MachineLP's starred repositories

ffmpeg_hw_decode

video stream hardware decoding and color space conversion by ffmpeg and cuda. thread safe.

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PINTO_model_zoo

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

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PaddleSeg

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

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PP-HumanSeg-opencv-onnxrun

分别使用OpenCV、ONNXRuntime部署PP-HumanSeg肖像分割模型,包含C++和Python两个版本的程序

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tflite-micro

Infrastructure to enable deployment of ML models to low-power resource-constrained embedded targets (including microcontrollers and digital signal processors).

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ColossalAI

Making large AI models cheaper, faster and more accessible

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coremltools

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

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mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

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ffmpegcv

The ffmpegcv is a ffmpeg backbone for open-cv like Video Reader and Writer

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nanoGPT

The simplest, fastest repository for training/finetuning medium-sized GPTs.

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MNN_Demo

🥭 移动端MNN部署学习笔记。支持Android与iOS。

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TNN

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.

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ncnn-portrait-segmentation

⚡️Real-time portrait segmentation

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XNNPACK

High-efficiency floating-point neural network inference operators for mobile, server, and Web

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DAMO-YOLO

DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.

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Swin-Transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

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mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

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awesome-pretrained-chinese-nlp-models

Awesome Pretrained Chinese NLP Models,高质量中文预训练模型&大模型&多模态模型&大语言模型集合

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ml-neuman

Official repository of NeuMan: Neural Human Radiance Field from a Single Video (ECCV 2022)

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ChatYuan

ChatYuan: Large Language Model for Dialogue in Chinese and English

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VulkanTutorialCN

Vulkan中文教程

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FastDeploy

⚡️An Easy-to-use and Fast Deep Learning Model Deployment Toolkit for ☁️Cloud 📱Mobile and 📹Edge. Including Image, Video, Text and Audio 20+ main stream scenarios and 150+ SOTA models with end-to-end optimization, multi-platform and multi-framework support.

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TextMatch

QAmatch(qa_match)/文本匹配/文本分类/文本embedding/文本聚类/文本检索(bow/ifidf/ngramtf-df/bert/albert/bm25/…/nn/gbdt/xgb/kmeans/dscan/faiss/….)

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RVM-Inference

🔥Robust Video Matting C++ inference toolkit with ONNXRuntime、MNN、NCNN and TNN, via lite.ai.toolkit.

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mnn_example

alibaba MNN, mobilenet classifier, centerface detecter, ultraface detecter, pfld landmarker and zqlandmarker, mobilefacenet

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MNN

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

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robustvideomatting-onnxruntime

使用ONNXRuntime部署鲁棒性视频抠图,包含C++和Python两种版本的程序

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ParC-Net

[ECCV 2022] Source code of "EdgeFormer: Improving Light-weight ConvNets by Learning from Vision Transformers"

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RobustVideoMatting

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

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Text2Human

Code for Text2Human (SIGGRAPH 2022). Paper: Text2Human: Text-Driven Controllable Human Image Generation

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