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 | ignaciorlando/fundus-vessel-segmentation-tbme-master | vl_demo_kdtree_sift.m | .m | fundus-vessel-segmentation-tbme-master/Util/vlfeat/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 | ignaciorlando/fundus-vessel-segmentation-tbme-master | vl_impattern.m | .m | fundus-vessel-segmentation-tbme-master/Util/vlfeat/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 | ignaciorlando/fundus-vessel-segmentation-tbme-master | vl_tpsu.m | .m | fundus-vessel-segmentation-tbme-master/Util/vlfeat/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 | ignaciorlando/fundus-vessel-segmentation-tbme-master | vl_xyz2lab.m | .m | fundus-vessel-segmentation-tbme-master/Util/vlfeat/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 | ignaciorlando/fundus-vessel-segmentation-tbme-master | getLabeledDataFilenames.m | .m | fundus-vessel-segmentation-tbme-master/Util/other/getLabeledDataFilenames.m | 495 | utf_8 | 5a57ff659fe563b2ec1715164104abe8 |
function [images, labels, masks] = getLabeledDataFilenames(folder)
imagesFolder = strcat(folder, filesep, 'images', filesep);
masksFolder = strcat(folder, filesep, 'masks', filesep);
labelsFolder = strcat(folder, filesep, 'labels', filesep);
% Open images, masks and labels for the training set... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | resizeImages.m | .m | fundus-vessel-segmentation-tbme-master/Util/other/resizeImages.m | 148 | utf_8 | 4c7e4a2c4d1bc0a7a8d81468e24c4175 |
function [images] = resizeImages(images, scale)
for i = 1 : length(images)
images{i} = imresize(images{i}, scale);
end
end |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | encodeFileName.m | .m | fundus-vessel-segmentation-tbme-master/Util/other/encodeFileName.m | 626 | utf_8 | 787eb1e719666cc6efa2a2c41b2ea54a |
function [filefullname] = encodeFileName(root, param, type)
%training_dataset_uUNARIES_pPAIRWISES
filefullname = strcat(root, filesep, type, '_', param.dataset, '_', ...
'u', num2str(featuresToNumber(param.unaryFeatures)), '_', ...
'p', num2str(featuresToNumber(param.pairwiseFeatures)), ... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | removeFileNamesWithExtension.m | .m | fundus-vessel-segmentation-tbme-master/Util/other/removeFileNamesWithExtension.m | 543 | utf_8 | f9eced2fb806edf03d321fcb16d36d2e |
function [fileNames] = removeFileNamesWithExtension(fileNames, extension)
% newNames = {};
%
% % for each file name
% for i = 1 : length(fileNames)
% % if the filename contains the extension, it is saved in the list
% filename = fileNames{i};
% if ~strcmp(filename(end-3:e... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | getMultipleImagesFileNames.m | .m | fundus-vessel-segmentation-tbme-master/Util/other/getMultipleImagesFileNames.m | 511 | utf_8 | 71d12d783157b3f6fef5bd8ed3abd303 | % Open multiple files from a given directory
function allNames = getMultipleImagesFileNames(directory)
% Get all file names
allFiles = dir(directory);
% Get only the names of the images inside the folder
allNames = {allFiles.name};
allNames(strcmp(allNames, '..')) = [];
allNames(strcmp(al... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | openMultipleImages.m | .m | fundus-vessel-segmentation-tbme-master/Util/other/openMultipleImages.m | 581 | utf_8 | 66b2c48c4f5c4a2f30fdf9bf93ee00c7 | % Open multiple files from a given directory
function [images, allNames] = openMultipleImages(directory)
% Get all file names
allNames = getMultipleImagesFileNames(directory);
% Get all the images in the directory and count the number of pixels
images = cell(length(allNames), 1);
for i = 1:len... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | CRFInference.m | .m | fundus-vessel-segmentation-tbme-master/CRF/CRFInference.m | 1,041 | utf_8 | 37c019386c415ff5d586fee09bb9b56c |
function [segmentation] = CRFInference(config, unaryPotentials, mask, pairwiseFeatures, weights)
% CRFInference Obtain the segmentation by minimizing the overall energy of
% the CRF.
% [segmentation] = CRFInference(config, unaryPotentials, mask, pairwiseFeatures, weights)
% OUTPUT: segmentation: binary segmentati... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | FullyCRFWrapperWithGivenPairwises.m | .m | fundus-vessel-segmentation-tbme-master/CRF/CRF_1.0/FullyCRFWrapperWithGivenPairwises.m | 1,158 | utf_8 | f117e5ae97e8e2215ebbb84875838018 |
function y = FullyCRFWrapperWithGivenPairwises(config, unaryPotentials, mask, pairwiseFeatures, weights)
% FullyCRFWrapperWithGivenPairwises This function wrapps the MEX-function
% that implements the fully connected CRF inference
% y = FullyCRFWrapperWithGivenPairwises(config, unaryPotentials, mask, pairwiseFeatu... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | LocalNeighborhoodBasedCRF.m | .m | fundus-vessel-segmentation-tbme-master/CRF/maxflow/LocalNeighborhoodBasedCRF.m | 1,744 | utf_8 | 5b365e65ee536fda9c62f799be85ea51 |
function [segmentation] = LocalNeighborhoodBasedCRF(unaryPotentials, mask, pairwiseFeatures, weights)
% LocalNeighborhoodBasedCRF This function wrapps the inference on local
% neighborhood based CRFs.
% [segmentation] = LocalNeighborhoodBasedCRF(unaryPotentials, mask, pairwiseFeatures, weights)
% OUTPUT: segmenta... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | getLocalNeighborhoodBasedPairwisePotentials.m | .m | fundus-vessel-segmentation-tbme-master/CRF/maxflow/getLocalNeighborhoodBasedPairwisePotentials.m | 2,094 | utf_8 | e848d1ddee2c3f24aff8b4dd7d4c54d1 |
function [potentials] = getLocalNeighborhoodBasedPairwisePotentials(pairwiseFeatures, labels)
% getLocalNeighborhoodBasedPairwisePotentials This function computes
% efficiently the pairwise potentials.
% [potentials] = getLocalNeighborhoodBasedPairwisePotentials(pairwiseFeatures, labels)
% OUTPUT: potentials: pai... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | getBunchSegmentations2.m | .m | fundus-vessel-segmentation-tbme-master/Segmentations/getBunchSegmentations2.m | 4,863 | utf_8 | 1bf96eedccb35714092a13b6bbf3a0b4 |
function [segmentations, qualityMeasures] = getBunchSegmentations2(config, data, model)
% getBunchSegmentations2 Segment a number of given images
% [segmentations, qualityMeasures] = getBunchSegmentations2(config, data, model)
% OUTPUT: segmentations: a cell array containing all the segmentations
% qualit... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | getWeights.m | .m | fundus-vessel-segmentation-tbme-master/Segmentations/getWeights.m | 971 | utf_8 | 22e31e2d6fad1a6de01885e8c7d2d45d |
function [W_unaries, W_pairwises, bias] = getWeights(W, config)
% getWeights Separates the weights for unary, pairwise and bias
% [W_unaries, W_pairwises, bias] = getWeights(W, config)
% OUTPUT: W_unaries: weights for the unary potentials
% W_pairwises: weights for the pairwise potentials
% bias:... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | getSegmentationFromData2.m | .m | fundus-vessel-segmentation-tbme-master/Segmentations/getSegmentationFromData2.m | 4,557 | utf_8 | 5dfb170c71e4ddc797a125879c051af5 |
function [segmentation, qualityMeasures] = getSegmentationFromData2(config, mask, y, X, pairwiseKernels, model)
% getSegmentationFromData2 Segment a given image
% [segmentation, qualityMeasures] = getSegmentationFromData2(config, mask, y, X, pairwiseKernels, model)
% OUTPUT: segmentation: resulting segmentation
%... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | generateFeatureFilter.m | .m | fundus-vessel-segmentation-tbme-master/Features/Util/generateFeatureFilter.m | 662 | utf_8 | 71465f731b2b9b3bb962b462c87fe5d3 |
function [featureFilter] = generateFeatureFilter(selectedFeatures, sizes)
% generateFeatureFilter Generate a binary array to filter the features
% [featureFilter] = generateFeatureFilter(selectedFeatures, sizes)
% OUTPUT: featureFilter: a binary array indicating which features are going
% to be used
% IN... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | extractFeatures.m | .m | fundus-vessel-segmentation-tbme-master/Features/Extraction/extractFeatures.m | 1,739 | utf_8 | 7c5e7ab13809608a07c5019fa045f01a |
function [features, dimensionality, numberOfPixels, masks, imgNames] = extractFeatures(imagesPath, masksPath, config, selectedFeatures, isUnary)
%
%
%
%
% retrieve image names...
imgNames = getMultipleImagesFileNames(imagesPath);
% ...and mask names
mskNames = getMultipleImagesFileNames(mask... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | extractFeaturesFromSingleImage.m | .m | fundus-vessel-segmentation-tbme-master/Features/Extraction/extractFeaturesFromSingleImage.m | 3,226 | utf_8 | a61c7b919a2b541564106315e4092d67 |
function [features_array] = extractFeaturesFromSingleImage(imagesPath, imgName, mask, config, isUnary)
% Generic function to compute features
computedFeature = cell(size(config.features.features));
% for each of the features
for k = 1 : length(config.features.features)
% generate fe... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | getPairwiseDeviations.m | .m | fundus-vessel-segmentation-tbme-master/Features/Extraction/getPairwiseDeviations.m | 2,253 | utf_8 | d731b388d494dbfa0f3e234c2cf5370d |
function [pairwiseDeviations] = getPairwiseDeviations(pairwiseFeatures, pairwiseDimensionality)
% getPairwiseDeviations Obtain the pairwise deviations for the pairwise
% kernels.
% [pairwiseDeviations] = getPairwiseDeviations(pairwiseFeatures, pairwiseDimensionality)
% OUTPUT: pairwiseDeviations: pairwise deviati... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | getPairwiseFeatures.m | .m | fundus-vessel-segmentation-tbme-master/Features/Extraction/getPairwiseFeatures.m | 745 | utf_8 | f6baeaa9a2ea8fde29aa1dd9034821bb |
function [pairwiseKernels] = getPairwiseFeatures(pairwiseFeatures, deviations)
% getPairwiseFeatures Divide the pairwise features by the given deviations
% [pairwiseKernels] = getPairwiseFeatures(pairwiseFeatures, deviations)
% OUTPUT: pairwiseKernels: pairwise kernels.
% INPUT: pairwiseFeatures: a cell array con... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | Nguyen2013.m | .m | fundus-vessel-segmentation-tbme-master/Features/Features/Nguyen2013.m | 1,727 | utf_8 | b2cdf5e2e382a00044a1a273d83108c2 |
function [features, bestResponsesAngles] = Nguyen2013(I, mask, unary, options)
% Nguyen2013 Compute the Nguyen et al features
% I = Nguyen2013(I, mask, unary, options)
% OUTPUT: features: Nguyen et al features
% INPUT: I: grayscale image
% mask: a binary mask representing the FOV
% unary: a boolea... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | Intensities.m | .m | fundus-vessel-segmentation-tbme-master/Features/Features/Intensities.m | 1,217 | utf_8 | 52ee6644edf1503ee668edac833e9ad5 |
function I = Intensities(I, mask, unary, options)
% Intensities Compute the intensity feature
% I = Intensities(I, mask, unary, options)
% OUTPUT: I: image intensities
% INPUT: I: grayscale image
% mask: a binary mask representing the FOV
% unary: a boolean flag indicating if the feature is unary ... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | Zana2001.m | .m | fundus-vessel-segmentation-tbme-master/Features/Features/Zana2001.m | 2,518 | utf_8 | ed69ce86a873e61146dcf55e312166b5 |
function [zanan] = Zana2001(I, mask, unary, options)
% Zana2001 Compute the Zana and Klein feature
% I = Zana2001(I, mask, unary, options)
% OUTPUT: features: Zana and Klein features
% INPUT: I: grayscale image
% mask: a binary mask representing the FOV
% unary: a boolean flag indicating if the fe... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | standardize.m | .m | fundus-vessel-segmentation-tbme-master/Features/Features/nguyen/standardize.m | 705 | utf_8 | a230c73b3ee00ca28f0157a0325e1bf3 | function simg = standardize(img,mask,wsize)
if (nargin == 2 || wsize == 0)
simg = globalstandardize(img,mask);
else
img(mask == 0) = 0;
img_mean = nlfilter(img,[wsize, wsize],@getmean);
img_std = nlfilter(img,[wsize, wsize],@getstd);
simg = (img - img_mean)./img_std;
simg(img_std =... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | get_lineresponse.m | .m | fundus-vessel-segmentation-tbme-master/Features/Features/nguyen/get_lineresponse.m | 705 | utf_8 | 7b1133993d0e6985ea4537c26d61c7f8 |
function [R, bestResponse] = get_lineresponse(I, angles, W, L)
% img: extended inverted gc
% W: window size, L: line length
% R: line detector response
% Compute the average
avgresponse = imfilter(I, fspecial('average', W), 'replicate');
% Compute the responses
imglinestrength... |
github | ignaciorlando/fundus-vessel-segmentation-tbme-master | get_linemask.m | .m | fundus-vessel-segmentation-tbme-master/Features/Features/nguyen/get_linemask.m | 2,209 | utf_8 | bdad43b772ba3d768d25e519921bbf87 | function linemask = get_linemask(theta,masksize)
% (theta,masksize)
% Create a mask for line with angle theta
if theta > 90
mask = getbasemask(180- theta,masksize);
linemask = rotatex(mask);
else
linemask = getbasemask(theta,masksize);
end
% imshow(linemask,'InitialMagnification','fit');
end
funct... |
github | uttamavillain/FinalProject_CS231A-master | homography2d.m | .m | FinalProject_CS231A-master/homography2d.m | 1,461 | utf_8 | 7c1627dbec4b7c4664b392b242bdf698 | function H = homography2d(varargin)
[x1, x2] = checkargs(varargin(:));
% Attempt to normalise each set of points so that the origin
% is at centroid and mean distance from origin is sqrt(2).
[x1, T1] = normalise2dpts(x1);
[x2, T2] = normalise2dpts(x2);
% Note that it may have not bee... |
github | FengZhenhua/Supervised-Descent-Method-master | obtain_features.m | .m | Supervised-Descent-Method-master/src/obtain_features.m | 1,347 | utf_8 | c709ec726464c346419b6c9d2738c863 | %
% Supervised descent method for facial landmark detection and face tracking
%
% Subfunction used for extracting shape-indexed local features
%
% Copyright @ Zhenhua Feng, fengzhenhua2010@gmail.com
% Centre for Vision, Speech and Signal Processing, University of Surrey
%
% Please cite the following papers if you are u... |
github | FengZhenhua/Supervised-Descent-Method-master | fit_sdm.m | .m | Supervised-Descent-Method-master/src/fit_sdm.m | 1,121 | utf_8 | 28ea9d8b2fe6e3bd4dcb67e915360657 | %
% Supervised descent method for facial landmark detection and face tracking
%
% Subfunction used for fitting SDM to a new image
%
% Copyright @ Zhenhua Feng, fengzhenhua2010@gmail.com
% Centre for Vision, Speech and Signal Processing, University of Surrey
%
% Please cite the following papers if you are using this cod... |
github | FengZhenhua/Supervised-Descent-Method-master | project_s2b.m | .m | Supervised-Descent-Method-master/src/project_s2b.m | 1,252 | utf_8 | a9d54da30da31b93722fd4b287f43b9a | %
% Supervised descent method for facial landmark detection and face tracking
%
% Subfunction used for projecting a shape to a face bounding box
%
% Copyright @ Zhenhua Feng, fengzhenhua2010@gmail.com
% Centre for Vision, Speech and Signal Processing, University of Surrey
%
% Please cite the following papers if you ar... |
github | FengZhenhua/Supervised-Descent-Method-master | train_sdm.m | .m | Supervised-Descent-Method-master/src/train_sdm.m | 2,560 | utf_8 | 73122b63f932cbe17b977daacbe72c86 | %
% Supervised descent method for facial landmark detection and face tracking
%
% Subfunction used for training of cascaded linear regressors in SDM
%
% Copyright @ Zhenhua Feng, fengzhenhua2010@gmail.com
% Centre for Vision, Speech and Signal Processing, University of Surrey
%
% Please cite the following papers if you... |
github | meng-tang/PBO-master | setOptimizationOptions.m | .m | PBO-master/pairwise/setOptimizationOptions.m | 1,477 | utf_8 | 5ef34ada2d59fed2fe6fbf666f68f974 |
function newOptimizationOptions = setOptimizationOptions(grayScalar, myString, lambdaPotts, beta, padSize, nType, fg_mu, bg_mu, sigma)
if nargin ==5
nType = 4;
fg_mu = 0;
bg_mu = 1;
sigma = 0.5;
end
% OPTIMIZATION PARAMS
newOptimizationOptions.padSize = padSize;
newOptimizationOptions.neighb... |
github | meng-tang/PBO-master | getDeconvolutionEnergy.m | .m | PBO-master/pairwise/getDeconvolutionEnergy.m | 5,047 | utf_8 | d0470db84caeda55621e0c2dbc1e6d49 | % function [unaryTerms pairwiseTerms] = getDeconvolutionEnergy(numRows, numCols, img, optimizationOptions)
%
% myFilter = optimizationOptions.myFilter;
%
% filterSize = size(myFilter,1);
% padSize = filterSize;
% unaryTerms = zeros(numRows, numCols);
% myFilterSquared = myFilter(:)*myFilter(:)'... |
github | hanchuan/vaa3d_tools-master | scanChecks.m | .m | vaa3d_tools-master/hackathon/brl/s2/scanChecks.m | 706 | utf_8 | a6acf1d0f927c909e8e3dca1bfdc88e2 | %% checking PV scan parameter relationships
function out = scanChecks(xPixels, linePeriod, dwellTime, mode, piezoDelay, nSlices)
yPixels = xPixels;
dwellTime*xPixels;
% 5.7ms
% 0.9205 percent duty cycle.
% lost time:
lost = linePeriod-dwellTime*xPixels ; % = 0.5ms per line lost. where to?
% front porch and backpo... |
github | hanchuan/vaa3d_tools-master | xml2struct.m | .m | vaa3d_tools-master/hackathon/brl/s2/xml2struct.m | 6,955 | utf_8 | 58f0b998cc71b30b4a6a12b330cfe950 | function [ s ] = xml2struct( file )
%Convert xml file into a MATLAB structure
% [ s ] = xml2struct( file )
%
% A file containing:
% <XMLname attrib1="Some value">
% <Element>Some text</Element>
% <DifferentElement attrib2="2">Some more text</Element>
% <DifferentElement attrib3="2" attrib4="1">Even more t... |
github | hanchuan/vaa3d_tools-master | findKeyInShard.m | .m | vaa3d_tools-master/hackathon/brl/s2/findKeyInShard.m | 1,144 | utf_8 | 34ba862a7606c939816fdbf7a8de68e8 |
function out = findKeyInShard(stateShard,keystring,indexedValue)
elementList = [];
out = {};
outputIndex = 0;
for i=1:numel(stateShard)
if sum(strfind(stateShard{i}.Attributes.key,keystring))>0
elementList = [elementList,i];
if isfield(stateShard{i}, 'IndexedValue')
if isempty(indexedVa... |
github | hanchuan/vaa3d_tools-master | save_centralbrain.m | .m | vaa3d_tools-master/hackathon/2010/lobeseg/save_centralbrain.m | 519 | utf_8 | 27bab3acd9178b1ba2d9d727223012c2 | % function save_centralbrain(In_Filename, Out_Filename)
% by Benny Lam Sep 22, 2008
%
% Function to save the central brain after cutting off the optic lobes as
% the third channel mask.
function save_centralbrain(In_Filename, Out_Filename)
aa = loadRaw2Stack(In_Filename);
sz = size(aa);
for z=1:sz(3)
for y=1:sz... |
github | hanchuan/vaa3d_tools-master | cal_eigen_hessian.m | .m | vaa3d_tools-master/hackathon/zhi/local_enhancement/cal_eigen_hessian.m | 1,976 | utf_8 | d6d6a05a5cc846f37ab7e9fbcc549d98 | function cal_eigen_hessian(infile)
%function cal_eigen_hessian(infile)
% by Hanchuan Peng
% 2013-08-27
a=loadRaw2Stack(infile);
a=double(a);
%%
bxx=mydiff3d(mydiff3d(a,1), 1);
bxy=mydiff3d(mydiff3d(a,1), 2);
bxz=mydiff3d(mydiff3d(a,1), 3);
byx=mydiff3d(mydiff3d(a,2), 1);
byy=mydiff3d(mydiff3d(a,2), 2);
byz=mydiff3d... |
github | hanchuan/vaa3d_tools-master | compileMex.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/bigneuron_AmosSironi_PrzemyslawGlowacki_SQBTree_plugin/libs/sqb_0.1/src/MatrixSQB/compileMex.m | 1,476 | utf_8 | 320fc6bb584f8f38ed216ebbd2758099 | % LBFGS_BUILD_PATH is the path where LBFGS was built
function compileMex(LBFGS_BUILD_PATH, OUTPUT_PATH, debug)
if nargin < 2
OUTPUT_PATH = '../../build';
end
if nargin < 3
debug = false;
end
switch computer
case {'GLNXA64', 'GLNX86'}
mexCmd = ...
sprintf('mex -DMEX -I../../include -lr... |
github | hanchuan/vaa3d_tools-master | compileMexRegStump.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/bigneuron_AmosSironi_PrzemyslawGlowacki_SQBTree_plugin/libs/sqb_0.1/src/MatrixSQB/compileMexRegStump.m | 1,064 | utf_8 | 5f8bb04b0f350b27da07d41dfb2a7647 | % LBFGS_BUILD_PATH is the path where LBFGS was built
function compileMexRegStump(LBFGS_BUILD_PATH, OUTPUT_PATH, debug)
if nargin < 2
OUTPUT_PATH = '../../build';
end
if nargin < 3
debug = false;
end
mexCmd = ...
sprintf('mex -DMEX -I../../include -I%s/include -lrt %s/lib/.libs/lbfgs.o', LBFGS_BUILD_PATH... |
github | hanchuan/vaa3d_tools-master | save_centralbrain.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/Janelia_lobeseg/lobeseg_main/save_centralbrain.m | 519 | utf_8 | 27bab3acd9178b1ba2d9d727223012c2 | % function save_centralbrain(In_Filename, Out_Filename)
% by Benny Lam Sep 22, 2008
%
% Function to save the central brain after cutting off the optic lobes as
% the third channel mask.
function save_centralbrain(In_Filename, Out_Filename)
aa = loadRaw2Stack(In_Filename);
sz = size(aa);
for z=1:sz(3)
for y=1:sz... |
github | hanchuan/vaa3d_tools-master | normalize_points.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/celegans_seganno/main_src/matlab/normalize_points.m | 656 | utf_8 | f161a8f4becb064c68b7dd0a84f7e209 | %centrilize and scale the point set
%xn = T*x;
%x: every column represent a point [3*N]
%by Lei Qu
function [xn, T]=normalize_points(x)
% compute the center of every points's XYZ coordinate
x_avg=mean(x, 2);
% center the points
for i=1:size(x,1)
xc(i,:)=x(i,:)-x_avg(i);
end
% compute the average distance of ever... |
github | hanchuan/vaa3d_tools-master | genscript_1.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/celegans_seganno/main_src/matlab/genscript_1.m | 2,575 | utf_8 | f30c28080c98b57405434107a5e4531c | % revised by Hanchuan Peng, 20110524 for testing on pengh-wm1
%generate the script for celegans cell annotation
%for standford_326 data
function genscript_1(n,filefullname,dir_output)
%fixed files
%filename_atlas_input='/groups/peng/home/qul/myhome/work/0.data/celegans_anno/atlas_related/atlas.apo';
DATAHOMEDIR = ... |
github | hanchuan/vaa3d_tools-master | save_arr2apo.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/celegans_seganno/main_src/matlab/save_arr2apo.m | 628 | utf_8 | 01396e690df949b15030e401ddb7eb4f | %save 3xN arr_pos to apo file
function save_arr2apo(arr_pos,arr_name,filename)
for i=1:size(arr_pos,2)
cellarr{i}.n=i;
cellarr{i}.orderinfo=num2str(i);
cellarr{i}.name=arr_name{i};
cellarr{i}.comment='';
cellarr{i}.pixmax=0;
cellarr{i}.intensity=79;
cellarr{i}.sdev=18;
cellarr{i}.volsiz... |
github | hanchuan/vaa3d_tools-master | affine3D_model.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/celegans_seganno/main_src/matlab/affine3D_model.m | 1,198 | utf_8 | aea39e0610043c6583377a891bc8faf8 | %compute 3D affine transform matrix
%X2=T*X1
%X1,X2=[3,N]
%by Lei Qu
function T=affine3D_model(X1,X2)
% normalize points
[X1,T1]=normalize_points(X1);
[X2,T2]=normalize_points(X2);
% fill matrix A
%
% | h1, h2, h3, h4 | |x1| |x2|
% | h5, h6, h7, h8 | * |y1|=|y2| <=>
% | h9, h10,h11,h12| |z1| |z2|
% | 0 , ... |
github | hanchuan/vaa3d_tools-master | ctps_warp_pts.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/celegans_seganno/main_src/matlab/ctps_warp_pts.m | 2,116 | utf_8 | b17a269781bfe01f623db91cec513166 | % Robust Point Matching (RPM) Demo (version 20000427):
% ----------------------------------------------------
% Copyright (C) 2000 Haili Chui, Anand Rangarajan
%
% Authors: Haili Chui and Anand Rangarajan
% Date: 04/27/2000
%
% Contact Information:
%
% Haili Chui: chui@noodle.med.yale.edu
% Anand Rangarajan: anan... |
github | hanchuan/vaa3d_tools-master | ctps_gen.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/celegans_seganno/main_src/matlab/ctps_gen.m | 5,198 | utf_8 | 986f7d687f76a1ce614933703f39eda5 | % Robust Point Matching (RPM) Demo (version 20000427):
% ----------------------------------------------------
% Copyright (C) 2000 Haili Chui, Anand Rangarajan
%
% Authors: Haili Chui and Anand Rangarajan
% Date: 04/27/2000
%
% Contact Information:
%
% Haili Chui: chui@noodle.med.yale.edu
% Anand Rangarajan: anan... |
github | hanchuan/vaa3d_tools-master | save_centralbrain.m | .m | vaa3d_tools-master/released_plugins/v3d_plugins/lobeseg/lobeseg_main/save_centralbrain.m | 519 | utf_8 | 27bab3acd9178b1ba2d9d727223012c2 | % function save_centralbrain(In_Filename, Out_Filename)
% by Benny Lam Sep 22, 2008
%
% Function to save the central brain after cutting off the optic lobes as
% the third channel mask.
function save_centralbrain(In_Filename, Out_Filename)
aa = loadRaw2Stack(In_Filename);
sz = size(aa);
for z=1:sz(3)
for y=1:sz... |
github | hanchuan/vaa3d_tools-master | polygon2voxel_double.m | .m | vaa3d_tools-master/bigneuron_ported/pcole/Main/Functions/polygon2voxel/polygon2voxel_double.m | 5,866 | utf_8 | 1d04ca8f6b0527fa906781f71944aa5d | function Volume=polygon2voxel_double(FacesA,FacesB,FacesC,VerticesX,VerticesY,VerticesZ,VolumeSize,Wrap)
Vertices=[VerticesX(:) VerticesY(:) VerticesZ(:)]-1;
% List with all vertices coordinates of a face
FaceVertices=[Vertices(FacesA,:) Vertices(FacesB,:) Vertices(FacesC,:)];
Volume=false(VolumeSize);
Volume=Dr... |
github | hanchuan/vaa3d_tools-master | findTerminalsold.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/Objects/@SpineAnalysisImage/findTerminalsold.m | 2,416 | utf_8 | 51ae37395fe53f9403207ec081bd3cc5 |
function out=findTerminals(y, th, n, maxn)
% function to find bouton (synaptic terminal) locations
% INPUTS: y - vector of intesities along the axonal contour
% th - fractional intensity elevation required to score as axon (i.e. 0.2 means 20%)
% n - 'size' of a terminal (say 10 for pixels ize 0.0... |
github | hanchuan/vaa3d_tools-master | findTerminalsoldversion.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/Objects/@SpineAnalysisImage/findTerminalsoldversion.m | 2,425 | utf_8 | dfd5a603e9886bf518cdc7fb6f32ce5f |
function out=findTerminals(y, th, n)
% function to find bouton (synaptic terminal) locations
% INPUTS: y - vector of intesities along the axonal contour
% th - fractional intensity elevation required to score as axon (i.e. 0.2 means 20%)
% n - 'size' of a terminal (say 10 for pixels ize 0.080)
%... |
github | hanchuan/vaa3d_tools-master | findTerminals.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/Objects/@SpineAnalysisImage/findTerminals.m | 2,416 | utf_8 | 51ae37395fe53f9403207ec081bd3cc5 |
function out=findTerminals(y, th, n, maxn)
% function to find bouton (synaptic terminal) locations
% INPUTS: y - vector of intesities along the axonal contour
% th - fractional intensity elevation required to score as axon (i.e. 0.2 means 20%)
% n - 'size' of a terminal (say 10 for pixels ize 0.0... |
github | hanchuan/vaa3d_tools-master | _FindSpines.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/Objects/@SpineAnalysisImage/_FindSpines.m | 7,611 | utf_8 | aa9312fc76947d2eee2c425cae81400f | % --------------------------------------------------------------------
function obj = FindSpines_Callback(obj)
if isfield(obj.data,'burnArray') & isfield(obj.data,'dendrites')
for i=1:size(obj.data.dendrites,2)
% the C program uses indices starting from 0. This needs to be converted
% to MATLAB co... |
github | hanchuan/vaa3d_tools-master | FindSpines.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/Objects/@SpineAnalysisImage/FindSpines.m | 7,611 | utf_8 | aa9312fc76947d2eee2c425cae81400f | % --------------------------------------------------------------------
function obj = FindSpines_Callback(obj)
if isfield(obj.data,'burnArray') & isfield(obj.data,'dendrites')
for i=1:size(obj.data.dendrites,2)
% the C program uses indices starting from 0. This needs to be converted
% to MATLAB co... |
github | hanchuan/vaa3d_tools-master | generatedat.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/Objects/@SpineSeriesAnalysis/generatedat.m | 2,171 | utf_8 | a73ca496167eee4d9947f206744287e8 | % generate .dat file
function self=generatedat(db,experimentuid)
self=struct();
% Add experiment
db.experiments(experimentuid).uid=experimentuid;
self.data.ch(1).imagemedian=db.experiments(experimentuid).imagemedian;
self.data.ch(1).imagestd=db.experiments(experimentuid).imagestd;
if isfield(db.experiments(exp... |
github | hanchuan/vaa3d_tools-master | nextpair.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/Objects/@SpineSeriesAnalysis/nextpair.m | 6,810 | utf_8 | 52a177bdf977cd9bb6a38c10809bfa00 | function objseries=nextpair(objseries)
global self;
global objects;
global ogh;
global imageobj;
filenames=objseries.state.display.filenames;
pathname=objseries.state.pathname;
pathnames=objseries.state.display.pathnames;
fileselection=objseries.state.display.fileselection;
% Save previous images
try
if ... |
github | hanchuan/vaa3d_tools-master | medfilt1.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/medfilt1.m | 677 | utf_8 | ff487f8ea0313e086e49c563faf97027 | %MEDFILT1 One-dimensional median filter
%
% y = MEDFILT(x)
% y = MEDFILT(x, w)
%
% median filter the signal with window of width W (default is 5).
%
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% pic 6/93
% vectorized version 8/95 pic
function m = medfilt1(s, w)
if nargi... |
github | hanchuan/vaa3d_tools-master | selectboutonsfromexcel3.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/selectboutonsfromexcel3.m | 47,215 | utf_8 | 864d0cb3eee57fbd7271f66cfa3f3088 | % first read in the source file
function selectboutonsfromexcel3
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% change parameters here!!!!
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
gainthres=1.3;
lossthres=1.3;
keepthres=2;
stableperiod=7;
[fname, pname] = uigetfile({'*.xlsx','*.xls'}, 'Specify the file to analyze');
pan... |
github | hanchuan/vaa3d_tools-master | findTerminals.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/findTerminals.m | 5,065 | utf_8 | b6b721668bbb0f6050179467d53077a3 |
function [out, Rel, Abs]=findTerminals(y, thRel, thAbs, maxwidth,minwidth)
% function to find boutons (synaptic terminals)
% INPUTS: y - vector of intesities along the axonal contour; units are
% backbone intensities
% thRel - fractional intensity elevation required to score as bouton (i.e. 0.2 m... |
github | hanchuan/vaa3d_tools-master | modelPMTIntegral.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/modelPMTIntegral.m | 1,628 | utf_8 | cd197153190756dd596572b1fabc27c6 | function [AreaInt,AreaSamp]=modelPMTIntegral(pulseWidth,samplingRate)
% This function compares the integral of a random waveform generated
% using 10x sampling with reference to the pulsewidth(i.e. 1 1e-6 sec pulsewidth is sampled at 10
% 10 MHz to one that would be sampled at the sampling rate, like we do in Scan... |
github | hanchuan/vaa3d_tools-master | findpeaks.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/findpeaks.m | 7,658 | utf_8 | 8abe508f1859a897583e07cc5c44e284 | function [pks,locs] = findpeaks(X,varargin)
%FINDPEAKS Find local peaks in data
% PKS = FINDPEAKS(X) finds local peaks in data set X where is a
% vector
%
% [PKS,LOCS]= FINDPEAKS(X) also returns the indices LOCS at which the
% peaks occur.
%
% [...] = FINDPEAKS(X,'MINPEAKHEIGHT',MPH) finds only those ... |
github | hanchuan/vaa3d_tools-master | generatedat.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/generatedat.m | 2,235 | utf_8 | 7553b56beb21e751a71e709b9b2bb4a3 | % generate .dat file
function self=generatedat(db,experimentuid)
self=struct();
% Add experiment
db.experiments(experimentuid).uid=experimentuid;
self.data.ch(1).imagemedian=db.experiments(experimentuid).imagemedian;
self.data.ch(1).imagestd=db.experiments(experimentuid).imagestd;
if isfield(db.experiments(exp... |
github | hanchuan/vaa3d_tools-master | medfilt1cir.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/medfilt1cir.m | 680 | utf_8 | 6671d916350e21788592886144118250 | %MEDFILT1 One-dimensional median filter
%
% y = MEDFILT(x)
% y = MEDFILT(x, w)
%
% median filter the signal with window of width W (default is 5).
%
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% pic 6/93
% vectorized version 8/95 pic
function m = medfilt1cir(s, w)
if na... |
github | hanchuan/vaa3d_tools-master | smooth.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/smooth.m | 19,289 | utf_8 | 51817959356b84d3b8973a172b3c5ae4 | function [c,ww] = smooth(varargin)
%SMOOTH Smooth data.
% Z = SMOOTH(Y) smooths data Y using a 5-point moving average.
%
% Z = SMOOTH(Y,SPAN) smooths data Y using SPAN as the number of points used
% to compute each element of Z.
%
% Z = SMOOTH(Y,SPAN,METHOD) smooths data Y with specified METHOD. The
% ... |
github | hanchuan/vaa3d_tools-master | summarygraphshort.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/summarygraphshort.m | 21,055 | utf_8 | 7affbccd1533ffb32aae5616aa9667cf | function summarygraphshort(overdayden,positions,terminalpositions,daypositions,dayterminalpositions,acrossday,terminalacrossday,stablethres,lastlabel,a,b,pathnames,daystartpos,dayendpos)
figure;
maximize(gcf);
try
ibs=[];
itbs=[];
icbs=[];
for j=1:size(overdayden,2)
if isfinite(overdayde... |
github | hanchuan/vaa3d_tools-master | cluster.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/cluster.m | 7,647 | utf_8 | 81c3068f0a048d9a8ee14d8ff588ced3 | function T = cluster(Z, varargin)
%CLUSTER Construct clusters from LINKAGE output.
% T = CLUSTER(Z,'CUTOFF',C) constructs clusters from cluster
% tree Z. Z is a matrix of size M-1 by 3, generated by LINKAGE.
% C is a threshold for cutting the hierarchical tree generated
% by LINKAGE into clusters. Cluste... |
github | hanchuan/vaa3d_tools-master | selectboutonsfromexcel.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/selectboutonsfromexcel.m | 47,218 | utf_8 | 2f1cec58a60027f2cc2450dd66f28b16 | % first read in the source file
function selectboutonsfromexcel
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% change parameters here!!!!
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
gainthres=1.3;
lossthres=1.3;
keepthres=2;
stableperiod=7;
[fname, pname] = uigetfile({'*.xlsx','*.xls'}, 'Specify the file to analyze');
pane... |
github | hanchuan/vaa3d_tools-master | selectboutonsfromexcel4.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/selectboutonsfromexcel4.m | 47,101 | utf_8 | 5422620cfd6e6179274d396e07e537f1 | % first read in the source file
function selectboutonsfromexcel4
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% change parameters here!!!!
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
gainthres=1.3;
lossthres=1.3;
keepthres=2;
stableperiod=7;
[fname, pname] = uigetfile({'*.xlsx','*.xls'}, 'Specify the file to analyze');
pan... |
github | hanchuan/vaa3d_tools-master | thresholdbackground.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/thresholdbackground.m | 2,012 | utf_8 | 1dbd8e7836919e7b7c3500cdde2e3986 | %THRESHOLD Thresholding
%
% SYNOPSIS:
% image_out = thresholdbackground(image_in,parameter)
%
% PARAMETERS:
% parameter ('background'): Distance to the peak where we cut-off, in
% terms of the half-width at half the maximum.
% Inf selects the default v... |
github | hanchuan/vaa3d_tools-master | selectboutonsfromexcel2.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/selectboutonsfromexcel2.m | 47,224 | utf_8 | 055946fa402c97eaf82ba74de741f50e | % first read in the source file
function selectboutonsfromexcel2
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% change parameters here!!!!
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
gainthres=1.3;
lossthres=1.3;
keepthres=2;
stableperiod=7;
[fname, pname] = uigetfile({'*.xlsx','*.xls'}, 'Specify the file to analyze');
pan... |
github | hanchuan/vaa3d_tools-master | generatecontrolplot.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/generatecontrolplot.m | 5,455 | utf_8 | 6d203b689b6888805edf834cd8f8d2fc | function generatecontrolplot()
color='k';
figure;
perROI=[];
perbouton=[];
meanperbouton=[];
errorperbouton=[];
perROIvar=[];
meanperboutonvar=[];
errorperboutonvar=[];
perboutonturnover=[];
load -mat d:\axons\fix.db
[a,b,c,d,e,f]=getavgvalues(db.summaries([1:2 4:5]));
perROI=[perROI; a];
meanperbo... |
github | hanchuan/vaa3d_tools-master | medfilt1pad.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/medfilt1pad.m | 680 | utf_8 | 71edfe727265cc66b98786c93d4e314e | %MEDFILT1 One-dimensional median filter
%
% y = MEDFILT(x)
% y = MEDFILT(x, w)
%
% median filter the signal with window of width W (default is 5).
%
%
% Copyright (c) Peter Corke, 1999 Machine Vision Toolbox for Matlab
% pic 6/93
% vectorized version 8/95 pic
function m = medfilt1pad(s, w)
if na... |
github | hanchuan/vaa3d_tools-master | tokenize.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/utilities/tokenize.m | 611 | utf_8 | fa4e39d955ca8d532dd823571a70b288 | function out=tokenize(line)
out={};
line=deblank(line);
while (length(line)>0)
[token, line]=getToken(line);
if (length(token)>0)
out{length(out)+1}=token;
end
end
function [token, remLine]=getToken(line)
[token, remLine]=strtok(line);
if length(token)==0
return
end
if any(findstr(... |
github | hanchuan/vaa3d_tools-master | createConfigFileFast.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/io/file_io/initialization/createConfigFileFast.m | 1,672 | utf_8 | 72e7f0f908292dc363686cb567cb4520 | function createConfigFile(bitFlags, fid, outputFlag)
global configGlobals
if isstruct(configGlobals)
fNames=fieldnames(configGlobals);
for i=1:length(fNames)
recurseCreateConfigFile(fNames{i}, bitFlags, '', fid, outputFlag);
end
end
recurseCreateConfigFile('state', bitFlags, '', fid, outputFlag);
... |
github | hanchuan/vaa3d_tools-master | SpineSeriesAnalysisAxon.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/guis/gui_building/SpineSeriesAnalysisAxon.m | 26,249 | utf_8 | 85970e12afaaa909198ca8fd80487996 | function varargout = SpineSeriesAnalysisAxon(varargin)
% SPINESERIESANALYSISAXON Application M-file for SpineSeriesAnalysis.fig
% FIG = SPINESERIESANALYSISAXON launch SpineSeriesAnalysis GUI.
% SPINESERIESANALYSISAXON('callback_name', ...) invoke the named callback.
% Last Modified by GUIDE v2.5 12-Jan-2004... |
github | hanchuan/vaa3d_tools-master | SeriesAnalysisAxon.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/guis/gui_building/SeriesAnalysisAxon.m | 26,244 | utf_8 | 5227464ea109b914f5f6450f7c7899a2 | function varargout = SeriesAnalysisAxon(varargin)
% SPINESERIESANALYSISAXON Application M-file for SpineSeriesAnalysis.fig
% FIG = SPINESERIESANALYSISAXON launch SpineSeriesAnalysis GUI.
% SPINESERIESANALYSISAXON('callback_name', ...) invoke the named callback.
% Last Modified by GUIDE v2.5 12-Jan-2004 11:4... |
github | hanchuan/vaa3d_tools-master | spineanalysisimageGUI.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/guis/gui_building/spineanalysisimageGUI.m | 40,507 | utf_8 | 08317ebff5daa270f4480fb1d863d4a3 | function varargout = spineanalysisimageGUI(varargin)
% spineanalysisimageGUI Application M-file for spineanalysisimageGUI.fig
% FIG = spineanalysisimageGUI launch spineanalysisimageGUI GUI.
% spineanalysisimageGUI('callback_name', ...) invoke the named callback.
% Last Modified by GUIDE v2.5 08-Feb-2011 14:... |
github | hanchuan/vaa3d_tools-master | excludeboutondialog.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/guis/gui_building/excludeboutondialog.m | 8,433 | utf_8 | 702159dfc5c5961faf28ded523237a11 | function varargout = excludeboutondialog(varargin)
% EXCLUDEBOUTONDIALOG M-file for excludeboutondialog.fig
% EXCLUDEBOUTONDIALOG by itself, creates a new EXCLUDEBOUTONDIALOG or raises the
% existing singleton*.
%
% H = EXCLUDEBOUTONDIALOG returns the handle to a new EXCLUDEBOUTONDIALOG or the handl... |
github | hanchuan/vaa3d_tools-master | SpineAnalysisImageGUI.m | .m | vaa3d_tools-master/bigneuron_ported/cher/EPBscore/guis/gui_building/SpineAnalysisImageGUI/SpineAnalysisImageGUI.m | 40,505 | utf_8 | 9bb9899159e3644defa032d5d39a27ca | function varargout = SpineAnalysisImageGUI(varargin)
% SpineAnalysisImageGUI Application M-file for SpineAnalysisImageGUI.fig
% FIG = SpineAnalysisImageGUI launch SpineAnalysisImageGUI GUI.
% SpineAnalysisImageGUI('callback_name', ...) invoke the named callback.
% Last Modified by GUIDE v2.5 08-Feb-2011 14:... |
github | hanchuan/vaa3d_tools-master | vaa3d_trace3D.m | .m | vaa3d_tools-master/bigneuron_ported/pengyu_zhihao/instruction/vaa3d_trace3D.m | 389 | utf_8 | bc918e7111d40a97c3f0d20426a4a95f | % vaa3d_trace3D: sample code for vaa3d plugin
% Zhihao Zheng 10/2015
% zhihaozh@brandeis.edu
function result = vaa3d_trace3D(raw,unit_bytes,x,y,z,t,para,fileDir)
p1 = para(1);
p2 = para(2);
p3 = para(3);
swcOutputDir = [fileDir , '_sample.swc']
raw = double(raw);
unit_bytes = double(unit_bytes);
x = double(x)... |
github | hbtang/sim-calib-map-3d-matlab-master | SolveJointOptVSlam.m | .m | sim-calib-map-3d-matlab-master/@ClassSolverSlam/SolveJointOptVSlam.m | 14,827 | utf_8 | 3e588e3d41d008284f690e29b1040f38 | function SolveJointOptVSlam(this, measure, calib, map, options)
%% init
if nargin < 5
options = [];
end
if ~isfield(options, 'bCalibExtRot')
options.bCalibExtRot = true;
end
if ~isfield(options, 'bCalibExtLin')
options.bCalibExtLin = true;
end
if ~isfield(options, 'bCalibTmp')
options.bCalibTmp = tru... |
github | hbtang/sim-calib-map-3d-matlab-master | SolveInitGuo.m | .m | sim-calib-map-3d-matlab-master/@ClassSolverSlam/SolveInitGuo.m | 4,858 | utf_8 | 41c43c6c979ff22c118d2900c669d296 | function SolveInitGuo( this, measure, calib )
%SOLVEINITGUO init calibration with linear constraints follows Guo's
%solution
disp('Init: VO based method ...');
%% build constraints
odo = measure.odo;
mk = measure.mk;
if isfield(this.setting.solver, 'init_thresh_locallp')
threshLpLocal = this.setting.solver.init... |
github | hbtang/sim-calib-map-3d-matlab-master | SolveJointOptMSlam.m | .m | sim-calib-map-3d-matlab-master/@ClassSolverSlam/SolveJointOptMSlam.m | 10,653 | utf_8 | 753ed840731e56c67121f984b215fde7 | function SolveJointOptMSlam(this, measure, calib, map, options)
%% init
if nargin < 5
options = [];
end
if ~isfield(options, 'bCalibExtRot')
options.bCalibExtRot = true;
end
if ~isfield(options, 'bCalibExtLin')
options.bCalibExtLin = true;
end
if ~isfield(options, 'bCalibTmp')
options.bCalibTmp = tru... |
github | hbtang/sim-calib-map-3d-matlab-master | gui.m | .m | sim-calib-map-3d-matlab-master/old/graphic/gui.m | 4,435 | utf_8 | 752beee0c61366a01757c70b9e48a3e0 | function varargout = gui(varargin)
% GUI MATLAB code for gui.fig
% GUI, by itself, creates a new GUI or raises the existing
% singleton*.
%
% H = GUI returns the handle to a new GUI or the handle to
% the existing singleton*.
%
% GUI('CALLBACK',hObject,eventData,handles,...) calls the local
% ... |
github | hbtang/sim-calib-map-3d-matlab-master | mergeimports.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/mergeimports.m | 5,211 | utf_8 | 4da2dd097dd2a6bc8760a552a3772599 | %==========================================================================
% Walks through a tree structure data. Whenever it finds a structure, which
% have field named 'import' it assumes that in that field is a cell array
% and merges all structures found in that array. Parameter verb is used for
% debugging purpos... |
github | hbtang/sim-calib-map-3d-matlab-master | ReadYamlRaw.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/ReadYamlRaw.m | 7,855 | utf_8 | 08547bee9155d85872d5c3aa02188c11 | %==========================================================================
% Reads YAML file, converts YAML sequences to MATLAB cell columns and YAML
% mappings to MATLAB structs
%
% filename ... name of yaml file to be imported
% verbose ... verbosity level (0 or absent = no messages,
% ... |
github | hbtang/sim-calib-map-3d-matlab-master | makematrices.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/makematrices.m | 5,620 | utf_8 | 91bb9555a9c43e067d55d8a19d77d345 | %==========================================================================
% Recursively walks through a Matlab hierarchy and substitutes cell vectors
% by a matrix when possible.
% Specifically substitutes cell objects like
%
% {{1,2,3},{4,5,6}}
%
% by
%
% {1,2,3;4,5,6}
%
% It leaves other objects unchanged e... |
github | hbtang/sim-calib-map-3d-matlab-master | deflateimports.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/deflateimports.m | 1,778 | utf_8 | e53673892cee46273e1d082ce414e2eb | %==========================================================================
% Transforms structures:
% - import: A, B
% - import: C
% - import: D, E, F
%
% into:
% - import: A, B, C, D, F, F
%
%==========================================================================
function result = deflateimports(r)
res... |
github | hbtang/sim-calib-map-3d-matlab-master | dosubstitution.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/dosubstitution.m | 1,049 | utf_8 | e636b95c55cfbd365bef23bf26cca2e9 | %==========================================================================
%==========================================================================
function result = dosubstitution(r, dictionary)
if ~exist('dictionary','var')
dictionary = {};
end;
result = recurse(r, 0, dictionary);
end
functi... |
github | hbtang/sim-calib-map-3d-matlab-master | merge_struct.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/merge_struct.m | 1,324 | utf_8 | 598e80779e8f9b41cc46b4e653cf9c64 |
%--------------------------------------------------------------------------
% Does merge of two structures. The result is structure which is union of
% fields of p and s. If there are equal field names in p and s, fields in p
% are overwriten with their peers from s.
%
function result = merge_struct(p, s, donotmerge, ... |
github | hbtang/sim-calib-map-3d-matlab-master | datadump.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/datadump.m | 1,033 | utf_8 | 494cf2ee060b8fc4ea99610e7e8b6361 | function datadump(data)
recurse(data, 0, []);
end
function result = recurse(data, level, addit)
indent = repmat(' | ',1,level);
if iscell(data) && ~ismymatrix(data)
result = iter_cell(data, level, addit);
elseif isstruct(data)
result = iter_struct(data, level, addit);
else
f... |
github | hbtang/sim-calib-map-3d-matlab-master | ReadYaml.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/ReadYaml.m | 2,715 | utf_8 | c00de4a18624e5153181627c94f6d3c3 | %==========================================================================
% Actually reads YAML file and transforms it using several mechanisms:
%
% - Transforms mappings and lists into Matlab structs and cell arrays,
% for timestamps uses DateTime class, performs all imports (when it
% finds a struct field... |
github | hbtang/sim-calib-map-3d-matlab-master | doinheritance.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/doinheritance.m | 3,174 | utf_8 | 2a6bc392a640f0b1c1388ddc7032b751 | %==========================================================================
% Searches through some hierarchy and performs inheritance. Whenever finds
% struct field named 'parent' it tries to find all points, defined by its
% content and uses them as the struct ancestors. Example:
%
% Given:
%
% s.a.a = 1
% s.a.b ... |
github | hbtang/sim-calib-map-3d-matlab-master | WriteYaml.m | .m | sim-calib-map-3d-matlab-master/old/io/YAMLMatlab_0.4.3/WriteYaml.m | 6,739 | utf_8 | 7457702c6232fc6ccb7c1304975670f7 | %==========================================================================
% Recursively walks through a Matlab hierarchy and converts it to the
% hierarchy of java.util.ArrayListS and java.util.MapS. Then calls
% Snakeyaml to write it to a file.
%=======================================================================... |
github | camel007/caffe-yolo-face-detection-master | classification_demo.m | .m | caffe-yolo-face-detection-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | camel007/caffe-yolo-face-detection-master | BWN.m | .m | caffe-yolo-face-detection-master/matlab/Binary/BWN.m | 3,913 | utf_8 | 91caec5c1db25e93041287864dba2018 | function BWN()
clear;clc;
current_dir = pwd;
caffe_dir = '../..'; cd(caffe_dir); caffe_dir = pwd;
cd(current_dir);
addpath(fullfile(caffe_dir,'matlab'));
caffe.reset_all();
caffe.set_mode_gpu();
caffe.set_device(5);
rand('seed',0);
cifar10_train_data = load(fullfile(caffe_dir,'examples','cifar10','cifar10_train_lmdb.... |
github | ajeet-ujjwal/Character-Segmentation-of-Handwritten-Text-master | Word_Segmentation.m | .m | Character-Segmentation-of-Handwritten-Text-master/Word_Segmentation.m | 1,585 | utf_8 | 7b17df532e94245d2de9cb4b1dcfb3d0 | % WORD SEGMENTATION
function [word]=Word_Segmentation(Line)
bwword=im2bw(cell2mat(Line));%convert the image im into binary(black and white)
aword=bwword;
bword=sum(aword,1);
%%Measure lengths of all "0" regions.
measurementsword = regionprops(bword == 0, 'Area', 'PixelIdxList');
% Get indexes of ... |
github | ajeet-ujjwal/Character-Segmentation-of-Handwritten-Text-master | Binarize.m | .m | Character-Segmentation-of-Handwritten-Text-master/Binarize.m | 439 | utf_8 | c7f6442ce592119fb886b34f449c439e | % Convert RGB image to binarized image
function [ Binarized_Image ] = Binarize( Initial_Image )
if size(Initial_Image,3)==3 % RGB image %% Convert to gray scale
Initial_Image=rgb2gray(Initial_Image);
end
threshold = graythresh(Initial_Image); %% Convert to binary image
Initial_Image=~im2bw(Initial_Image,threshold);... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.