Lite.Ai.Toolkit

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lite.ai.toolkit is a C++ AI toolkit that provides over 100 AI models for various tasks like object detection, segmentation, and face fusion. It supports MNN, ORT, and TRT for efficient inference.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is lite.ai.toolkit?

lite.ai.toolkit is a comprehensive C++ AI toolkit offering over 100 pre-trained AI models for a wide range of computer vision tasks. It supports multiple inference engines including MNN, ONNX Runtime (ORT), and TensorRT (TRT), allowing for flexible deployment across different platforms like Linux, macOS, Windows, and Android. The toolkit includes models for object detection (YOLO series, SSD, EfficientDet), face detection and recognition (RetinaFace, ArcFace), segmentation (MODNet, RobustVideoMatting), and other advanced functionalities like Stable Diffusion and Face Fusion. It emphasizes simplicity and user-friendliness with consistent syntax, minimal dependencies, and detailed build instructions for easy integration into C++ projects.

Best used for

Ideal for developers and data scientists who need to integrate a wide array of AI models into C++ applications, perform object detection, and implement face recognition. Especially valuable for those requiring efficient inference across various platforms using MNN, ONNX Runtime, or TensorRT.

Common actions

implement AI models

develop computer vision

integrate AI toolkit

deploy AI inference

github copilot"AI Agents"low-code/no-codeworkflowsdeepfakeopen-sourceautomated workflowcollaborationface swapping

Capabilities

Key features

100+ AI models
MNN/ORT/TRT support
Object detection
Face recognition
Image segmentation
Stable Diffusion
Face fusion

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What types of AI models are included in lite.ai.toolkit?

The toolkit includes over 100 AI models covering object detection (YOLO, SSD), face detection and recognition (RetinaFace, ArcFace), image segmentation (MODNet), and advanced generative models like Stable Diffusion and Face Fusion. It offers a comprehensive suite for various computer vision applications.

Which inference engines does lite.ai.toolkit support?

lite.ai.toolkit supports multiple inference engines to optimize performance and compatibility. These include MNN, ONNX Runtime (ORT), and TensorRT (TRT). This flexibility allows users to choose the best engine for their specific hardware and performance requirements.

What are the minimum dependencies required to use lite.ai.toolkit?

By default, lite.ai.toolkit requires minimal dependencies, primarily OpenCV and ONNXRuntime. Users can also enable MNN support during the build process. This design choice aims to simplify integration and reduce potential conflicts with existing project setups.

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AI Agents & Automation › AI Frameworks & Infra

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