pearl_house

Introduction

This is a library which aiming to save all my code about cpp. It will help me to write code conveniently. I want to save some value codes during daily time. that will make me not focus on duplicate code again. Besides that, search others work and reuse always take too many time to adjusted, it envolve me to note every value thing in cpp. I believe it can been finished to add with time going by. Why I called it as pearl_house? Because I think these libs consist a hug vale in rest life. Just Hoping, Trying, Waiting!

We define a libs contracture, which name pearl_house, as follow:

1. bin : conf file and exe file can been seen in here.
2. build : generate Cmake file and other junk file.
3. lib : all the lab is generate in this path.
4. kernel : it contain many important libs. many sub-lib such as base_algorithm contain example,include, src.

• kernel/*/example: it contain the demo how to using this lib.
• kernel/*/include: it contain head file in sub-lab.
• kernel/*/src : sub-lib source code, it not display for other people.
• kernel/*/test : test this sub whether have bug and performance.
• kernel/* : this path is mean that which lib we want to build. it is so important. In the beginning, we want to build these lib for work.
• • base_algorithm : save some sort algorithm, design pattern or others(such like LRU). I have no idea at this moment.
• • base_structure : save some basic structure、 safe structure in threads.
• • memorandum : save some daily work code , debug experience in system design, effective c++ code experiences.
• • network_engineer: save basic engineer in network, all the module need to un-connection.
• • backend_middleware: save some middleware, like nginx, rpc, redis,mysql,es source code help me to fast build project and understand achieve rule.
• • backend_projects: using pre libs to achieve a high level backend project, not limit language.
• • SOTA_things : do a project to achieve SOTA performance.
• • deep_learning: some common code about deep learning work. Like audiovisual, NLP.

5. CMakeLists.txt : Cmake to manage all libs compile.
6. autobuild.sh to compile automation.

How to use it ?

base_algorithm part

deep_learning part

1. Using FastAudioVisual lib to develop your model in audiovisual please ref : fast_audiovisual readme.md

writing requirement:

1. all knowledge should have a high-level quality, but it needs to have self understand and concise. If other articles are good for us, please make a cite.
2. It need has rule about notes.
3. please don't write an essential part causally. Be serious!
4. make the whole framework is reasonable.
5. If some word is not well to understand by English, Please using Chinese.