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ByteDance, Southwest Jiaotong University
- Chengdu, China
Stars
The new Windows Terminal and the original Windows console host, all in the same place!
📚 C/C++ 技术面试基础知识总结,包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, in…
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)
An unidentifiable mechanism that helps you bypass GFW.
brpc is an Industrial-grade RPC framework using C++ Language, which is often used in high performance system such as Search, Storage, Machine learning, Advertisement, Recommendation etc. "brpc" mea…
An open source library for face detection in images. The face detection speed can reach 1000FPS.
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
A fast multi-producer, multi-consumer lock-free concurrent queue for C++11
Tars is a high-performance RPC framework based on name service and Tars protocol, also integrated administration platform, and implemented hosting-service via flexible schedule.
A simple C++11 Thread Pool implementation
搞定C++:punch:。C++ Primer 中文版第5版学习仓库,包括笔记和课后练习答案。
A Detailed Cplusplus Concurrency Tutorial 《C++ 并发编程指南》
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…
A fast single-producer, single-consumer lock-free queue for C++
快速入门CMake,通过例程学习语法。在线阅读地址:https://sfumecjf.github.io/cmake-examples-Chinese/
C++11/14/17/20 Concurrency Demystified: From Core Principles to Thread-Safe Code
📘《OpenCV3编程入门》书本配套源码 |《Introduction to OpenCV3 Programming》Book Source Code
tensorrt5 , centernet , centerface, deform conv, int8
🍡 LeetCode Online Judge刷题题解(Java/C++/Python/Ruby/Swift)
C++ port of Simple online and realtime tracking(SORT)
Paper ibrahim et al, cvpr 2016 - A Hierarchical Deep Temporal Model for Group Activity Recognition -