autonomi-nos 0.0.7

Nitrous oxide system (NOS) for computer-vision.

nos 🔥: Nitrous Oxide System (NOS) for Computer Vision

NOS is a PyTorch library for optimizing and running lightning-fast inference of popular computer vision models. NOS inherits its name from "Nitrous Oxide System", the performance-enhancing system typically used in racing cars. NOS is designed to be modular and easy to extend.

Why NOS?

• ⚡️ Fast: Built for PyTorch and designed to optimize/run models faster
• 🔥 Performant: Run models such as SDv2 or object detection 2-3x faster out-of-the-box
• 👩‍💻 No PhD required: Optimize models for maximum HW performance without a PhD in ML
• 📦 Extensible: Easily add optimization and HW-support for custom models
• ⚙️ HW-accelerated: Take full advantage of your HW (GPUs, ASICs) without compromise
• ☁️ Cloud-agnostic: Run on any cloud HW (AWS, GCP, Azure, Lambda Labs, On-Prem)

Batteries Included

• 💪 SOTA Model Support: NOS provides out-of-the-box support for popular CV models such as Stable Diffusion, OpenAI CLIP, YOLOX object detection, tracking and more
• 🔌 APIs: NOS provides out-of-the-box APIs and avoids all the ML model deployment hassles
• 🐳 Docker: NOS ships with docker images to run accelerated and scalable CV workloads
• 📈 Multi-Platform: NOS allows you to run models on different HW (NVIDIA, custom ASICs) without any model compilation or runtime management.

Contribute

We welcome contributions! Please see our contributing guide for more information.