Command-line Tools
This page describes the standalone StarNet and DeepSNR command-line packages. Use these files for command-line workflows, automation, host applications, and standalone processing outside PixInsight.
Command-line tool releases
Command-line archives are for standalone processing, automation, and applications that call StarNet or DeepSNR executables directly. For example, Siril's StarNet integration uses the command-line StarNet installation path.
Release matrix
Current command-line packages are published for Linux x64, Windows x64, macOS x64, and macOS ARM64. StarNet2 and DeepSNR use the same version lines as the current PixInsight modules, but the command-line archives are separate files intended for terminal use, scripts, and host applications that call external executables.
Current ORT/CoreML command-line packages are self-contained. Users do not install a separate TensorFlow, Torch, or backend-runtime package.
Current command-line release matrix
| Operating system | Architecture | StarNet2 version | DeepSNR version | Backend |
|---|---|---|---|---|
| Linux | x64 | 2.5.0 | 1.2.0 | ONNX/ORT |
| Windows | x64 | 2.5.0 | 1.2.0 | ONNX/ORT |
| macOS | x64 | 2.5.0 | 1.2.0 | ONNX/ORT |
| macOS | ARM64 | 2.5.0 | 1.2.0 | CoreML |
Updates in the latest releases
Recent command-line releases focus on current runtime backends, clearer input/output behavior, and StarNet2 workflow additions:
- StarNet2 2.5.0 and DeepSNR 1.2.0 use ORT/CoreML as the current public command-line builds; TensorFlow and Torch builds are not part of this release and likely will not be part of future releases.
- Command-line input handling now preserves source bit depth for supported 8-bit and 16-bit integer images instead of relying on OpenCV's default 8-bit conversion path.
- Unsupported inputs, including 32-bit floating-point images and unsupported channel counts, are rejected. Convert them to 8-bit or 16-bit grayscale/RGB before running the command-line tool.
- TIFF and PNG outputs are written as 16-bit images by default; use
--eightonly when an 8-bit output file is intentionally needed. - StarNet2 adds
--unscreenfor an optional star-layer output alongside the existing starless output and optional subtractive mask. - macOS ARM64 command-line packages use native CoreML and are the recommended Apple Silicon lane for best performance.
Command-line download pages
- StarNet CLI tools Current StarNet command-line archives and previous recovery files
- DeepSNR CLI tools Current DeepSNR command-line archives
- Legacy Legacy releases