xlite-dev/lite.ai.toolkit

What it solves

Lite.Ai.ToolKit is a lightweight C++ toolkit designed to simplify the deployment of AI models. It provides a consistent, user-friendly API for integrating a vast library of pre-implemented AI models into applications, reducing the boilerplate code required to run inference across different hardware and runtimes.

How it works

The toolkit acts as a high-level wrapper around popular inference engines. It supports multiple backends including ONNXRuntime, MNN, NCNN, TNN, and TensorRT for NVIDIA GPUs. By providing a unified syntax (e.g., lite::cv::Type::Class), developers can load model weights and perform tasks like object detection or segmentation without needing to write low-level runtime-specific code.

Who it’s for

It is primarily for C++ developers who need to integrate computer vision or other AI capabilities into their software, particularly those targeting Linux, Windows, MacOS, or Android, and those looking for high-performance inference on both CPU and GPU.

Highlights

• Extensive Model Zoo: Includes over 300 C++ implementations and 500+ weights for various tasks.
• Broad Backend Support: Compatible with ONNXRuntime, MNN, NCNN, TNN, and TensorRT.
• Minimal Dependencies: Only requires OpenCV and ONNXRuntime by default.
• Hardware Acceleration: Specifically supports NVIDIA GPUs via TensorRT to boost inference performance.