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insightface

State-of-the-art 2D and 3D Face Analysis Project

Language:PythonMIT100

MASR

Pytorch实现的流式与非流式的自动语音识别框架，同时兼容在线和离线识别，目前支持DeepSpeech2模型，支持多种数据增强方法。

Language:PythonApache-2.0100

Serving

A flexible, high-performance carrier for machine learning models（『飞桨』服务化部署框架）

Language:C++Apache-2.0100

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

Language:C++NOASSERTION100

lite.ai.toolkit

🍅🍅A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOX, YOLOP, YOLOv5, YOLOR, NanoDet, YOLOX, SCRFD, YOLOX . MNN, NCNN, TNN, ONNXRuntime, CPU/GPU.

Language:C++GPL-3.0000

MaskTheFace

Convert face dataset to masked dataset

Language:PythonMIT000

MNN

MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba

Language:C++000

MNNKit

MNNKit is a collection of AI solutions for mobile developers, powered by MNN engine.

Language:Objective-CNOASSERTION000

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

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onnx

Open standard for machine learning interoperability

Language:C++Apache-2.0000

Paddle2ONNX

ONNX Model Exporter for PaddlePaddle

Apache-2.0000

PaddleOCR

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)