StarNet Software

AI-powered software for star removal and noise reduction in astrophotography.

PixInsight Modules

This page describes the StarNet and DeepSNR PixInsight modules: which repository to add, what changed in the current backend/runtime setup, and where the shared installation instructions live.

PixInsight module releases

StarNet and DeepSNR are now installed in PixInsight through tool-specific repositories. Current releases use a single repository for each tool.

The old TensorFlow/runtime repository path is deprecated for new installs.

Release matrix

The PixInsight release matrix has four package lanes for each tool: Linux x64, Windows x64, macOS x64, and macOS ARM64. Each lane ships both StarNet2 and DeepSNR through the tool-specific PixInsight repositories.

Current ORT/CoreML PixInsight packages are self-contained per module. Users do not install a separate TensorFlow, Torch, or backend-runtime package.

Current StarNet2 PixInsight release matrix

Operating system Architecture Version Backend Release date
Linux x64 2.5.2 ONNX/ORT 2026-06-06
Windows x64 2.5.2 ONNX/ORT 2026-06-06
macOS x64 2.5.2 ONNX/ORT 2026-06-06
macOS ARM64 2.5.2 CoreML 2026-06-06

Current DeepSNR PixInsight release matrix

Operating system Architecture Version Backend Release date
Linux x64 1.2.1 ONNX/ORT 2026-05-30
Windows x64 1.2.1 ONNX/ORT 2026-05-30
macOS x64 1.2.0 ONNX/ORT 2026-05-27
macOS ARM64 1.2.0 CoreML 2026-05-27

The architecture column above refers to the installed PixInsight architecture, not hardware architecture. PixInsight x64 installations on Apple Silicon Macs do not get GPU acceleration even when the hardware has an Apple GPU. For maximum StarNet2 and DeepSNR performance on Apple Silicon, install the PixInsight 1.9.4 ARM64 build.

System and build information

Current PixInsight module packages are self-contained per module. The table below separates what users need to run the package from the systems used to build and validate the release.

Current PixInsight module system information

Target Runtime requirement Built and validated on
Linux x64 Linux x64 PixInsight on a compatible glibc-based Linux distribution. Ubuntu 24.04.2 LTS / WSL2; Linux PixInsight 1.9.4 for validation.
Windows x64 Windows x64 PixInsight on 64-bit Windows 10 or 11. Windows 11 x64; Windows x64 PixInsight for validation.
macOS x64 macOS x64 PixInsight on macOS 13.1 or newer. Intel Mac, or Apple Silicon through Rosetta 2. macOS 26.5 Tahoe on Apple Silicon; macOS x64 PixInsight for validation.
macOS ARM64 macOS ARM64 PixInsight on Apple Silicon with macOS 13.1 or newer. macOS 26.5 Tahoe on Apple Silicon; macOS ARM64 PixInsight 1.9.4 for validation.

Current PixInsight module packages do not require TensorFlow, Torch, separate ONNX Runtime installation, or the old /tensorflow/ repository URLs.

Updates in the latest releases

Recent PixInsight module updates focus on simpler installation, current runtime backends, and clearer behavior:

  • TensorFlow packages are discontinued; remove old /tensorflow/ repository URLs or ignore errors from those old repositories.
  • Current packages use ORT/CoreML instead of TensorFlow: ONNX/ORT on Linux, Windows, and macOS x64; CoreML on macOS ARM64.
  • StarNet2 2.5.2 improves highlight protection in very bright image regions and fixes unscreen star-layer artifacts in saturated or near-saturated regions.
  • DeepSNR 1.2.1 Linux and Windows PixInsight modules were released on 2026-05-30. macOS DeepSNR packages remain on 1.2.0.
  • Windows ONNX/ORT modules can use optional NVIDIA CUDA acceleration when a compatible CUDA runtime is installed; otherwise they run on CPU. See Windows PixInsight CUDA setup instructions.

Installation information