Thanks to visit codestin.com
Credit goes to github.com

Skip to content

blace-ai/hub

Repository files navigation

Header

A curated collection of ready-to-use AI models compatible with the blace.ai inference SDK.

🌟 Highlight Models

Segment Anything 3 — Image Segmentation 👉 Model Card
Depth Anything 2 — Depth Estimation 👉 Model Card
Memfof — Optical Flow 👉 Model Card

Header

Available Models

Model Configuration Category Link
Distillanydepth default Depth Estimation Model Card
Distillanydepth small Depth Estimation Model Card
Distillanydepth large Depth Estimation Model Card
BEN2 default Human Matting Model Card
Coordfill default Image Inpainting Model Card
Depth Anything V2 small Depth Estimation Model Card
Depth Anything 3 metric_large Depth Estimation Model Card
Depth Anything 3 mono_large Depth Estimation Model Card
Gemma 2b-v2 LLM Model Card
Llmdet default Open-Vocabulary Object Detection Model Card
Memfof default Optical Flow Estimation Model Card
Raft default Optical Flow Estimation Model Card
Retinexformer default Low Light Image Enhancement Model Card
Segment Anything 3 default Image Segmentation Model Card
Semantic Guided Human Matting default Human Matting Model Card
Videoflow default Optical Flow Estimation Model Card

Why blace.ai models?

Our hub is designed for developers who want cross-platform, plug-and-play AI in their native C++ applications with minimal setup. Model features:

  • ✅ Can be included with a few lines of code
  • ✅ Continuously tested across supported devices and backends
  • ✅ Self-contained — no Python required
  • ✅ Ship with easy-to-use demos
  • ✅ Hardware-Accelerated on CUDA, MPS and DirectML

Custom models

You can make your custom Torchscript and ONNX models compatible with the blace.ai runtime (Documentation).

Searchable Database

A searchable database of all models is available under https://blace.ai/hub.

About

Ready-to-deploy models including Segment Anything 3, Depth Anything 2 and Gemma.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages