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追寻梦土's Projects

clang-format icon clang-format

clang-format 配置文件,带一个批量格式化项目代码的脚本。

efficientnet icon efficientnet

Gluon implementation of EfficientNet and EfficientNet-lite

http icon http

Basic http server and client

incubator-mxnet icon incubator-mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

labelimgtool icon labelimgtool

:metal: LabelImgTool is a graphical image annotation tool which supports CLS,DET and SEG(semantic&instance )

labelme icon labelme

Annotation Tool for Object Segmentation.

mediamtx icon mediamtx

Also known as rtsp-simple-server. ready-to-use RTSP / RTMP / LL-HLS / WebRTC server and proxy that allows to read, publish and proxy video and audio streams.

mxnet-ssd icon mxnet-ssd

MXNet port of SSD: Single Shot MultiBox Object Detector. Reimplementation of https://github.com/weiliu89/caffe/tree/ssd

mxnet_goturn icon mxnet_goturn

A mxnet implementation of GOTURN: Generic Object Tracking Using Regression Networks.

nmssh icon nmssh

NMSSH is an Objective-C wrapper for libssh2, with a sweet API.

opensips icon opensips

OpenSIPS is a GPL implementation of a multi-functionality SIP Server that targets to deliver a high-level technical solution (performance, security and quality) to be used in professional SIP server platforms.

paddle icon paddle

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

protocolmaster icon protocolmaster

协议大师可以解析各种协议,支持各种信道,并且易于扩展

py-goturn icon py-goturn

This is the python implementation of single object tracking from GOTURN paper

pytorchocr icon pytorchocr

基于Pytorch的OCR工具库,支持常用的文字检测和识别算法

res2net icon res2net

The mxnet implemention of the paper Res2Net with gluon interface.

shufflenet-v2 icon shufflenet-v2

Shuffnet-v2 implementated with gluon, a dynamic graph interface of MXNet.

softmaxfocalloss icon softmaxfocalloss

the loss function in Aritcal ‘Focal Loss for Dense Object Detection‘’

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