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followers: 19.0 following: 284.0 repos: 7.6K gists: 18.0

Name: Chang-Ho Hwang

Type: User

Company: CMI-TECH

Bio: Iris Recognition Application Engineer

Twitter: hKmT1cWPvVHwTYw

Location: seoul

Chang-Ho Hwang's Projects

006796_image_process_viewer

Visual C++ Image Processing Programming 예제 소스

0xdarkvortex-malwaredevelopment

This repo will contain code snippets for blogs: Malware on Steroids written by me at https://scriptdotsh.com/index.php/category/malware-development/

0xdarkvortex-reverse-engineering

This repo contains all the code that will be referred at https://scriptdotsh.com by Paranoid Ninja

1c_libreoffice_sample

Пример использования API LibreOffice из внешней компоненты 1C (Linux)

二自由度云台实现人脸追踪。首先是使用一款名字叫做IP摄像头的APP 采集手机摄像头的图像，在手机上建立一个视频流服务器。在局域网下，PC通过IP还有端口号获取图像。使用OpenCV的人脸检测的API获取人脸在画面中的位置，根据人脸位置距离画面中心的x轴与y轴的偏移量(offset) ，通过P比例控制(PID控制中最简单的一种)控制二自由度云台上臂与下臂的旋转角度，将角度信息通过串口通信UART发送给ESP32单片机(不限于ESP32，STM32,Arduino都可以)解析执行对应的操作，从而使得人脸尽可能处在画面的正中间。

2016_super_resolution

ICCV2015 Image Super-Resolution Using Deep Convolutional Networks

2022-06-05-malware-av-evasion-7

Malware AV evasion via disable Windows Defender (Registry). C++

2d-and-3d-face-alignment

This repository implements a demo of the networks described in "How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)" paper.

3000fps-mtcnn

face detect and align

3d-face-landmark-in-unitycg-hlsl

3D face landmark detection using MediaPipe's Facemesh and Iris tracking models

3d-face-mesh

tensorflow mediapipe ar webapp

3d-face-reconstruction

3D reconstruction of detected face

3d-game

Experimental 3D-Game using three.js

3d-game-master

Master server using Socket.io

3d-machine-learning

A resource repository for 3D machine learning

3d-mapping-using-a-uav-an-imu-and-a-2d-lidar

This code was made as part of a REU at Auburn University. The goal of the project was to make 3D maps using a 2D LiDAR, IMU, and UAV. For this project, we ended up using a RPLIDAR A1, a 3DR IRIS (which uses a Pixhawk flight controller), and a Raspberry Pi 3B. Our method of mapping was to mount the LiDAR on its side and then have the UAV yaw 360 degrees so it gave a near-complete sphere of view of the surroundings.