Laminar
Native planetary imaging capture for macOS and Apple Silicon
What it does
Laminar is the first planetary imaging capture app built natively for macOS. Record high-framerate SER video of Jupiter, Saturn, the Moon, and the Sun through your telescope with real-time frame quality analysis, atmospheric seeing scores, and automatic target tracking. Built in Swift with Metal GPU acceleration for Apple Silicon. Supports ZWO ASI and PlayerOne cameras. Free to download with an optional one-time Pro upgrade. A native Mac alternative to FireCapture and SharpCap.
Does the same job
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I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files. Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as…
- ASApple's SHARP running in the browser via ONNX runtime webMay 2026 · github.com · ▲185
Hi HN, author here. SHARP is Apple's recent single-image 3D Gaussian splatting model (https://arxiv.org/abs/2512.10685). Their reference code is PyTorch + a pretty heavy pipeline; I wanted to see if it could run in a browser with no server hop, so I exported the predictor to ONNX and ran it via onnxruntime-web with the WebGPU EP. What works: drop in an image, get a .ply you can download or preview live, all on your machine — your image never leaves the tab. The model is large (~2.4 GB sidecar) so first load is slow on a cold cache, but inference itself is a few seconds on…
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