plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | ghazi94/IRIS-Segmentation-master | partiald.m | .m | IRIS-Segmentation-master/Equivalent_MATLAB_Code/partiald.m | 1,971 | utf_8 | 68639e9f7dd6fcde5787cd8ba32593c5 | %function to find the partial derivative
%calculates the partial derivative of the normailzed line integral
%holding the centre coordinates constant
%and then smooths it by a gaussian of appropriate sigma
%%rmin and rmax are the minimum and maximum values of radii expected
%function also returns the maximum value... |
github | ghazi94/IRIS-Segmentation-master | lineint.m | .m | IRIS-Segmentation-master/Equivalent_MATLAB_Code/lineint.m | 2,250 | utf_8 | 0c44ce59f8fff0711233868ae7dafc67 | %function to calculate the normalised line integral around a circular contour
%A polygon of large number of sides approximates a circle and hence is used
%here to calculate the line integral by summation
%INPUTS:
%1.I:Image to be processed
%2.C(x,y):Centre coordinates of the circumcircle
%Coordinate system :
%or... |
github | xyza11808/imaging-data-processing-master | dftregistration.m | .m | imaging-data-processing-master/dftregistration.m | 8,234 | utf_8 | 7dc727aebf333c1a5cef2b2821265218 |
function [output Greg] = dftregistration(buf1ft,buf2ft,usfac)
% function [output Greg] = dftregistration(buf1ft,buf2ft,usfac);
% Efficient subpixel image registration by crosscorrelation. This code
% gives the same precision as the FFT upsampled cross correlation in a
% small fraction of the computation time an... |
github | xyza11808/imaging-data-processing-master | nx_imAnalysisGUI2013.m | .m | imaging-data-processing-master/nx_imAnalysisGUI2013.m | 91,522 | utf_8 | 9e7350870b11d6abb0897c295cb06682 | function varargout = nx_imAnalysisGUI2013(varargin)
% NX_IMANALYSISGUI2013 M-file for nx_imAnalysisGUI2013.fig
% NX_IMANALYSISGUI2013, by itself, creates a new NX_IMANALYSISGUI2013 or raises the existing
% singleton*.
%
% H = NX_IMANALYSISGUI2013 returns the handle to a new NX_IMANALYSISGUI2013 or the ha... |
github | xyza11808/imaging-data-processing-master | CaSignal_ROI_GUI.m | .m | imaging-data-processing-master/CaSignal_ROI_GUI.m | 90,203 | utf_8 | f675c2eb22b09695a22211f32a4714bb |
function varargout = CaSignal_ROI_GUI(varargin)
% CaSignal_ROI_GUI M-file for CaSignal_ROI_GUI.fig
% CaSignal_ROI_GUI, by itself, creates a new CaSignal_ROI_GUI or raises the existing
% singleton*.
%
% H = CaSignal_ROI_GUI returns the handle to a new CaSignal_ROI_GUI or the handle to
% the existing... |
github | xyza11808/imaging-data-processing-master | load_scim_data.m | .m | imaging-data-processing-master/load_scim_data.m | 6,629 | utf_8 | 3671d6df36b097f106d449c17a167c30 | function [im, header] = load_scim_data(filename,varargin)
% function [im, header] = load_scim_data(filename,varargin)
% varargin{1}, frame_range, 1x2 array specifying start and end frame to
% load. If not specified, load all frames
%
% -NX 2013-5-30
%
% varargin{2}, offset_to_mode_flag. ScanImage4 data has negative va... |
github | xyza11808/imaging-data-processing-master | CaSignal_ROI_GUI_NP_extract.m | .m | imaging-data-processing-master/Imaging_data_processing_XIN/CaSignal_ROI_GUI_NP_extract.m | 110,563 | utf_8 | 41897af6023adb75cbdcb9581041344f | function varargout = CaSignal_ROI_GUI_NP_extract(varargin)
% CaSignal_ROI_GUI_NP_extract M-file for CaSignal_ROI_GUI_NP_extract.fig
% CaSignal_ROI_GUI_NP_extract, by itself, creates a new CaSignal_ROI_GUI_NP_extract or raises the existing
% singleton*.
%
% H = CaSignal_ROI_GUI_NP_extract returns the hand... |
github | xyza11808/imaging-data-processing-master | CaSignal_ROI_GUI_par.m | .m | imaging-data-processing-master/Imaging_data_processing_XIN/CaSignal_ROI_GUI_par.m | 96,268 | utf_8 | 2bb9df9e305f57aa7ec7d8e6cb716282 |
function varargout = CaSignal_ROI_GUI_par(varargin)
% CaSignal_ROI_GUI_par M-file for CaSignal_ROI_GUI_par.fig
% CaSignal_ROI_GUI_par, by itself, creates a new CaSignal_ROI_GUI_par or raises the existing
% singleton*.
%
% H = CaSignal_ROI_GUI_par returns the handle to a new CaSignal_ROI_GUI_par or the h... |
github | xyza11808/imaging-data-processing-master | Labeled_ROI_Selection.m | .m | imaging-data-processing-master/Imaging_data_processing_XIN/Labeled_ROI_Selection.m | 21,834 | utf_8 | d212f2149fc91d155d0dddac8a427c38 | function varargout = Labeled_ROI_Selection(varargin)
% LABELED_ROI_SELECTION MATLAB code for Labeled_ROI_Selection.fig
% LABELED_ROI_SELECTION, by itself, creates a new LABELED_ROI_SELECTION or raises the existing
% singleton*.
%
% H = LABELED_ROI_SELECTION returns the handle to a new LABELED_ROI_SELECTI... |
github | xyza11808/imaging-data-processing-master | dftregistration.m | .m | imaging-data-processing-master/Imaging_data_processing_XIN/dftregistration.m | 8,022 | utf_8 | 7c769c44dc6d69fb9e814689586f0424 |
function [output Greg] = dftregistration(buf1ft,buf2ft,usfac)
% function [output Greg] = dftregistration(buf1ft,buf2ft,usfac);
% Efficient subpixel image registration by crosscorrelation. This code
% gives the same precision as the FFT upsampled cross correlation in a
% small fraction of the computation time and with... |
github | xyza11808/imaging-data-processing-master | nx_imAnalysisGUI2013.m | .m | imaging-data-processing-master/Imaging_data_processing_XIN/nx_imAnalysisGUI2013.m | 91,474 | utf_8 | d338f9abfebe98fae59bb569f43a9443 | function varargout = nx_imAnalysisGUI2013(varargin)
% NX_IMANALYSISGUI2013 M-file for nx_imAnalysisGUI2013.fig
% NX_IMANALYSISGUI2013, by itself, creates a new NX_IMANALYSISGUI2013 or raises the existing
% singleton*.
%
% H = NX_IMANALYSISGUI2013 returns the handle to a new NX_IMANALYSISGUI2013 or the ha... |
github | xyza11808/imaging-data-processing-master | CaSignal_ROI_GUI.m | .m | imaging-data-processing-master/Imaging_data_processing_XIN/CaSignal_ROI_GUI.m | 94,930 | utf_8 | 45fc95f9aef68a8ddf438d66bdebb764 |
function varargout = CaSignal_ROI_GUI(varargin)
% CaSignal_ROI_GUI M-file for CaSignal_ROI_GUI.fig
% CaSignal_ROI_GUI, by itself, creates a new CaSignal_ROI_GUI or raises the existing
% singleton*.
%
% H = CaSignal_ROI_GUI returns the handle to a new CaSignal_ROI_GUI or the handle to
% the existing... |
github | xyza11808/imaging-data-processing-master | load_scim_data.m | .m | imaging-data-processing-master/Imaging_data_processing_XIN/load_scim_data.m | 6,629 | utf_8 | 3671d6df36b097f106d449c17a167c30 | function [im, header] = load_scim_data(filename,varargin)
% function [im, header] = load_scim_data(filename,varargin)
% varargin{1}, frame_range, 1x2 array specifying start and end frame to
% load. If not specified, load all frames
%
% -NX 2013-5-30
%
% varargin{2}, offset_to_mode_flag. ScanImage4 data has negative va... |
github | ZHANGXinxinPKU/defocus-deblurring-master | BM3DDEB.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/BM3D/BM3DDEB.m | 17,198 | utf_8 | 1338daac736306d7c65f8f7d24cbedeb | function [ y_hat_RWI] = BM3DDEB(z,v,sigma)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Copyright (c) 2008-2014 Tampere University of Technology. All rights reserved.
% This work should only be used for nonprofit purposes.
%
% AUTHORS:
% Kostadin Dabov
% Alessandro Foi ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | CBM3D.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/BM3D/CBM3D.m | 28,530 | utf_8 | 9a3e40b8b0f177169d223c8676892b13 | function [PSNR, yRGB_est] = CBM3D(yRGB, zRGB, sigma, profile, print_to_screen, colorspace)
%
% CBM3D is algorithm for attenuation of additive white Gaussian noise from
% color RGB images. This algorithm reproduces the results from the article:
%
% [1] K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, "Color image
... |
github | ZHANGXinxinPKU/defocus-deblurring-master | BM3D.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/BM3D/BM3D.m | 22,746 | utf_8 | 1db07f61b119fa6ab501801453c24330 | function [PSNR, y_est] = BM3D(y, z, sigma, profile, print_to_screen)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% BM3D is an algorithm for attenuation of additive white Gaussian noise from
% grayscale images. This algorithm reproduces the results from the article:
%
% [1] K. Dab... |
github | ZHANGXinxinPKU/defocus-deblurring-master | function_CreateLPAKernels.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/BM3D/BM3D-SAPCA/function_CreateLPAKernels.m | 5,075 | utf_8 | 5036e27fea466f53341e109a39c29786 | % Creates LPA kernels cell array (function_CreateLPAKernels)
%
% Alessandro Foi - Tampere University of Technology - 2003-2005
% ---------------------------------------------------------------
%
% Builds kernels cell arrays kernels{direction,size}
% and kernels_higher_order{direction,size,1:... |
github | ZHANGXinxinPKU/defocus-deblurring-master | function_Window2D.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/BM3D/BM3D-SAPCA/function_Window2D.m | 2,242 | utf_8 | 514b002214f1f4efa8ff48a3997efcfd | % Returns a scalar/matrix weights (window function) for the LPA estimates
% function w=function_Window2D(X,Y,window,sig_wind, beta);
% X,Y scalar/matrix variables
% window - type of the window weight
% sig_wind - std scaling for the Gaussian ro-weight
% beta -parameter of the degree in the weights
%--------------------... |
github | ZHANGXinxinPKU/defocus-deblurring-master | function_LPAKernelMatrixTheta.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/BM3D/BM3D-SAPCA/function_LPAKernelMatrixTheta.m | 6,268 | utf_8 | 3f5b0af0d5c8ac49f518f547b0de78da | % Return the discrete kernels for LPA estimation and their degrees matrix
%
% function [G, G1, index_polynomials]=function_LPAKernelMatrixTheta(h2,h1,window_type,sig_wind,TYPE,theta, m)
%
%
% Outputs:
%
% G kernel for function estimation
% G1 kernels for function and derivative estimation
% G1(:,:,j), j=1 for fu... |
github | ZHANGXinxinPKU/defocus-deblurring-master | clusterLocations.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/clusterLocations.m | 906 | utf_8 | b8edf17a93d81f6dcf7f11becd55390f | % M is a segmentation mask, entries in {1,2,...,K}.
% C is a segmentation mask, entries in {1,2,...,L}.
%
% Compute a segmentation respecting the boundaries in M, clustering points until there
% are no more than p_max pixels in a cluster.
% k-means clustering on (x,y) position is run on each cluster from M.
function C ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | imncut_sp.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/imncut_sp.m | 4,934 | utf_8 | 61fe98ac6c5377d492dc487537a64b4e | % function par = imncut_sp; or
% [Sp,Seg,V,S,W] = imncut_sp(I,par)
%
% Compute "superpixels."
% An intial segmentation into K1=par.nv segments is performed using cncut.
% These initial segments are then subdivided into K2=par.sp "superpixels"
% by running kmeans on the cncut eigenvector coordinates, followed ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | pbThicken.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/pbThicken.m | 234 | utf_8 | 56e89d5786e0f329d462261d6c9fba24 | % T = pbThicken(P)
%
% Thicken P by taking max in 3x3 window
function T = pbThicken(P)
[MM,NN] = size(P);
B = im2col(P,[3 3],'sliding');
B = max(B,[],1);
T_c = reshape(B,[MM-3+1 NN-3+1]);
T = zeros(size(P));
T(2:end-1,2:end-1) = T_c; |
github | ZHANGXinxinPKU/defocus-deblurring-master | pbWrapper.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/pbWrapper.m | 1,397 | utf_8 | 6f16686d034158c6c50a402163201efc | % [max_pb,phase] = pbWrapper(I)
% [max_pb,phase] = pbWrapper(I,pb_timing)
%
% Wrap Martin-Fowlkes pb code to do phase calcuations as well.
function [max_pb,phase] = pbWrapper(I,varargin)
if nargin >=2
pb_timing = varargin{1};
else
pb_timing=0;
end
if ~exist('pbCGTG')
addpath('/cs/fac1/mori/linux/src/segbench/lib... |
github | ZHANGXinxinPKU/defocus-deblurring-master | getbinsol.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/yu_imncut/getbinsol.m | 1,454 | utf_8 | f3c214689db1b58f5e092a6ee18f2c5e | % function [X,R,Z,iter] = getbinsol(V,n_iter,X0)
% iteratively solving X = \tV R, R R' = I
% Input:
% V = N x K (#nodes x #segments), eigensolutions from cncut.m
% n_iter = # iterations for refinement. default = 50;
% n_iter = 0, no refinement
% X0 = initial estimation of a partitioning
% Output:
% X = ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | computeW.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/yu_imncut/computeW.m | 2,194 | utf_8 | c3bc1a79dace0b994ba5fc178e708b0e | % [W,samp] = computeW(I,par)
% [W,samp] = computeW(I,par,I_mask)
%
% Same style as imncut.
% Uses intervening contour and/or intensity
% if I_mask is set, compute sparse W connection matrix from points in Mask region to points outside Mask region
function [W,samp] = computeW(I,par,varargin)
nb_r = par.nb_r;
sample_rate... |
github | ZHANGXinxinPKU/defocus-deblurring-master | cncut.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/yu_imncut/cncut.m | 1,538 | utf_8 | 2a594272cc36d60a80f4c72213801a22 | % function [V,S] = cncut(W,U,nv,reg)
% Input:
% W = N x N affinity matrix, negative entries treated as repulsion
% U = N x C constraint matrix, default = []
% nv = number of eigenvectors, default = 6
% reg = regularization factor, default = 0
% Output:
% V = N x nv, eigenvectors
% S = nv x 1, eigenvalue of ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | boundaryBenchGraphs.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Benchmark/boundaryBenchGraphs.m | 2,149 | utf_8 | 5d36c953bdb6419ab347d32a33237106 | function boundaryBenchGraphs(pbDir)
% function boundaryBenchGraphs(pbDir)
%
% Create graphs, after boundaryBench(pbDir) has been run.
%
% See also boundaryBench.
%
% David Martin <dmartin@eecs.berkeley.edu>
% May 2003
fname = fullfile(pbDir,'scores.txt');
scores = dlmread(fname); % iid,thresh,r,p,f
fname = fullfile(pb... |
github | ZHANGXinxinPKU/defocus-deblurring-master | boundaryBench.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Benchmark/boundaryBench.m | 3,527 | utf_8 | 72c57116e042a9982380b57fb6535200 | function boundaryBench(pbDir,pres,nthresh,fast)
% function boundaryBench(pbDir,pres,nthresh,fast)
%
% Run the boundary detector benchmark on the Pb files found in
% pbDir for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
if nargin<3, nthresh=30; end
if ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | boundaryBenchGraphsMulti.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Benchmark/boundaryBenchGraphsMulti.m | 3,290 | utf_8 | 329d8ab5d50641ff5c45b80ea534c65b | function boundaryBenchGraphsMulti(baseDir)
% function boundaryBenchGraphsMulti(baseDir)
%
% See also boundaryBenchGraphs.
%
% David Martin <dmartin@eecs.berkeley.edu>
% July 2003
presentations = {'gray','color'};
presNames = {'Grayscale','Color'};
iidsTest = imgList('test');
% Infer list of algorithms from directorie... |
github | ZHANGXinxinPKU/defocus-deblurring-master | boundaryBenchGraphsHuman.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Benchmark/boundaryBenchGraphsHuman.m | 2,305 | utf_8 | 22ab87b11ee29175d476f559f66be48d | function boundaryBenchGraphsHuman(pbDir)
% function boundaryBenchGraphsHuman(pbDir)
%
% Create graphs, after boundaryBenchHuman has been run.
%
% See also boundaryBenchHuman.
%
% David Martin <dmartin@eecs.berkeley.edu>
% July 2003
iids = imgList('test');
n = numel(iids);
% read in all the data
fwrite(2,'Reading data... |
github | ZHANGXinxinPKU/defocus-deblurring-master | boundaryBenchHuman.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Benchmark/boundaryBenchHuman.m | 2,560 | utf_8 | dbf3eae48252f53e5d2042206192db85 | function boundaryBenchHuman(pbRoot,pres)
% function boundaryBenchHuman(pbRoot,pres)
%
% Compute the human precision/recall data for the BSDS test images.
%
% See also imgList, bsdsRoot.
%
% David Martin <dmartin@eecs.berkeley.edu>
% March 2003
iids = imgList('test');
cR_total = 0;
sR_total = 0;
cP_total = 0;
sP_total... |
github | ZHANGXinxinPKU/defocus-deblurring-master | plotem.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/plotem.m | 2,925 | utf_8 | f4a8f0ca366638ae79dde05510959f65 |
function plotem()
figure(1); clf; hold on;
pr = load('pb/bgtg_0.01_0.02_64/pr.txt');
plot(pr(:,2),pr(:,3),'co-');
pr = load('pb/bgtg/pr.txt');
plot(pr(:,2),pr(:,3),'bx-');
pr = load('pb/cgtg/pr.txt');
plot(pr(:,2),pr(:,3),'rx-');
prplot('');
legend('bgtg zone=2','bgtg zone=10','cgtg');
return
figure(1); clf; hold on... |
github | ZHANGXinxinPKU/defocus-deblurring-master | trainCG.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/trainCG.m | 529 | utf_8 | f26b31c142e8ebbcf87c8620eeb67dd3 | function trainCG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('bet... |
github | ZHANGXinxinPKU/defocus-deblurring-master | trainTG.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/trainTG.m | 463 | utf_8 | ddb30948004726a57eecc581e6ec7d77 | function trainTG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('bet... |
github | ZHANGXinxinPKU/defocus-deblurring-master | trainCGTG.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/trainCGTG.m | 618 | utf_8 | 7f916f99fa0df2efaa8092302648814b | function trainCGTG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('b... |
github | ZHANGXinxinPKU/defocus-deblurring-master | trainBGTG.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/trainBGTG.m | 504 | utf_8 | 20fd0459e57773aa11ff7eaa4e39cdcb | function trainBGTG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('b... |
github | ZHANGXinxinPKU/defocus-deblurring-master | tmp.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/tmp.m | 275 | utf_8 | 3af6b6692bbaa42694b868a8cb2e8897 |
function tmp()
iids = imgList('test');
ignore = mkdir('pb');
ignore = mkdir('pb/bgtg');
for iid = iids,
im = rgb2gray(imgRead(iid));
fprintf(2,'Computing Pb for image %d using BG/TG...\n',iid);
pb = pbBGTG(im);
imwrite(pb,sprintf('pb/bgtg/%d.bmp',iid),'bmp');
end
|
github | ZHANGXinxinPKU/defocus-deblurring-master | trainGM.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/trainGM.m | 1,201 | utf_8 | f1233bddee2a7579e85b87462f9f38c2 | function trainGM()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_1.mat' f y;
beta = logist2(y',f');
save 'beta_gm_1.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_2.mat' f y;
beta = logist2(y',f');
sav... |
github | ZHANGXinxinPKU/defocus-deblurring-master | trainGM2.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/trainGM2.m | 828 | utf_8 | 75c7bd3ab84c9640886bf0613776406b | function [beta,f,y] = trainGM2()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_1_2.mat' f y;
beta = logist2(y',f');
save 'beta_gm_1_2.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_gm_2_4.mat' f y;
beta =... |
github | ZHANGXinxinPKU/defocus-deblurring-master | train2MM.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/train2MM.m | 1,240 | utf_8 | af6b211e73cf494661ccb31e77a6d4d6 | function train2MM()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_1.mat' f y;
beta = logist2(y',f');
save 'beta_2mm_1.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_2.mat' f y;
beta = logist2(y',f');... |
github | ZHANGXinxinPKU/defocus-deblurring-master | trainBG.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/trainBG.m | 465 | utf_8 | 8a744b43d2e9e5ca3f48c186c9c413e8 | function trainBG(pres)
% get features and labels
[f,y] = sampleDetector(@detector,pres);
f=f'; y=y';
% normalize features to unit variance
fstd = std(f);
fstd = fstd + (fstd==0);
f = f ./ repmat(fstd,size(f,1),1);
% fit the model
fprintf(2,'Fitting model...\n');
beta = logist2(y,f);
% save the result
save(sprintf('bet... |
github | ZHANGXinxinPKU/defocus-deblurring-master | train2MM2.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Detectors/train2MM2.m | 682 | utf_8 | 95dd4f445a6a665a9100a8e3669fadcd | function [beta,f,y] = train2MM2()
[f,y] = sampleDetector(@detector1,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_1_2.mat' f y;
beta = logist2(y',f');
save 'beta_2mm_1_2.txt' beta -ascii;
[f,y] = sampleDetector(@detector2,1000000,8);
fprintf(2,'Fitting model...\n');
save 'samples_2mm_2_4.mat' f y;
be... |
github | ZHANGXinxinPKU/defocus-deblurring-master | kmeansML.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Util/kmeansML.m | 3,650 | utf_8 | 7a4a29d66a1f8aeb10ecf636dd483a3a | function [membership,means,rms] = kmeansML(k,data,varargin)
% [membership,means,rms] = kmeansML(k,data,...)
%
% Multi-level kmeans.
% Tries very hard to always return k clusters.
%
% INPUT
% k Number of clusters
% data dxn matrix of data points
% 'maxiter' Max number of iterations. [30]
% 'dtol' Min change in cen... |
github | ZHANGXinxinPKU/defocus-deblurring-master | cgmo.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Gradients/cgmo.m | 4,181 | utf_8 | 6c29fc1b4d710f1f7fa1e4448062c599 | function [cg,theta] = cgmo(im,radius,norient,varargin)
% function [cg] = cgmo(im,radius,norient,...)
%
% Compute the color gradient at a single scale and multiple
% orientations.
%
% INPUT
% im Grayscale or RGB image, values in [0,1].
% radius Radius of disc for cg.
% norient Number of orientations for cg.
% 'nbins'... |
github | ZHANGXinxinPKU/defocus-deblurring-master | cgso.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/superpixel/segbench/Gradients/cgso.m | 4,061 | utf_8 | b6247b3c62e7cdc72babce695b7096e3 | function [cg,theta] = cgso(im,radius,theta,varargin)
% function [cg] = cgso(im,radius,theta,...)
%
% Compute the color gradient at a single scale and multiple
% orientations.
%
% INPUT
% im Grayscale or RGB image, values in [0,1].
% radius Radius of disc for cg.
% theta Orientation orthogonal to cg.
% 'nbins' Numbe... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_compile.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/vl_compile.m | 5,060 | utf_8 | 978f5189bb9b2a16db3368891f79aaa6 | function vl_compile(compiler)
% VL_COMPILE Compile VLFeat MEX files
% VL_COMPILE() uses MEX() to compile VLFeat MEX files. This command
% works only under Windows and is used to re-build problematic
% binaries. The preferred method of compiling VLFeat on both UNIX
% and Windows is through the provided Makefile... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_noprefix.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/vl_noprefix.m | 1,875 | utf_8 | 97d8755f0ba139ac1304bc423d3d86d3 | function vl_noprefix
% VL_NOPREFIX Create a prefix-less version of VLFeat commands
% VL_NOPREFIX() creats prefix-less stubs for VLFeat functions
% (e.g. SIFT for VL_SIFT). This function is seldom used as the stubs
% are included in the VLFeat binary distribution anyways. Moreover,
% on UNIX platforms, the stub... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_pegasos.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/misc/vl_pegasos.m | 2,837 | utf_8 | d5e0915c439ece94eb5597a07090b67d | % VL_PEGASOS [deprecated]
% VL_PEGASOS is deprecated. Please use VL_SVMTRAIN() instead.
function [w b info] = vl_pegasos(X,Y,LAMBDA, varargin)
% Verbose not supported
if (sum(strcmpi('Verbose',varargin)))
varargin(find(strcmpi('Verbose',varargin),1))=[];
fprintf('Option VERBOSE is no longer supported.\n');
en... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_svmpegasos.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/misc/vl_svmpegasos.m | 1,178 | utf_8 | 009c2a2b87a375d529ed1a4dbe3af59f | % VL_SVMPEGASOS [deprecated]
% VL_SVMPEGASOS is deprecated. Please use VL_SVMTRAIN() instead.
function [w b info] = vl_svmpegasos(DATA,LAMBDA, varargin)
% Verbose not supported
if (sum(strcmpi('Verbose',varargin)))
varargin(find(strcmpi('Verbose',varargin),1))=[];
fprintf('Option VERBOSE is no longer suppor... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_override.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/misc/vl_override.m | 4,654 | utf_8 | e233d2ecaeb68f56034a976060c594c5 | function config = vl_override(config,update,varargin)
% VL_OVERRIDE Override structure subset
% CONFIG = VL_OVERRIDE(CONFIG, UPDATE) copies recursively the fileds
% of the structure UPDATE to the corresponding fields of the
% struture CONFIG.
%
% Usually CONFIG is interpreted as a list of paramters with their
... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_quickvis.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/quickshift/vl_quickvis.m | 3,696 | utf_8 | 27f199dad4c5b9c192a5dd3abc59f9da | function [Iedge dists map gaps] = vl_quickvis(I, ratio, kernelsize, maxdist, maxcuts)
% VL_QUICKVIS Create an edge image from a Quickshift segmentation.
% IEDGE = VL_QUICKVIS(I, RATIO, KERNELSIZE, MAXDIST, MAXCUTS) creates an edge
% stability image from a Quickshift segmentation. RATIO controls the tradeoff
% bet... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_demo_aib.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/demo/vl_demo_aib.m | 2,928 | utf_8 | 590c6db09451ea608d87bfd094662cac | function vl_demo_aib
% VL_DEMO_AIB Test Agglomerative Information Bottleneck (AIB)
D = 4 ;
K = 20 ;
randn('state',0) ;
rand('state',0) ;
X1 = randn(2,300) ; X1(1,:) = X1(1,:) + 2 ;
X2 = randn(2,300) ; X2(1,:) = X2(1,:) - 2 ;
X3 = randn(2,300) ; X3(2,:) = X3(2,:) + 2 ;
figure(1) ; clf ; hold on ;
vl_plotframe(X... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_demo_alldist.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/demo/vl_demo_alldist.m | 5,460 | utf_8 | 6d008a64d93445b9d7199b55d58db7eb | function vl_demo_alldist
%
numRepetitions = 3 ;
numDimensions = 1000 ;
numSamplesRange = [300] ;
settingsRange = {{'alldist2', 'double', 'l2', }, ...
{'alldist', 'double', 'l2', 'nosimd'}, ...
{'alldist', 'double', 'l2' }, ...
{'alldist2', 's... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_demo_ikmeans.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/demo/vl_demo_ikmeans.m | 774 | utf_8 | 17ff0bb7259d390fb4f91ea937ba7de0 | function vl_demo_ikmeans()
% VL_DEMO_IKMEANS
numData = 10000 ;
dimension = 2 ;
data = uint8(255*rand(dimension,numData)) ;
numClusters = 3^3 ;
[centers, assignments] = vl_ikmeans(data, numClusters);
figure(1) ; clf ; axis off ;
plotClusters(data, centers, assignments) ;
vl_demo_print('ikmeans_2d',0.6);
[tree, assig... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_demo_svm.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/demo/vl_demo_svm.m | 1,235 | utf_8 | 7cf6b3504e4fc2cbd10ff3fec6e331a7 | % VL_DEMO_SVM Demo: SVM: 2D linear learning
function vl_demo_svm
y=[];X=[];
% Load training data X and their labels y
load('vl_demo_svm_data.mat')
Xp = X(:,y==1);
Xn = X(:,y==-1);
figure
plot(Xn(1,:),Xn(2,:),'*r')
hold on
plot(Xp(1,:),Xp(2,:),'*b')
axis equal ;
vl_demo_print('svm_training') ;
% Parameters
lambda =... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_demo_kdtree_sift.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/demo/vl_demo_kdtree_sift.m | 6,832 | utf_8 | e676f80ac330a351f0110533c6ebba89 | function vl_demo_kdtree_sift
% VL_DEMO_KDTREE_SIFT
% Demonstrates the use of a kd-tree forest to match SIFT
% features. If FLANN is present, this function runs a comparison
% against it.
% AUTORIGHS
rand('state',0) ;
randn('state',0);
do_median = 0 ;
do_mean = 1 ;
% try to setup flann
if ~exist('flann_search'... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_impattern.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/imop/vl_impattern.m | 6,876 | utf_8 | 1716a4d107f0186be3d11c647bc628ce | function im = vl_impattern(varargin)
% VL_IMPATTERN Generate an image from a stock pattern
% IM=VLPATTERN(NAME) returns an instance of the specified
% pattern. These stock patterns are useful for testing algoirthms.
%
% All generated patterns are returned as an image of class
% DOUBLE. Both gray-scale and colou... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_tpsu.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/imop/vl_tpsu.m | 1,755 | utf_8 | 09f36e1a707c069b375eb2817d0e5f13 | function [U,dU,delta]=vl_tpsu(X,Y)
% VL_TPSU Compute the U matrix of a thin-plate spline transformation
% U=VL_TPSU(X,Y) returns the matrix
%
% [ U(|X(:,1) - Y(:,1)|) ... U(|X(:,1) - Y(:,N)|) ]
% [ ]
% [ U(|X(:,M) - Y(:,1)|) ... U(|X(:,M) - Y(:,N)|) ]
%
% where X... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_xyz2lab.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/imop/vl_xyz2lab.m | 1,570 | utf_8 | 09f95a6f9ae19c22486ec1157357f0e3 | function J=vl_xyz2lab(I,il)
% VL_XYZ2LAB Convert XYZ color space to LAB
% J = VL_XYZ2LAB(I) converts the image from XYZ format to LAB format.
%
% VL_XYZ2LAB(I,IL) uses one of the illuminants A, B, C, E, D50, D55,
% D65, D75, D93. The default illuminatn is E.
%
% See also: VL_XYZ2LUV(), VL_HELP().
% Copyright ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_gmm.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_gmm.m | 1,332 | utf_8 | 76782cae6c98781c6c38d4cbf5549d94 | function results = vl_test_gmm(varargin)
% VL_TEST_GMM
% Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
vl_test_init ;
end
function s = setup()
randn('st... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_twister.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_twister.m | 1,251 | utf_8 | 2bfb5a30cbd6df6ac80c66b73f8646da | function results = vl_test_twister(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_illegal_args()
vl_assert_exception(@() vl_twister(-1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister(1, -1), 'vl:invalidArgument') ;
vl_assert_exception(@() vl_twister([1, -1]), 'vl:invalidArgument') ;
function te... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_kdtree.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_kdtree.m | 2,449 | utf_8 | 9d7ad2b435a88c22084b38e5eb5f9eb9 | function results = vl_test_kdtree(varargin)
% VL_TEST_KDTREE
vl_test_init ;
function s = setup()
randn('state',0) ;
s.X = single(randn(10, 1000)) ;
s.Q = single(randn(10, 10)) ;
function test_nearest(s)
for tmethod = {'median', 'mean'}
for type = {@single, @double}
conv = type{1} ;
tmethod = char(tmethod) ;... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_imwbackward.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_imwbackward.m | 514 | utf_8 | 33baa0784c8f6f785a2951d7f1b49199 | function results = vl_test_imwbackward(varargin)
% VL_TEST_IMWBACKWARD
vl_test_init ;
function s = setup()
s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
function test_identity(s)
xr = 1:size(s.I,2) ;
yr = 1:size(s.I,1) ;
[x,y] = meshgrid(xr,yr) ;
vl_assert_almost_equal(s.I, vl_imwbackward(xr,yr,s.I,... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_alphanum.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_alphanum.m | 1,624 | utf_8 | 2da2b768c2d0f86d699b8f31614aa424 | function results = vl_test_alphanum(varargin)
% VL_TEST_ALPHANUM
vl_test_init ;
function s = setup()
s.strings = ...
{'1000X Radonius Maximus','10X Radonius','200X Radonius','20X Radonius','20X Radonius Prime','30X Radonius','40X Radonius','Allegia 50 Clasteron','Allegia 500 Clasteron','Allegia 50B Clasteron','Al... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_printsize.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_printsize.m | 1,447 | utf_8 | 0f0b6437c648b7a2e1310900262bd765 | function results = vl_test_printsize(varargin)
% VL_TEST_PRINTSIZE
vl_test_init ;
function s = setup()
s.fig = figure(1) ;
s.usletter = [8.5, 11] ; % inches
s.a4 = [8.26772, 11.6929] ;
clf(s.fig) ; plot(1:10) ;
function teardown(s)
close(s.fig) ;
function test_basic(s)
for sigma = [1 0.5 0.2]
vl_printsize(s.fig, s... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_cummax.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_cummax.m | 838 | utf_8 | 5e98ee1681d4823f32ecc4feaa218611 | function results = vl_test_cummax(varargin)
% VL_TEST_CUMMAX
vl_test_init ;
function test_basic()
vl_assert_almost_equal(...
vl_cummax(1), 1) ;
vl_assert_almost_equal(...
vl_cummax([1 2 3 4], 2), [1 2 3 4]) ;
function test_multidim()
a = [1 2 3 4 3 2 1] ;
b = [1 2 3 4 4 4 4] ;
for k=1:6
dims = ones(1,6) ;
dim... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_imintegral.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_imintegral.m | 1,429 | utf_8 | 4750f04ab0ac9fc4f55df2c8583e5498 | function results = vl_test_imintegral(varargin)
% VL_TEST_IMINTEGRAL
vl_test_init ;
function state = setup()
state.I = ones(5,6) ;
state.correct = [ 1 2 3 4 5 6 ;
2 4 6 8 10 12 ;
3 6 9 12 15 18 ;
4 8 12 ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_sift.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_sift.m | 1,318 | utf_8 | 806c61f9db9f2ebb1d649c9bfcf3dc0a | function results = vl_test_sift(varargin)
% VL_TEST_SIFT
vl_test_init ;
function s = setup()
s.I = im2single(imread(fullfile(vl_root,'data','box.pgm'))) ;
[s.ubc.f, s.ubc.d] = ...
vl_ubcread(fullfile(vl_root,'data','box.sift')) ;
function test_ubc_descriptor(s)
err = [] ;
[f, d] = vl_sift(s.I,...
... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_binsum.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_binsum.m | 1,377 | utf_8 | f07f0f29ba6afe0111c967ab0b353a9d | function results = vl_test_binsum(varargin)
% VL_TEST_BINSUM
vl_test_init ;
function test_three_args()
vl_assert_almost_equal(...
vl_binsum([0 0], 1, 2), [0 1]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, 1), [0 7]) ;
vl_assert_almost_equal(...
vl_binsum([1 7], -1, [1 2 2 2 2 2 2 2]), [0 0]) ;
function te... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_lbp.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_lbp.m | 892 | utf_8 | a79c0ce0c85e25c0b1657f3a0b499538 | function results = vl_test_lbp(varargin)
% VL_TEST_TWISTER
vl_test_init ;
function test_unfiorm_lbps(s)
% enumerate the 56 uniform lbps
q = 0 ;
for i=0:7
for j=1:7
I = zeros(3) ;
p = mod(s.pixels - i + 8, 8) + 1 ;
I(p <= j) = 1 ;
f = vl_lbp(single(I), 3) ;
q = q + 1 ;
vl_assert_equal(find(f... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_colsubset.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_colsubset.m | 828 | utf_8 | be0c080007445b36333b863326fb0f15 | function results = vl_test_colsubset(varargin)
% VL_TEST_COLSUBSET
vl_test_init ;
function s = setup()
s.x = [5 2 3 6 4 7 1 9 8 0] ;
function test_beginning(s)
vl_assert_equal(1:5, vl_colsubset(1:10, 5, 'beginning')) ;
vl_assert_equal(1:5, vl_colsubset(1:10, .5, 'beginning')) ;
function test_ending(s)
vl_assert_equa... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_alldist.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_alldist.m | 2,373 | utf_8 | 9ea1a36c97fe715dfa2b8693876808ff | function results = vl_test_alldist(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist(zeros(15,12), zeros(15,0), 'kl2'), ...
zeros(12,0)) ;
vl_assert_equa... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_ihashsum.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_ihashsum.m | 581 | utf_8 | edc283062469af62056b0782b171f5fc | function results = vl_test_ihashsum(varargin)
% VL_TEST_IHASHSUM
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(round(16*rand(2,100))) ;
sel = find(all(s.data==0)) ;
s.data(1,sel)=1 ;
function test_hash(s)
D = size(s.data,1) ;
K = 5 ;
h = zeros(1,K,'uint32') ;
id = zeros(D,K,'uint8');
next = zer... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_grad.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_grad.m | 434 | utf_8 | 4d03eb33a6a4f68659f868da95930ffb | function results = vl_test_grad(varargin)
% VL_TEST_GRAD
vl_test_init ;
function s = setup()
s.I = rand(150,253) ;
s.I_small = rand(2,2) ;
function test_equiv(s)
vl_assert_equal(gradient(s.I), vl_grad(s.I)) ;
function test_equiv_small(s)
vl_assert_equal(gradient(s.I_small), vl_grad(s.I_small)) ;
function test_equiv... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_whistc.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_whistc.m | 1,384 | utf_8 | 81c446d35c82957659840ab2a579ec2c | function results = vl_test_whistc(varargin)
% VL_TEST_WHISTC
vl_test_init ;
function test_acc()
x = ones(1, 10) ;
e = 1 ;
o = 1:10 ;
vl_assert_equal(vl_whistc(x, o, e), 55) ;
function test_basic()
x = 1:10 ;
e = 1:10 ;
o = ones(1, 10) ;
vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ;
x = linspace(-1,11,100) ;
o =... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_roc.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_roc.m | 1,019 | utf_8 | 9b2ae71c9dc3eda0fc54c65d55054d0c | function results = vl_test_roc(varargin)
% VL_TEST_ROC
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[tpr,tnr] = vl_roc(s.labels,s.scores0) ;
vl_assert_almost_equal(tpr, [0 1 2 2 2 2] / 2) ;
vl_assert_almost_equal(tnr,... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_dsift.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_dsift.m | 2,048 | utf_8 | fbbfb16d5a21936c1862d9551f657ccc | function results = vl_test_dsift(varargin)
% VL_TEST_DSIFT
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
s.I = rgb2gray(single(I)) ;
function test_fast_slow(s)
binSize = 4 ; % bin size in pixels
magnif = 3 ; % bin size / keypoint scale
scale = binSize... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_alldist2.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_alldist2.m | 2,284 | utf_8 | 89a787e3d83516653ae8d99c808b9d67 | function results = vl_test_alldist2(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
% TODO: test integer classes
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist2(zeros(15,12), zeros(15,0), 'kl2'), ...
... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_fisher.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_fisher.m | 2,097 | utf_8 | c9afd9ab635bd412cbf8be3c2d235f6b | function results = vl_test_fisher(varargin)
% VL_TEST_FISHER
vl_test_init ;
function s = setup()
randn('state',0) ;
dimension = 5 ;
numData = 21 ;
numComponents = 3 ;
s.x = randn(dimension,numData) ;
s.mu = randn(dimension,numComponents) ;
s.sigma2 = ones(dimension,numComponents) ;
s.prior = ones(1,numComponents) ;
s... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_imsmooth.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_imsmooth.m | 1,837 | utf_8 | 718235242cad61c9804ba5e881c22f59 | function results = vl_test_imsmooth(varargin)
% VL_TEST_IMSMOOTH
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
I = max(min(vl_imdown(I),1),0) ;
s.I = single(I) ;
function test_pad_by_continuity(s)
% Convolving a constant signal padded with continuity does not change... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_svmtrain.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_svmtrain.m | 4,277 | utf_8 | 071b7c66191a22e8236fda16752b27aa | function results = vl_test_svmtrain(varargin)
% VL_TEST_SVMTRAIN
vl_test_init ;
end
function s = setup()
randn('state',0) ;
Np = 10 ;
Nn = 10 ;
xp = diag([1 3])*randn(2, Np) ;
xn = diag([1 3])*randn(2, Nn) ;
xp(1,:) = xp(1,:) + 2 + 1 ;
xn(1,:) = xn(1,:) - 2 + 1 ;
s.x = [xp xn] ;
s.y = [ones(1,Np) ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_phow.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_phow.m | 549 | utf_8 | f761a3bb218af855986263c67b2da411 | function results = vl_test_phow(varargin)
% VL_TEST_PHOPW
vl_test_init ;
function s = setup()
s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
s.I = single(s.I) ;
function test_gray(s)
[f,d] = vl_phow(s.I, 'color', 'gray') ;
assert(size(d,1) == 128) ;
function test_rgb(s)
[f,d] = vl_phow(s.I, 'color',... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_kmeans.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_kmeans.m | 3,632 | utf_8 | 0e1d6f4f8101c8982a0e743e0980c65a | function results = vl_test_kmeans(varargin)
% VL_TEST_KMEANS
% Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
vl_test_init ;
function s = setup()
randn('sta... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_hikmeans.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_hikmeans.m | 463 | utf_8 | dc3b493646e66316184e86ff4e6138ab | function results = vl_test_hikmeans(varargin)
% VL_TEST_IKMEANS
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(rand(2,1000) * 255) ;
function test_basic(s)
[tree, assign] = vl_hikmeans(s.data,3,100) ;
assign_ = vl_hikmeanspush(tree, s.data) ;
vl_assert_equal(assign,assign_) ;
function test_elka... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_aib.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_aib.m | 1,277 | utf_8 | 78978ae54e7ebe991d136336ba4bf9c6 | function results = vl_test_aib(varargin)
% VL_TEST_AIB
vl_test_init ;
function s = setup()
s = [] ;
function test_basic(s)
Pcx = [.3 .3 0 0
0 0 .2 .2] ;
% This results in the AIB tree
%
% 1 - \
% 5 - \
% 2 - / \
% - 7
% 3 - \ /
% 6 - /
% 4 - /
%
% coded by the map [5 ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_plotbox.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_plotbox.m | 414 | utf_8 | aa06ce4932a213fb933bbede6072b029 | function results = vl_test_plotbox(varargin)
% VL_TEST_PLOTBOX
vl_test_init ;
function test_basic(s)
figure(1) ; clf ;
vl_plotbox([-1 -1 1 1]') ;
xlim([-2 2]) ;
ylim([-2 2]) ;
close(1) ;
function test_multiple(s)
figure(1) ; clf ;
randn('state', 0) ;
vl_plotbox(randn(4,10)) ;
close(1) ;
function test_style(s)
figure... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_imarray.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_imarray.m | 795 | utf_8 | c5e6a5aa8c2e63e248814f5bd89832a8 | function results = vl_test_imarray(varargin)
% VL_TEST_IMARRAY
vl_test_init ;
function test_movie_rgb(s)
A = rand(23,15,3,4) ;
B = vl_imarray(A,'movie',true) ;
function test_movie_indexed(s)
cmap = get(0,'DefaultFigureColormap') ;
A = uint8(size(cmap,1)*rand(23,15,4)) ;
A = min(A,size(cmap,1)-1) ;
B = vl_imarray(A,'m... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_homkermap.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_homkermap.m | 1,903 | utf_8 | c157052bf4213793a961bde1f73fb307 | function results = vl_test_homkermap(varargin)
% VL_TEST_HOMKERMAP
vl_test_init ;
function check_ker(ker, n, window, period)
args = {n, ker, 'window', window} ;
if nargin > 3
args = {args{:}, 'period', period} ;
end
x = [-1 -.5 0 .5 1] ;
y = linspace(0,2,100) ;
for conv = {@single, @double}
x = feval(conv{1}, x) ;... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_slic.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_slic.m | 200 | utf_8 | 12a6465e3ef5b4bcfd7303cd8a9229d4 | function results = vl_test_slic(varargin)
% VL_TEST_SLIC
vl_test_init ;
function s = setup()
s.im = im2single(vl_impattern('roofs1')) ;
function test_slic(s)
segmentation = vl_slic(s.im, 10, 0.1) ;
|
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_ikmeans.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_ikmeans.m | 466 | utf_8 | 1ee2f647ac0035ed0d704a0cd615b040 | function results = vl_test_ikmeans(varargin)
% VL_TEST_IKMEANS
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(rand(2,1000) * 255) ;
function test_basic(s)
[centers, assign] = vl_ikmeans(s.data,100) ;
assign_ = vl_ikmeanspush(s.data, centers) ;
vl_assert_equal(assign,assign_) ;
function test_elk... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_mser.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_mser.m | 242 | utf_8 | 1ad33563b0c86542a2978ee94e0f4a39 | function results = vl_test_mser(varargin)
% VL_TEST_MSER
vl_test_init ;
function s = setup()
s.im = im2uint8(rgb2gray(vl_impattern('roofs1'))) ;
function test_mser(s)
[regions,frames] = vl_mser(s.im) ;
mask = vl_erfill(s.im, regions(1)) ;
|
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_inthist.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_inthist.m | 811 | utf_8 | 459027d0c54d8f197563a02ab66ef45d | function results = vl_test_inthist(varargin)
% VL_TEST_INTHIST
vl_test_init ;
function s = setup()
rand('state',0) ;
s.labels = uint32(8*rand(123, 76, 3)) ;
function test_basic(s)
l = 10 ;
hist = vl_inthist(s.labels, 'numlabels', l) ;
hist_ = inthist_slow(s.labels, l) ;
vl_assert_equal(double(hist),hist_) ;
function... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_imdisttf.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_imdisttf.m | 1,885 | utf_8 | ae921197988abeb984cbcdf9eaf80e77 | function results = vl_test_imdisttf(varargin)
% VL_TEST_DISTTF
vl_test_init ;
function test_basic()
for conv = {@single, @double}
conv = conv{1} ;
I = conv([0 0 0 ; 0 -2 0 ; 0 0 0]) ;
D = vl_imdisttf(I);
assert(isequal(D, conv(- [0 1 0 ; 1 2 1 ; 0 1 0]))) ;
I(2,2) = -3 ;
[D,map] = vl_imdisttf(I) ;
asse... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_vlad.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_vlad.m | 1,977 | utf_8 | d3797288d6edb1d445b890db3780c8ce | function results = vl_test_vlad(varargin)
% VL_TEST_VLAD
vl_test_init ;
function s = setup()
randn('state',0) ;
s.x = randn(128,256) ;
s.mu = randn(128,16) ;
assignments = rand(16, 256) ;
s.assignments = bsxfun(@times, assignments, 1 ./ sum(assignments,1)) ;
function test_basic (s)
x = [1, 2, 3] ;
mu = [0, 0, 0] ;
a... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_pr.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_pr.m | 3,763 | utf_8 | 4d1da5ccda1a7df2bec35b8f12fdd620 | function results = vl_test_pr(varargin)
% VL_TEST_PR
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[rc,pr] = vl_pr(s.labels,s.scores0) ;
vl_assert_almost_equal(pr, [1 1/1 2/2 2/3 2/4 2/5]) ;
vl_assert_almost_equal(rc, ... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_hog.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_hog.m | 1,555 | utf_8 | eed7b2a116d142040587dc9c4eb7cd2e | function results = vl_test_hog(varargin)
% VL_TEST_HOG
vl_test_init ;
function s = setup()
s.im = im2single(vl_impattern('roofs1')) ;
[x,y]= meshgrid(linspace(-1,1,128)) ;
s.round = single(x.^2+y.^2);
s.imSmall = s.im(1:128,1:128,:) ;
s.imSmall = s.im ;
s.imSmallFlipped = s.imSmall(:,end:-1:1,:) ;
function test_basic... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_argparse.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_argparse.m | 795 | utf_8 | e72185b27206d0ee1dfdc19fe77a5be6 | function results = vl_test_argparse(varargin)
% VL_TEST_ARGPARSE
vl_test_init ;
function test_basic()
opts.field1 = 1 ;
opts.field2 = 2 ;
opts.field3 = 3 ;
opts_ = opts ;
opts_.field1 = 3 ;
opts_.field2 = 10 ;
opts = vl_argparse(opts, {'field2', 10, 'field1', 3}) ;
assert(isequal(opts, opts_)) ;
opts_.field1 = 9 ;
... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_liop.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_liop.m | 1,023 | utf_8 | a162be369073bed18e61210f44088cf3 | function results = vl_test_liop(varargin)
% VL_TEST_SIFT
vl_test_init ;
function s = setup()
randn('state',0) ;
s.patch = randn(65,'single') ;
xr = -32:32 ;
[x,y] = meshgrid(xr) ;
s.blob = - single(x.^2+y.^2) ;
function test_basic(s)
d = vl_liop(s.patch) ;
function test_blob(s)
% with a blob, all local intensity ord... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_test_binsearch.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/xtest/vl_test_binsearch.m | 1,339 | utf_8 | 85dc020adce3f228fe7dfb24cf3acc63 | function results = vl_test_binsearch(varargin)
% VL_TEST_BINSEARCH
vl_test_init ;
function test_inf_bins()
x = [-inf -1 0 1 +inf] ;
vl_assert_equal(vl_binsearch([], x), [0 0 0 0 0]) ;
vl_assert_equal(vl_binsearch([-inf 0], x), [1 1 2 2 2]) ;
vl_assert_equal(vl_binsearch([-inf], x), [1 1 1 1 1]) ;
vl_a... |
github | ZHANGXinxinPKU/defocus-deblurring-master | vl_roc.m | .m | defocus-deblurring-master/Defocus_code_xxzhang/vlfeat-0.9.20-bin/vlfeat-0.9.20/toolbox/plotop/vl_roc.m | 10,113 | utf_8 | 22fd8ff455ee62a96ffd94b9074eafeb | function [tpr,tnr,info] = vl_roc(labels, scores, varargin)
%VL_ROC ROC curve.
% [TPR,TNR] = VL_ROC(LABELS, SCORES) computes the Receiver Operating
% Characteristic (ROC) curve [1]. LABELS is a row vector of ground
% truth labels, greater than zero for a positive sample and smaller
% than zero for a negative o... |
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