automatically pick the darks and biases from the bank folder (matching bulb, gain, binning, ...). A summary resumes the light sequence(s) and the calibration files associated.
• Complex Light - Flat matching Poto-Siril helps to associate the right flats with the right lights when the project consists of multiple night sessions where the flats changed over time, e.g., a significant date gap between shooting sessions having a new collimation tuning and/or new dust in the optical train.
• Multi-layers project structure The imported files ☝️ are organized by filters and light sets (bulb, gain & binning, if there are multiple combinations). Each light set will map to a light sequence in Siril to be pre-processed separately. 👉 You can easily work on an LRGB or LRGBHaOIIISII project.
• Batch Siril script execution to pre-process the data (Generates and) Runs a Siril script (.ssl file) to calibrate the lights for each light set, based on a customizable ssl file template.
• A/B testing (PLANNED) Run the (generated ☝️) Siril script with different parameters (e.g. rejection algorithm, sigma low/high thresholds) and compare the results. Or run several different pre-processing scripts and compare the results.

What it is not doing

Poto-Siril does not eliminate bad light images, and everything related to the final processing such as channel compositing, color calibration, background extraction, etc...

Usage

First installation

Install node latest version and run:

npm install -g poto-siril
poto -v
# Should print `poto-siril 0.9.3`.

# Make sure to have `siril` registered in your PATH.
siril -v
# Should print `siril 1.2.5`.

CLI commands

# Drop ASIAIR .jpg thumbnails and empty directories (optional).
poto clear deepsky/2024_08_10_asiair_veil-nebula

# Prepare a Poto project by importing imaging sessions (lights, flats) and calibration files (darks, biases).
poto prepare -i deepsky/sessions/2024_08_10_asiair_veil-nebula -i deepsky/_bank deepsky/2024_08_10_poto_veil-nebula

# Batch pre-process all lights (filter by filter, set by set) using a Siril script template.
poto prepare -t deepsky/poto_pipeline/Mono_Preprocessing/Mono_Preprocessing.ssf deepsky/2024_08_10_poto_veil-nebula

Pre-processing pipeline

Usually, the pre-processing is a multi-step journey. The most usual case is to pre-process lights, eliminate bad ones in Siril directly, and go back to Poto-Siril to batch-run the stacking.

You can chain multiple scripts to achieve the desired result. See src/pipeline/Mono_Preprocessing/README.md for a full example of a pre-processing pipeline.

Create your own

You can easily create your own by following the Mono_Preprocessing pipeline example.

Some remarks about Poto-Siril script templates:

• .ssf extension like regular Siril scripts.
• Poto-Siril dynamically overwrites the {{poto-dir}}, {{lights}}, {{flats}}, {{darks}}, {{biases}}, {{process}} & {{masters}} variables to the current light set to pre-process.

File naming convention

Poto-Siril expects the files to follow the ASIAIR file naming convention {Light|Flat|Dark|Bias}_{TARGET}_{EXPOSURE_TIME}{s|ms}_Bin{BINNING}_{FILTER}_gain{GAIN}_{DATE}-{TIME}_{TEMPERATURE}C_{SEQUENCE_NUMBER}.fit.

For example:

• Light_10.0s_Bin1_S_gain360_20240320-203324_-10.0C_0001.fit
• Light_FOV_60.0s_Bin1_S_gain100_20240624-010840_-10.1C_0001.fit
• Flat_1.0ms_Bin1_S_gain100_20240320-233122_-10.5C_0001.fit
• Dark_300.0s_Bin1_S_gain100_20240320-233122_-10.5C_0001.fit
• Bias_1.0ms_Bin1_S_gain100_20240320-233122_-10.5C_0001.fit

Poto-Siril project architecture

# Poto project root directory
├── S    👈 Directory for each filter.
│   ├── Light_M42_10.0s_Bin1_S_gain360    👈 Sub directory for each light set (BIN-GAIN-BULB combination).
|   │   ├── Light_M42_10.0s_Bin1_S_gain360_20240320-203324_-10.0C_0001.fit
│   │   └── ...
│   ├── Light_M42_10.0s_Bin1_S_gain100
|   │   ├── Light_M42_10.0s_Bin1_S_gain100_20240321-223159_-10.0C_0001.fit
│   │   └── ...
│   └── Flat_1.0ms_Bin1_S_gain100
|       ├── Flat_1.0ms_Bin1_S_gain100_20240320-233122_-10.5C_0001.fit
│       └── ...
├── H
├── O
├── ...
└── any    👈 Biases & darks fall here.

💡 S, H, O are the filter names extracted from the File naming convention.

The bank folder (for reference)

It's common to store the darks and biases in a 'bank folder' since they are quite static. Poto-siril doesn't expect any precise directory structure for a directory to act like a bank folder as long as the file naming convention is respected.

Example of structure:

# Bank directory
├── Bias_1.0ms_Bin1_gain100_-9.9C_2024
│   ├── Bias_1.0ms_Bin1_L_gain100_20240308-154935_-10.0C_0001.fit
│   ├── Bias_1.0ms_Bin1_L_gain100_20240308-154936_-9.9C_0002.fit
│   └── ...
├── Darks_300.0s_Bin1_gain100_-10C_2024
│   ├── Dark_300.0s_Bin1_L_gain100_20240308-172757_-10.0C_0001.fit
│   ├── Dark_300.0s_Bin1_L_gain100_20240308-160224_-10.0C_0002.fit
│   └── ...
└── ...

ASIAIR directory structure (for reference)

💡 Note that this directory structure is optional.

# Root dump directory of an ASIAIR session
├── Autorun
│   ├── Light
|   |   └── M42
|   |       ├── Light_M42_10.0s_Bin1_S_gain360_20240320-203324_-10.0C_0001.fit
│   |       ├── ...
|   |       ├── Light_M42_10.0s_Bin1_S_gain100_20240321-223159_-10.0C_0001.fit
|   |       └── ...
│   └── Flat
|       ├── Flat_1.0ms_Bin1_S_gain100_20240320-233122_-10.5C_0001.fit
│       └── ...
├── Plan
│   # Same structure as Autorun.
├── Live
│   # Ignored in poto-siril
├── Preview
│   # Ignored in poto-siril
├── Video
│   # Ignored in poto-siril
└── log
    # Ignored in poto-siril

Development

Install node latest version and run:

npm i
# For Unix based systems:
chmod +x ./poto.sh
./poto.sh -v
# Should print `poto-siril 0.9.3`.

# Make sure to have `siril` registered in your PATH.
siril -v
# Should print `siril 1.2.5`.

# Run the tests
npm test

# Run the linter
npm run lint

# Run type checking
npm run check-types

# Generate dataset 1 for development
npm run dev-spawn-ds1

# Run dev-spawn-ds1 & the prepare command with the development dataset 1
npm run dev-prepare-ds1

# Run the preprocess command with the development dataset 1
npm run dev-preprocess-ds1

Side Notes

Sirilic and Sirilot are two alternatives to automate Siril. This project is another take that emphasizes the laziness of manipulating files in the file system, the love of Siril Scripting, and A/B testing.