xlite-dev/lite.ai.toolkit

Health v2 · maintenance only

Adoption not part of the score

4427 stars · 785 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A lightweight C++ toolkit providing unified APIs for 100+ pre-trained AI models across inference backends like ONNX Runtime, MNN, TensorRT, TNN, and NCNN. It covers object detection, segmentation, face detection/recognition, matting, Stable Diffusion, and Face Fusion.

Use cases

• run yolov5/yolov8 object detection in C++
• deploy face detection and recognition models natively
• run stable diffusion image generation in C++
• perform image matting and background removal
• swap inference backends between onnxruntime, mnn, and tensorrt
• port python AI models to C++ production applications

When to choose

• you need C++ inference for many vision models with a consistent API
• you want to deploy models on CPU or GPU without Python dependencies
• you need multiple backend support (ORT, MNN, TRT, NCNN, TNN) in one toolkit

When to avoid

• you need training or fine-tuning capabilities
• you work primarily in Python and don't need C++ integration
• you need a model not covered by its model zoo

Facets

library · maturity active

machine-learning deep-learning image-processing computer-vision llm-inference stable-diffusion computer-vision machine-learning deep-learning image-processing artificial-intelligence cpp cross-platform onnxruntime tensorrt mnn ncnn tnn yolov8 object-detection face-recognition segmentation matting face-fusion model-zoo inference linux gpu

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