vision-rs / Appendix
FAQ & Roadmap
Roadmap
vision-rs doesn’t have a published, authoritative roadmap yet. What’s implemented today:
- Model support: YOLO26 (variants N/S/M/L/XL), inference and training (single-head and dual-assignment).
- Deployment: cross-compilation and packaging for Jetson Orin Nano.
- Kernels: Flash Attention 2, PSA attention wrappers, detect-decode, CIoU/classification loss.
DetectorConfig is deliberately structured as an enum over model families
(see The Detection API) so additional
model families can be added without breaking the top-level
ObjectDetector API — check the
repository for current activity
if you need to know what’s actively being worked on.
FAQ
Why is cuda a default feature rather than optional?
Because vision-rs’s models are traced through teenygrad’s computational
graph and lowered to GPU kernels — there’s currently no CPU execution path
for the shipped models. --no-default-features still builds and documents
the parts of the crate that aren’t behind cuda/training (mostly type
definitions), which is what powers this crate’s docs.rs page, but it won’t
get you a runnable detector without a GPU.
Why does this depend on a custom Rust compiler fork (teenyc)?
Only for compiling GPU kernels (see
The teenyc Toolchain) —
the crate itself builds with stable rustc. The kernel DSL compiles
through an MLIR backend that isn’t part of upstream rustc, so a separate
compiler handles just that piece, either just-in-time during development or
ahead-of-time when packaging for deployment.
Can I install this from crates.io yet?
Not yet published — vision-rs depends on several teeny-* crates from
teenygrad that aren’t live on
crates.io yet either. Once they are, [patch.crates-io] in Cargo.toml
comes out and vision-rs publishes normally.