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, current releases and system requirements, and where the shared installation instructions live.

PixInsight module releases

Supported PixInsight versions: 1.9.4 and 1.9.5 only. Intel Mac modules remain on PixInsight 1.9.4.

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 platforms for each tool: Linux x64, Windows x64, macOS x64, and macOS ARM64. Each platform supports 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 / build Backend Release date
Linux x64 2.6.0-0235 ONNX/ORT 2026-09-13
Windows x64 2.6.0-0235 ONNX/ORT + DirectML 2026-09-13
macOS x64 2.6.0-0235 ONNX/ORT 2026-09-13
macOS ARM64 2.6.0-0235 CoreML 2026-09-13

Current DeepSNR PixInsight release matrix

Operating system Architecture Version / build Backend Release date
Linux x64 1.3.0-0141 ONNX/ORT 2026-09-13
Windows x64 1.3.0-0141 ONNX/ORT + DirectML 2026-09-13
macOS x64 1.3.0-0141 ONNX/ORT 2026-09-13
macOS ARM64 1.3.0-0141 CoreML 2026-09-13

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. Your PixInsight version may require a newer operating system.

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 LTS / WSL2; Linux PixInsight 1.9.4 for validation.
Windows x64 Windows x64 PixInsight on 64-bit Windows 10 or 11. DirectML runtime libraries are not bundled with StarNet Software packages. They should already be present on most supported Windows installations; missing DirectML components are the exception. See Microsoft's DirectML version history and official DirectML package. Windows 11 x64; Windows x64 PixInsight for validation.
macOS x64 macOS x64 PixInsight on macOS 13.4 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

StarNet2 2.6.0

  • Restore clipped pixels restores original pixel values clipped during stretching after the image is returned to linear form.
  • The interface remembers its last-used options across PixInsight sessions. Reset restores factory defaults.

DeepSNR 1.3.0

  • The interface remembers its last-used options across PixInsight sessions. Reset restores factory defaults.

Both releases also include minor bug fixes and improvements.

See the StarNet module reference for clipped-pixel restoration and output behavior, and the DeepSNR module reference for settings and input guidance.

Runtime support

  • Current packages use ONNX/ORT on Linux, Windows, and macOS x64, and CoreML on macOS ARM64.
  • Windows modules support DirectML acceleration on compatible systems, with CPU fallback. Advanced manual CUDA setup remains optional.
  • TensorFlow packages are discontinued. Remove old /tensorflow/ repository URLs when updating your repository list.

Installation information