solidsf-inc/solidcv

选用指南

AI 根据 README 整理 · 2026/10/19 10:26:52

使用方式

作为 Rust 库使用，通过 cargo 引入，提供类似 opencv-rust 的 API。

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# solidcv **Pure-Rust OpenCV Replacement & Visual/Mechanistic Accelerator for LLMs, VLMs, and 3D Spatial Computing (`solidSF`)** `solidcv` (re-exported as `solidcv::opencv` for drop-in `opencv-rust` ergonomics) is a 100% pure-Rust, zero-FFI computer vision, stereo reconstruction, and mechanistic interpretability engine developed by **solidSF** (**Andy Norris**).

| **Geometric Mean Across All 14 Stages** | **Full 2D / 3D / 4D / VLM / SAE / Uplift Suite** | — | **OpenCV 5.0.0 & Dense Baselines** | — | **`12.11x`** | **Faster across all 14 stages (`1.33x` to `575.35x`)** | --- ## Quickstart ### 1. Drop-In Pure-Rust OpenCV Replacement + StereoSGBM & ArUco ```rust use solidcv::opencv::{calib3d, core, features2d, imgproc, prelude::*}; fn main() -> solidcv::Result<()> { let mut img = core::Mat::zeros(128, 128, core::CV_8UC1)?; imgproc::rectangle( &mut img, core::Rect::new(32, 32, 48, 48), core::Scalar::all(220.0),

部署要求

需要 Rust 环境，并针对 Apple Silicon 和 NVIDIA Grace-Blackwell 等特定硬件优化，但核心功能可在 CPU 上运行。

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It eliminates C++ `libopencv` build chains while unifying classical 2D/3D computer vision with **Pixelean bit-sliced algebra**, **Voxelean 3D octree topology**, **$(3+1)\text{D}$ Hyper-Voxelean Worldtubes**, **RealityComber** static-vs-moving scene separation, and native hardware kernels for **Apple Silicon (`aarch64` NEON + Metal 3.1 + WebGPU)** and **NVIDIA Grace-Blackwell GB300 / GB10 (`PTX 8.5+` Tensor Core `b1.xor.popc` + NVLink-C2C coherent slabs)**. --- ## Why `solidcv` Exists for the LLM / VLM & Mechanistic Interpretability Community

Reproducible via `cargo run --release --example full_suite_benchmark` on Apple Silicon Unified Memory (`AppleSiliconUnified`, 16 KB Metal NoCopy + 128-byte Tensor-Core-aligned `GraceCoherentSlab`) compared head-to-head against **OpenCV 5.0.0 (`libopencv` 5.0.0 `arm64` NEON / Accelerate)** and standard VLM / SAE / 3D voxel baselines: | Stage | Workload | `solidcv` (`--release`) | Next Best Option | Baseline Latency | Speedup | Mathematical / Hardware Advantage | | :--- | :--- | ---: | :--- | ---: | ---: | :--- |

已知限制

部分高级引擎（如 Gb300TensorCorePtx）通过专有云 API 提供，需要 solidSF Credits 计量使用。

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Proprietary high-throughput engines (`Gb300TensorCorePtx`, `RealityComber`, `Worldtube4D`, and `VoxeleanOctree`) are served over a zero-copy RFC-6455 Binary WebSocket stream metered in **`solidSF Credits`** (`1 USD = 1,000,000 credits`, `$10.00` welcome grant at [`solidsf.com/compute-credits`](https://solidsf.com/compute-credits)):  --- ## Full 14-Stage Benchmark Suite (`solidcv` vs. OpenCV 5.0.0 & Dense VLM/SAE/3D Baselines)