setiastrosuitepro 1.14.10.post1

Seti Astro Suite Pro - Advanced astrophotography toolkit for image calibration, stacking, registration, photometry, and visualization

Seti Astro Suite Pro (SASpro)

Author: Franklin Marek

Website: www.setiastro.com

Contributors

The following individuals have made substantial contributions to the development of Seti Astro Suite Pro. Their work spans core architecture, tooling, platform support, localization, and documentation.

Fabio Tempera

• Complete structural refactoring of setiastrosuitepro.py (20,000+ lines), including elimination of duplicated logic and consolidation of responsibilities across the entire codebase
• Implementation of the AstroSpikes tool, Texture and Clarity processing module, real-time system resource monitor, and application usage statistics panel
• Addition of more than ten interface language translations, covering Arabic, German, Spanish, French, Hindi, Italian, Japanese, Portuguese, Russian, Swahili, Ukrainian, and Chinese
• Design and implementation of UI layout components, startup splash window, and application initialization optimizations
• Introduction of lazy import strategies, module-level caching mechanisms, and utility function libraries to reduce startup time and memory footprint
• Authorship of this README and project documentation

Joaquin Rodriguez

• Migration of the project dependency system to Poetry, introducing pyproject.toml as the canonical dependency manifest and establishing a reproducible build environment

Tim Dicke

• Development of native installers for Windows and macOS
• Authorship and ongoing maintenance of macOS-specific Wiki installation instructions
• Application testing across platforms and resolution of minor defects

Michael Lev

• Addition of the Hebrew (he) interface translation

Andrew Witwicki

• Addition of the Ukrainian (uk) interface translation

Overview

Seti Astro Suite Pro (SASpro) is a comprehensive astrophotography processing toolkit designed to cover the full image processing pipeline — from raw calibration frames through final export. The application targets both amateur astrophotographers and professional researchers, providing a graphical user interface suitable for interactive workflows as well as scripting interfaces for batch automation.

The project is built around three principal objectives:

• Produce repeatable, high-quality results through well-defined, algorithm-driven processing pipelines
• Expose advanced image processing capabilities through an accessible and consistent graphical interface
• Maintain a modular, extensible codebase that accommodates community contributions without sacrificing architectural coherence

SASpro is distributed as donationware. It is free to use, with an optional suggested donation to support continued development.

Features

Image Format Support

SASpro supports a broad range of astronomical and general-purpose image formats:

• FITS — the standard format for scientific astronomical imaging
• XISF — PixInsight's native extensible image serialization format
• TIFF — high-bit-depth raster format widely used in post-processing workflows
• RAW — native sensor data from digital cameras (via appropriate decoding libraries)
• PNG / JPEG — standard raster formats for preview and export purposes

Calibration and Pre-Processing

• Master frame generation and application: bias, dark, and flat calibration pipelines
• Debayering (CFA demosaicing) for color sensor data
• Pedestal removal and sensor-level corrections
• SER file batch import and stacking for planetary imaging sequences

Registration and Stacking

• Automated star detection and feature-based image registration
• Multi-frame stacking with configurable rejection algorithms
• Comet stacking mode with dual-target alignment support
• Live stacking interface for real-time session accumulation
• Mosaic composition tooling for multi-panel wide-field imaging

Photometry and Astrometry

• Aperture photometry with configurable aperture and annulus parameters
• Signal-to-noise ratio (SNR) measurement tool
• Plate solving integration for accurate world coordinate system (WCS) assignment
• GAIA catalog downloader for reference star data
• Minor body catalog integration for asteroid and comet identification
• Exoplanet transit detection utility
• Supernova and asteroid hunting tool

Color Processing

• Spectrophotometric color calibration (SPCC)
• Narrowband-to-RGB combination with normalization tools
• Background neutralization and gradient removal (including GraXpert integration)
• Selective color and selective luminance adjustment
• White balance correction (including star-based white balance)
• Green channel noise suppression (SCNR)
• RGB channel extraction, combination, and alignment

Stretching and Tone Mapping

• Generalized Hyperbolic Stretch (GHS) with interactive preview
• Statistical stretch and auto-stretch utilities
• CLAHE (Contrast Limited Adaptive Histogram Equalization)
• Histogram transformation with interactive curve manipulation
• Wavescale HDR processing pipeline
• Multiscale decomposition for detail and layer separation
• Frequency separation for independent large-scale and fine-detail processing

AI-Assisted Processing

• CosmicClarity engine suite: denoising, sharpening, dark star recovery, super-resolution, and satellite trail removal
• Syqon Prism denoising engine
• Syqon Parallax sharpening engine
• Syqon NafNet starless separation engine
• AI-driven aberration correction module
• Multi-frame deconvolution (MFDeconv) with CuDNN and sport-mode variants
• Morphological star reduction and halo suppression

Masking and Layers

• Interactive mask creation, application, and removal
• Layer-based compositing system with dockable layer panel
• Clone stamp and blemish removal tools
• Image combine with configurable blend modes

Utilities and Tools

• FITS header viewer and metadata editor
• PSF (Point Spread Function) viewer and analysis
• Isophote fitting for galaxy morphology analysis
• Finder chart generation
• ACV curve export compatibility
• Pixel math scripting interface
• Batch conversion and batch renaming utilities
• History explorer for processing session review
• AstroBin export integration
• Keyboard shortcut manager
• Application statistics panel
• Real-time system resource monitor (CPU, memory, GPU)
• Blink comparator for image-to-image comparison

Internationalization

The interface is fully localized in the following languages, with compiled Qt translation files (.qm) provided for each:

Language	Code
Arabic	ar
German	de
Spanish	es
French	fr
Hebrew	he
Hindi	hi
Italian	it
Japanese	ja
Portuguese	pt
Russian	ru
Swahili	sw
Ukrainian	uk
Chinese (Simplified)	zh

Architecture and Project Layout

The repository follows a modular package structure. The primary application code resides under src/setiastro/saspro/, with supporting tooling and configuration at the repository root.

Top-Level Directory Overview

Path	Description
src/setiastro/saspro/	Core application package containing all processing modules, GUI components, engines, and utilities
src/setiastro/data/	Bundled data assets including the main FITS dataset and all CSV catalogs
src/setiastro/images/	All application icons, toolbar images, and UI graphic assets
src/setiastro/qml/	QML components, including the system resource monitor overlay
ops/	Repository-level tooling scripts for build management and dependency export
config/	Packaging configuration files, including PyInstaller .spec files
build/	Distribution and packaging output scripts
logs/	Runtime log output directory (development mode)

Internal Package Structure (src/setiastro/saspro/)

gui/

The graphical interface layer, organized using a mixin-based composition pattern to isolate concerns across the main window:

Module	Responsibility
main_window.py	Central application window; coordinates all docks, toolbars, and the MDI workspace
statistics_dialog.py	Application usage statistics dialog
mixins/dock_mixin.py	Dockable panel management
mixins/file_mixin.py	File open, save, and recent file handling
mixins/geometry_mixin.py	Window geometry persistence and restoration
mixins/header_mixin.py	FITS header display integration
mixins/mask_mixin.py	Mask workflow integration
mixins/menu_mixin.py	Menu bar construction and action wiring
mixins/theme_mixin.py	Application theme and stylesheet management
mixins/toolbar_mixin.py	Toolbar layout and tool action registration
mixins/update_mixin.py	Update check and notification handling
mixins/view_mixin.py	Zoom, pan, and view state management

widgets/

Reusable UI components shared across processing dialogs:

Module	Responsibility
common_utilities.py	Shared widget helper functions
graphics_views.py	Custom QGraphicsView subclasses for image display
image_utils.py	Image conversion and display pipeline utilities
preview_dialogs.py	Base classes for before/after preview dialog patterns
resource_monitor.py	Real-time CPU, memory, and GPU utilization widget
spinboxes.py	Extended numeric input controls
themed_buttons.py	Consistently styled button components
wavelet_utils.py	Wavelet decomposition utilities shared across processing tools
minigame/	Embedded browser-based minigame (HTML/CSS/JS)

cosmicclarity_engines/

Inference engine wrappers for the CosmicClarity AI model family:

Engine	Function
benchmark_engine.py	Hardware performance benchmarking
darkstar_engine.py	Dark star recovery and enhancement
denoise_engine.py	AI-based noise suppression
satellite_engine.py	Satellite and aircraft trail detection and removal
sharpen_engine.py	AI-based image sharpening
superres_engine.py	Super-resolution upscaling

denoise_engines/ / sharpen_engines/ / starless_engines/

Additional AI inference engines based on the Syqon model family:

Engine	Function
syqon_prism_engine.py	Alternative denoising pipeline
syqon_parallax_engine.py	Alternative sharpening pipeline
syqon_nafnet_engine.py	Star removal for starless processing workflows

imageops/

Low-level image processing algorithms operating directly on array data:

Module	Function
stretch.py	Core stretching algorithms
narrowband_normalization.py	Narrowband channel normalization
scnr.py	Selective color noise reduction
serloader.py	SER video format frame loader
starbasedwhitebalance.py	Star-color-based white balance computation
mdi_snap.py	MDI subwindow snapping geometry utilities

translations/

Qt Linguist translation sources (.ts) and compiled binaries (.qm) for all supported interface languages, along with Python-side translation dictionaries and integration tooling.

ops/

Application-level operational components:

Module	Function
settings.py	Persistent user preferences and configuration
commands.py	Undo/redo command objects
command_runner.py	Command execution and history stack
scripts.py	Script execution runtime
script_editor.py	Integrated script editor dialog
benchmark.py	System benchmark orchestration

legacy/

Retained modules providing backward compatibility:

Module	Function
image_manager.py	Legacy image slot management interface
xisf.py	XISF format reader/writer
numba_utils.py	Legacy Numba JIT utility functions

Notable Root-Level Files

File	Description
setiastrosuitepro.py	Primary application entry point for development execution
pyproject.toml	Poetry-managed dependency manifest and project metadata
requirements.txt	pip-compatible dependency list generated from pyproject.toml
poetry.lock	Locked dependency resolution for reproducible environments
create_dmg.sh	Shell script for macOS DMG image creation
update_saspro.sh	Application update script
updates.json	Update manifest consumed by the in-application update checker
numba_runtime_hook.py	PyInstaller runtime hook for Numba JIT initialization
profile_init.py	Startup profiling utility for performance diagnostics
PUBLISHING.md	Internal release and publishing procedures

Repository Structure

setiastrosuitepro/
|-- ops/
|   |-- __init__.py
|   |-- export_requirements.py
|   |-- prime_matplotlib_cache.py
|   `-- write_build_info.py
|-- src/
|   `-- setiastro/
|       |-- data/
|       |   |-- catalogs/
|       |   |   |-- astrobin_filters.csv
|       |   |   |-- astrobin_filters_page1_local.csv
|       |   |   |-- cali2.csv
|       |   |   |-- cali2color.csv
|       |   |   |-- celestial_catalog.csv
|       |   |   |-- detected_stars.csv
|       |   |   |-- fits_header_data.csv
|       |   |   |-- List_of_Galaxies_with_Distances_Gly.csv
|       |   |   `-- updated_celestial_catalog.csv
|       |   `-- SASP_data.fits
|       |-- images/
|       |   `-- [application icons and UI graphics]
|       |-- qml/
|       |   `-- ResourceMonitor.qml
|       |-- saspro/
|       |   |-- _generated/
|       |   |-- cosmicclarity_engines/
|       |   |-- denoise_engines/
|       |   |-- gui/
|       |   |   `-- mixins/
|       |   |-- imageops/
|       |   |-- legacy/
|       |   |-- ops/
|       |   |-- sharpen_engines/
|       |   |-- starless_engines/
|       |   |-- syqon_model/
|       |   |-- syqon_parallax_model/
|       |   |-- syqon_prism_model/
|       |   |-- translations/
|       |   |-- widgets/
|       |   |   `-- minigame/
|       |   |-- __init__.py
|       |   |-- __main__.py
|       |   `-- [application modules]
|       `-- __init__.py
|-- .gitattributes
|-- .gitignore
|-- create_dmg.sh
|-- LICENSE
|-- numba_runtime_hook.py
|-- poetry.lock
|-- pyproject.toml
|-- requirements.txt
|-- setiastrosuitepro.py
|-- update_saspro.sh
|-- updates.json
`-- README.md

Development Setup

The following procedure describes how to establish a local development environment from source. The instructions apply to all supported platforms; platform-specific commands are noted where they differ.

Prerequisites

• Python 3.10 or later
• pip 23.0 or later (upgraded during setup)
• Git

Step 1 — Clone the Repository

git clone https://github.com/setiastro/setiastrosuitepro.git
cd setiastrosuitepro

Step 2 — Create and Activate a Virtual Environment

Windows (PowerShell):

python -m venv .venv
.\.venv\Scripts\Activate.ps1

If script execution is restricted by the system policy, adjust the execution policy for the current process:

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope Process

Windows (Command Prompt):

python -m venv .venv
.venv\Scripts\Activate.bat

macOS / Linux:

python3 -m venv .venv
source .venv/bin/activate

Step 3 — Install Dependencies

python -m pip install --upgrade pip
pip install -r requirements.txt

Step 4 — Launch the Application

python setiastrosuitepro.py

Dependency Management

This project uses Poetry as its authoritative dependency management tool. The pyproject.toml file defines all runtime and development dependencies. The requirements.txt file is a derived artifact generated from pyproject.toml to ensure compatibility with standard pip-based workflows.

For Contributors and Maintainers

All dependency additions or modifications must be made through pyproject.toml. After modifying dependencies, regenerate requirements.txt using one of the following methods:

Using the project export script:

poetry run python ops/export_requirements.py

Using Poetry directly:

poetry export -f requirements.txt --without-hashes --without dev -o requirements.txt

Commit both pyproject.toml and the regenerated requirements.txt together in the same commit.

For End Users

Standard pip installation from requirements.txt remains fully supported and requires no knowledge of Poetry:

pip install -r requirements.txt

The requirements.txt file is maintained in a current state at all times.

Data and Catalogs

All reference data and catalog files are located under src/setiastro/data/:

• SASP_data.fits — the primary application dataset used by multiple processing modules. This file is large and is excluded from version control via .gitignore where applicable. It must be obtained separately or via the official distribution package.
• data/catalogs/ — CSV-format astronomical catalogs including filter databases, celestial object catalogs, galaxy distance tables, and calibration reference data.

When adding custom catalogs, adhere to the CSV schema of the existing files and register the new catalog path using the get_data_path() helper function defined in resources.py.

Logging

During development, the application writes log output to saspro.log within the logs/ directory at the project root. In installed or packaged builds, log files are written to the appropriate per-platform user data directory.

Log file path resolution is implemented in setiastrosuitepro.py. Ensure the logs/ directory exists and is writable when running in development mode to facilitate debugging.

Testing

Unit and integration tests are placed in the tests/ directory and executed using pytest.

Install pytest:

pip install pytest

Run the test suite:

pytest -q

Contributors are encouraged to include tests for new functionality and to verify that existing tests pass before submitting a pull request.

Packaging

macOS

The repository includes a PyInstaller specification file and a DMG creation script for macOS distribution:

pip install pyinstaller
pyinstaller --clean -y config/setiastrosuitepro_mac.spec
bash create_dmg.sh

Ensure the .spec file includes src/setiastro/data/ and src/setiastro/data/catalogs/ in its datas list so that all required assets are bundled correctly.

Windows

Windows installer development is managed by Tim Dicke. Refer to the project Wiki for current Windows packaging instructions.

Resource Path Resolution

When running as a packaged application, all data and asset paths are resolved through the pro.resources module. Use get_resource_path() and get_data_path() for any file access that must function correctly in both development and packaged contexts.

Contributing

Contributions to SASpro are welcome. Please observe the following guidelines to maintain consistency and quality across the codebase.

Workflow

1. Fork the repository on GitHub.
2. Create a dedicated feature branch from main:

   git checkout -b feature/your-feature-name
   

3. Implement your changes. Keep commits atomic and scoped to a single logical change.
4. Include or update tests where applicable.
5. Regenerate requirements.txt if dependencies were modified.
6. Open a pull request against main, providing a clear description of the change, its motivation, and any relevant context.

Code Standards

• Follow PEP 8 style conventions throughout.
• All new user-facing strings must be passed through the internationalization system (i18n.py) to support translation.
• New tools or processing dialogs should follow the established pattern of separating business logic from UI code.
• Avoid introducing large binary files into the repository. Data files should be referenced in .gitignore and distributed through appropriate channels.

For detailed repository-specific guidelines, refer to CONTRIBUTING.md.

Troubleshooting

Missing Data Files

If the application reports that a CSV or FITS file cannot be located, verify that the src/setiastro/data/ and src/setiastro/data/catalogs/ directories are present and populated. In packaged builds, confirm that these paths are included in the PyInstaller .spec configuration.

Missing Dependencies

pip install -r requirements.txt

Ensure the virtual environment is activated before running this command.

Log Write Permission Errors

Ensure the logs/ directory exists and is writable by the current user. On some systems, elevated privileges may be required during the packaging phase.

Reporting Bugs

If a reproducible defect is identified, open an issue on GitHub and attach the contents of saspro.log. Include the operating system version, Python version, and a minimal description of the steps required to reproduce the problem.

License

Seti Astro Suite Pro is licensed under the GNU General Public License v3.0. See the LICENSE file at the repository root for the full license text.

Acknowledgments

The authors gratefully acknowledge the open-source libraries and projects upon which SASpro depends, as well as the broader astrophotography community whose feedback has continuously shaped the direction of development.

Contact and Links

Resource	URL
Official Website	https://www.setiastro.com
Source Repository	https://github.com/setiastro/setiastrosuitepro
Issue Tracker	https://github.com/setiastro/setiastrosuitepro/issues