登录
首页 » matlab » toolbox-master

toolbox-master

于 2018-05-25 发布
0 141
下载积分: 1 下载次数: 3

代码说明:

说明:  该节主要介绍下matlab下的光流法以及一个研究物体检测方面的一个较好的工具箱 :Piotr’s Computer Vision Matlab Toolbox .将这两个工具箱及其里面所有文件的路径都添加到matlab路径中去,这样的话基本上是可以用了。 Piotr’s 的工具箱里面的函数很多,也涉及到了很多方面,更主要的是关于目标检测方面的。(This section mainly introduces the optical flow under Matlab and a better toolkit for researching object detection: Piotr 's Computer Vision Matlab Toolbox. Add the two toolkits and all the files in the path to the MATLAB path, which is basically useful. There are many functions in the toolbox of Piotr 's, and there are many aspects involved)

文件列表:

toolbox-master, 0 , 2018-04-03
toolbox-master\.gitignore, 79 , 2018-04-03
toolbox-master\README.md, 50 , 2018-04-03
toolbox-master\channels, 0 , 2018-04-03
toolbox-master\channels\Contents.m, 1918 , 2018-04-03
toolbox-master\channels\chnsCompute.m, 9239 , 2018-04-03
toolbox-master\channels\chnsPyramid.m, 10523 , 2018-04-03
toolbox-master\channels\chnsScaling.m, 5019 , 2018-04-03
toolbox-master\channels\convBox.m, 3067 , 2018-04-03
toolbox-master\channels\convMax.m, 2318 , 2018-04-03
toolbox-master\channels\convTri.m, 4403 , 2018-04-03
toolbox-master\channels\fhog.m, 2966 , 2018-04-03
toolbox-master\channels\gradient2.m, 1213 , 2018-04-03
toolbox-master\channels\gradientHist.m, 3427 , 2018-04-03
toolbox-master\channels\gradientMag.m, 2340 , 2018-04-03
toolbox-master\channels\hog.m, 3460 , 2018-04-03
toolbox-master\channels\hogDraw.m, 1257 , 2018-04-03
toolbox-master\channels\imPad.m, 2228 , 2018-04-03
toolbox-master\channels\imResample.m, 2324 , 2018-04-03
toolbox-master\channels\private, 0 , 2018-04-03
toolbox-master\channels\private\chnsTestCpp.cpp, 2535 , 2018-04-03
toolbox-master\channels\private\convConst.cpp, 10301 , 2018-04-03
toolbox-master\channels\private\convConst.mexa64, 18665 , 2018-04-03
toolbox-master\channels\private\convConst.mexmaci64, 22124 , 2018-04-03
toolbox-master\channels\private\convConst.mexw64, 29184 , 2018-04-03
toolbox-master\channels\private\gradientMex.cpp, 18892 , 2018-04-03
toolbox-master\channels\private\gradientMex.mexa64, 23054 , 2018-04-03
toolbox-master\channels\private\gradientMex.mexmaci64, 26988 , 2018-04-03
toolbox-master\channels\private\gradientMex.mexw64, 38912 , 2018-04-03
toolbox-master\channels\private\gradientMexNew.mexmaci64, 26988 , 2018-04-03
toolbox-master\channels\private\imPadMex.cpp, 5424 , 2018-04-03
toolbox-master\channels\private\imPadMex.mexa64, 28577 , 2018-04-03
toolbox-master\channels\private\imPadMex.mexmaci64, 34220 , 2018-04-03
toolbox-master\channels\private\imPadMex.mexw64, 40960 , 2018-04-03
toolbox-master\channels\private\imResampleMex.cpp, 7810 , 2018-04-03
toolbox-master\channels\private\imResampleMex.mexa64, 21350 , 2018-04-03
toolbox-master\channels\private\imResampleMex.mexmaci64, 30252 , 2018-04-03
toolbox-master\channels\private\imResampleMex.mexw64, 34304 , 2018-04-03
toolbox-master\channels\private\rgbConvertMex.cpp, 8670 , 2018-04-03
toolbox-master\channels\private\rgbConvertMex.mexa64, 28926 , 2018-04-03
toolbox-master\channels\private\rgbConvertMex.mexmaci64, 47648 , 2018-04-03
toolbox-master\channels\private\rgbConvertMex.mexw64, 44544 , 2018-04-03
toolbox-master\channels\private\sse.hpp, 3125 , 2018-04-03
toolbox-master\channels\private\wrappers.hpp, 1573 , 2018-04-03
toolbox-master\channels\rgbConvert.m, 3630 , 2018-04-03
toolbox-master\classify, 0 , 2018-04-03
toolbox-master\classify\Contents.m, 2387 , 2018-04-03
toolbox-master\classify\adaBoostApply.m, 1230 , 2018-04-03
toolbox-master\classify\adaBoostTrain.m, 5096 , 2018-04-03
toolbox-master\classify\binaryTreeApply.m, 1111 , 2018-04-03
toolbox-master\classify\binaryTreeTrain.m, 5784 , 2018-04-03
toolbox-master\classify\confMatrix.m, 2166 , 2018-04-03
toolbox-master\classify\confMatrixShow.m, 1988 , 2018-04-03
toolbox-master\classify\demoCluster.m, 1522 , 2018-04-03
toolbox-master\classify\demoGenData.m, 3120 , 2018-04-03
toolbox-master\classify\distMatrixShow.m, 2204 , 2018-04-03
toolbox-master\classify\fernsClfApply.m, 936 , 2018-04-03
toolbox-master\classify\fernsClfTrain.m, 3277 , 2018-04-03
toolbox-master\classify\fernsInds.m, 985 , 2018-04-03
toolbox-master\classify\fernsRegApply.m, 1014 , 2018-04-03
toolbox-master\classify\fernsRegTrain.m, 5914 , 2018-04-03
toolbox-master\classify\forestApply.m, 1558 , 2018-04-03
toolbox-master\classify\forestTrain.m, 6138 , 2018-04-03
toolbox-master\classify\kmeans2.m, 5251 , 2018-04-03
toolbox-master\classify\meanShift.m, 3212 , 2018-04-03
toolbox-master\classify\meanShiftIm.m, 4812 , 2018-04-03
toolbox-master\classify\meanShiftImExplore.m, 2409 , 2018-04-03
toolbox-master\classify\pca.m, 3244 , 2018-04-03
toolbox-master\classify\pcaApply.m, 3320 , 2018-04-03
toolbox-master\classify\pcaData.mat, 165368 , 2018-04-03
toolbox-master\classify\pcaRandVec.m, 3140 , 2018-04-03
toolbox-master\classify\pcaVisualize.m, 4096 , 2018-04-03
toolbox-master\classify\pdist2.m, 5162 , 2018-04-03
toolbox-master\classify\private, 0 , 2018-04-03
toolbox-master\classify\private\IDX2order.m, 1038 , 2018-04-03
toolbox-master\classify\private\binaryTreeTrain1.cpp, 2744 , 2018-04-03
toolbox-master\classify\private\binaryTreeTrain1.mexa64, 9606 , 2018-04-03
toolbox-master\classify\private\binaryTreeTrain1.mexmaci64, 13020 , 2018-04-03
toolbox-master\classify\private\binaryTreeTrain1.mexw64, 10752 , 2018-04-03
toolbox-master\classify\private\fernsInds1.c, 1493 , 2018-04-03
toolbox-master\classify\private\fernsInds1.mexa64, 7187 , 2018-04-03
toolbox-master\classify\private\fernsInds1.mexmaci64, 8728 , 2018-04-03
toolbox-master\classify\private\fernsInds1.mexw64, 8192 , 2018-04-03
toolbox-master\classify\private\forestFindThr.cpp, 3717 , 2018-04-03
toolbox-master\classify\private\forestFindThr.mexa64, 10332 , 2018-04-03
toolbox-master\classify\private\forestFindThr.mexmaci64, 13040 , 2018-04-03
toolbox-master\classify\private\forestFindThr.mexw64, 11264 , 2018-04-03
toolbox-master\classify\private\forestInds.cpp, 1986 , 2018-04-03
toolbox-master\classify\private\forestInds.mexa64, 10221 , 2018-04-03
toolbox-master\classify\private\forestInds.mexmaci64, 8800 , 2018-04-03
toolbox-master\classify\private\forestInds.mexw64, 9216 , 2018-04-03
toolbox-master\classify\private\meanShift1.c, 5496 , 2018-04-03
toolbox-master\classify\private\meanShift1.mexa64, 9556 , 2018-04-03
toolbox-master\classify\private\meanShift1.mexmaci64, 13288 , 2018-04-03
toolbox-master\classify\private\meanShift1.mexw64, 10752 , 2018-04-03
toolbox-master\classify\private\meanShiftPost.m, 1374 , 2018-04-03
toolbox-master\classify\rbfComputeBasis.m, 5177 , 2018-04-03
toolbox-master\classify\rbfComputeFtrs.m, 1130 , 2018-04-03
toolbox-master\classify\rbfDemo.m, 2929 , 2018-04-03
toolbox-master\classify\softMin.m, 2317 , 2018-04-03

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论


0 个回复

  • 划痕canny
    可以用于图像的canny滤波处理,直接输入图像,可以保存下来处理后的canny图像(It can be used for canny filtering of images, directly inputting images, and preserving processed canny images.)
    2019-05-21 17:17:57下载
    积分:1
  • demo3
    说明:  基于高斯金字塔建模技术,使用高斯金字塔背景建模法完成的目标检测与跟踪,代码调试既可以使用!(Based on gaussian pyramid modeling technology, using gaussian pyramid background modeling method to complete the target detection and tracking, code debugging can be used!)
    2019-11-13 10:49:00下载
    积分:1
  • chapter11
    精通MATLAB数字图像处理与识别 chapter11 代码(Proficient in MATLAB digital image processing and recognition chapter11 code)
    2013-12-05 20:50:09下载
    积分:1
  • entropy_correlation
    说明:  用于计算图像的信息熵和相关性系数,在信息隐藏的图像算法评价中有很好的应用。(It is used to calculate the information entropy and correlation coefficient of image, and has a good application in the evaluation of image algorithm of information hiding.)
    2019-03-03 17:12:10下载
    积分:1
  • ShearLab3Dv11
    多尺度多方向性的剪切波Shearlet变换优于小波变换,里面包含很多例子,可以直接运行,可以用于图像去噪,分割,增强等,是一个优于小波的图像稀疏表示工具(Shearlet transform of multi-scale and multi-directional shear wave is better than wavelet transform. It contains many examples and can run directly. It can be used for image denoising, segmentation and enhancement. It is an image sparse representation tool better than wavelet transform.)
    2021-01-18 16:38:43下载
    积分:1
  • VMD_2D
    变分模态分解,VMD二维算法及测试示例,用来分解二维图像数据(Decomposition of two-dimensional image data)
    2021-03-08 16:49:28下载
    积分:1
  • AADEMO字平滑delphi
    delphi开发的显示字体平滑程序(display font smoothing procedures)
    2004-11-17 00:16:48下载
    积分:1
  • Saliency_Detection
    说明:  简单可用的显著性检测程序,用matlab'语言实现,经调试可用。(A matlab code for Saliency Detection)
    2017-07-30 17:36:58下载
    积分:1
  • ImageSimilarity
    计算img文件夹内所有图像之间的相似度,并根据相似度排序,呈现每个图片的最相似图片结果(calculate the image similarity of each pic in img filedir)
    2018-05-20 00:07:26下载
    积分:1
  • watershed_example
    说明:  分水岭算法是一种图像区域分割法,在分割的过程中,它会把跟临近像素间的相似性作为重要的参考依据,从而将在空间位置上相近并且灰度值相近的像素点互相连接起来构成一个封闭的轮廓,封闭性是分水岭算法的一个重要特征。本示例适用于二维和三维图像,计算分水岭变换并将结果标签矩阵显示为RGB图像。 分水岭算法是一种图像区域分割法,在分割的过程中,它会把跟临近像素间的相似性作为重要的参考依据,从而将在空间位置上相近并且灰度值相近的像素点互相连接起来构成一个封闭的轮廓,封闭性是分水岭算法的一个重要特征。本示例适用于二维和三维图像,计算分水岭变换并将结果标签矩阵显示为RGB图像。(The watershed algorithm is an image region segmentation method. In the segmentation process, it will use the similarity with neighboring pixels as an important reference basis, so as to connect pixels that are close in space and have similar gray values to each other. Forming a closed contour, closedness is an important feature of the watershed algorithm. This example applies to 2D and 3D images, calculates the watershed transformation and displays the resulting label matrix as an RGB image.)
    2020-04-08 21:45:20下载
    积分:1
  • 696518资源总数
  • 104603会员总数
  • 38今日下载