souwang324's repositories
2048_Game
Program for the 2048 game using OpenCV
caedemo
演示使用VTK Paraview VR AR等技术实现CAE的过程
Clustering-Algorithms
基于Python实现了K-Means、GMM、DBSCAN、AGNES等四种常见的聚类算法
Contour-and-Centroid
这个demo可以处理语义分割之后的图像，提取图像的各个区域和质心的坐标，这样就可以有针对性地计算这些质心的深度值，从而实现简单的避障。
CPP-Fluid-Particles
my own implementation of the WCSPH, DFSPH and PBD fluid solvers using CUDA and C++
Defect-Detection-Classifier
Visual Defect Detection on Boiler Water Wall Tube Using Small Dataset
Fourier-Descriptors
OpenCV project for my image processing course, horribly bad work.
gray-code-structured-light
Reconstructs a 3D scene with the use of a projector and a camera
HaraliCU
Haralick feature extraction on medical images exploiting the full dynamics of gray-scale levels
HDR-US
High Dynamic Range Ultrasound Imaging
HDR_ImageAndVideo
For VR Final Project
Kernighan-Lin
Implementation of Kernighan-Lin graph partitioning algorithm in Python
NCC
Stereo Matching -- Normalized Cross Correlation by python
opencv-haralickfeatures
Implementation of GLCM Haralick Features in openCV
OpenCVision
implementations of opencv
photometric-stereo-1
A MATLAB Implementation of the Basic Photometric Stereo Algorithm
PhotometricStereo
Photometric Stereo Recovery of Shape & Relative Distances
PoissonImageEditing
An image fusion techniques presented in “Poisson image editing", P. Pérez, M. Gangnet, and A. Blake, SIGGRAPH 2003.
python.dojang
파이썬 코딩 도장
stereo-matching-using-minimum-spanning-tree
Implement Stereo Matching Algorithm by Minimum Spanning Tree (MST)
StereoCorrespondence_GraphCuts
An implemenetation of Kolmogorov and Zabih’s Graph Cuts Stereo Matching Algorithm
Structured-Light-Scanner
A low-cost 3D light scanner based on the Coded Structured Light and Close-range Photogrammetry principles
structured_light_reconstructe
结构光三维重建算法
TF-ESPCN
Tensorflow implementation of ESPCN
Tiled-Naive-2D-Convolution-1-D-Histogram-CUDA-OpenCL
2D convolution and 1D histogram calculation was performed in both CUDA and OpenCL. 2D convolution was implemented, taking advantage of both shared memory/tiles and global memory (naive methods). Tiled 2D convolution was performed in CUDA only. For naive 2D convolution, the input to the algorithm is an [M X N] matrix and a [K X K] kernel of odd dime
Traffic-Sign-Recognition-with-Machine-LearningAndOpenCV
OpenCV & 기계 학습기반 고속 표지판 인식 (Using KNN, SVM)