基于YOLOv5的卫星图像目标检测demo | A demo for satellite imagery object detection based on YOLOv5

This page is for the SlimYOLOv3: Narrower, Faster and Better for UAV Real-Time Applications

工业控制上位机通用框架 —— 实现用户注册、登录以及登录后跳转至主页面的Winform应用程序Demo。使用C#开发，采用三层架构(UI、BLL、DAL、Model)搭建，其中UI层即解决方案中名为UserLoginFramework的项目，同时UserLoginFramework也是该解决方案的启动项目；所有的界面项都放在UserLoginFramework下的UIForms文件夹内了。下…

WPF工业控制项目

项目是关于c#基本知识学习的练习

C#版 网易云音乐 API（翻译自Node.js项目Binaryify/NeteaseCloudMusicApi）

C#并发流程控制框架、运动控制框架，适用于工业自动化运动控制、机器视觉流程开发。

C#: EPSON Robot Remote TCP/IP Control,Motion Control(GoogolTech/LeadShine),Advantech(PCI1752/PCI1754),Keyence Laser,RS232C,RS485,TCP/IP Server/Client(Sync/Async),OPC Client/Server,CAN, EtherCAT,XML…

实习期间开发的一体式照相检验机项目源码，使用c#开发，包括PLC通讯、光源控制、使用工业相机采图、多线程处理图像等

Unofficial PyTorch Code for “MBLLEN: Low-light Image/Video Enhancement Using CNNs”, BMVC 2018.

Code for “MBLLEN: Low-light Image/Video Enhancement Using CNNs”, BMVC 2018.

Image Dehaze, Pytorch, An All-in-One Network for Dehazing, AOD-Net

A Pytorch implementation for DehazeNet in paper 'DehazeNet: An End-to-End System for Single Image Haze Removal'

Gated Fusion Network for Single Image Dehazing

This is Tensorflow implementation of Single Image Dehazing via Multi-Scale Convolutional Neural Networks https://sites.google.com/site/renwenqi888/research/dehazing/mscnndehazing

An Pytorch implementent of CVPR2009 "single image dehazing using dark channel prior." Support Batch Level Operation.

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

这是一个YoloV5-pytorch的源码，可以用于训练自己的模型。

后台开发相关知识

C++ Linux WebServer服务器

🔥 Linux下C++轻量级WebServer服务器

this is the official code for the paper "Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement"

AI for GNU Image Manipulation Program

A reimplement of Kindling the Darkness (KinD)

Kindling the Darkness: a Practical Low-light Image Enhancer

Python implementation of two low-light image enhancement techniques via illumination map estimation

A Python implementation for the following papers: Dual Illumination Estimation for Robust Exposure Correction and LIME: Low-light Image Enhancement via Illumination Map Estimation

PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)