Gauss Cannon, the Blender add on designed to streamline camera and point cloud workflows for Gaussian Splatting pipelines, has officially moved out of beta. Version 1.0.2, released this week, marks the first non-beta milestone for the tool and introduces a series of practical upgrades focused on usability, reliability, and pipeline compatibility.
Rather than defaulting to a hardcoded .png extension, Gauss Cannon now reads Blender’s active render output format through a json system and applies the correct file extension automatically, including PNG, EXR, JPEG, TIFF, and others.
The update also reshapes how point clouds are generated. What was previously a blocking operation has been redesigned as a responsive modal operator, allowing users to monitor progress directly within Blender’s interface. Artists can now see live progress feedback, view estimated time remaining in the header, and cancel the operation with a simple press of the ESC key.
Inside Blender’s UI, Gauss Cannon has received a visual cleanup. Panel sections have been reorganized for clarity, icons have been refreshed for quicker scanning, and a version footer has been added to make it easier to confirm which release is active. The Gauss Cannon codebase itself has been refactored into a more modular structure. Operators, UI components, and utility functions now live in clearly separated directories, a change accompanied by updated documentation reflecting the new architecture.
Gauss Cannon continues to operate as a Blender native add-on requiring Blender 4.2.0 or higher, with GPU support recommended for point cloud generation tasks. Its underlying system leverages Blender’s Python API alongside ray casting and BVH accelerated intersection routines to derive camera placement, detect interior positions, and generate geometry aware point data. Export pathways support both JSON camera descriptions and binary PLY point clouds compatible with common splatting workflows for Postshot and Lichtfeld Studio.
Gauss Cannon is available for free with a GPL 3.0 license on GitHub.
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