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 | ohadf/isomatch-master | RandomSwaps.m | .m | isomatch-master/RandomSwaps.m | 1,923 | utf_8 | 7d9f0889638322ee0e680ad3e8bbd006 | function [grid_permutation, obj_value] = RandomSwaps(image_dist_matrix, ...
grid_dist_matrix, ...
num_swaps, threshold)
if ~exist('threshold', 'var')
threshold = 0;
end
i... |
github | ohadf/isomatch-master | test.m | .m | isomatch-master/test.m | 1,128 | utf_8 | 494c795578aae92571086de504b1f4cd | function [] = test()
% Either supply a grid size (for a regular grid) or specific target
% locations
options = struct();
options.grid_size = [20 20];
% Uncomment to test random swaps as refinement
%options.num_swaps = 3e3;
% Generate random colors
rand_colors = rand(prod(options.grid_size), 3);
... |
github | ohadf/isomatch-master | EvaluateObjectiveFunc.m | .m | isomatch-master/EvaluateObjectiveFunc.m | 3,693 | utf_8 | f4e80da2630990a6358db94284b0c4ec | function [result, C] = EvaluateObjectiveFunc(distances1, distances2)
% distances1 and distances2 hold pair-wise distances between objects.
% Usually, distances1 will contain pair-wise distances between input
% objects (e.g. color difference between images) and distances2 will
% contain Euclidean distan... |
github | anushagj/LTE-OFDM-SYSTEM-master | fft_block.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/fft_block.m | 220 | utf_8 | 588e9380b2ab5192ef741a767937e0b3 | % This function performs fft of the symbol after the cyclic prefix has been
% removed
function output_fft=fft_block(data_without_cp)
output_fft=fft(data_without_cp,512);
output_fft=ifftshift(output_fft);
end |
github | anushagj/LTE-OFDM-SYSTEM-master | downsampling.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/downsampling.m | 349 | utf_8 | fbb69c741e45f8ea0800dba763f9d897 | %This function downsamples the data, that is removes three out of fout bits
function downsampled_data=downsampling(symbol_filtered)
size_symbol_filtered=length(symbol_filtered);
downsampled_data=zeros(size_symbol_filtered/4,1);
for iy=0:1:length(downsampled_data)-1
downsampled_data(iy+1,1)=symbol_fi... |
github | anushagj/LTE-OFDM-SYSTEM-master | upsampling.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/upsampling.m | 264 | utf_8 | 80d025397844f0cc71e3cbe729afb2bd | % This function performs upsampling by padding evry bit with 3 zero bits
function upsampled_data=upsampling(symbol_cp)
upsampled_data=zeros(1,length(symbols_cp)*4);
for i=0:1:length(symbols_cp)-1
upsampled_data(1,4*i+1)=symbols_cp(i+1);
end
end |
github | anushagj/LTE-OFDM-SYSTEM-master | cyclic_prefix.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/cyclic_prefix.m | 191 | utf_8 | c4fb63405ae83ba31fbefa20ace33793 | % This function adds the last 36 bits of the symbol to the beginning as cyclic prefix
function symbol_cp=cyclic_prefix(output_ifft)
symbol_cp=[output_ifft(477:512); output_ifft];
end |
github | anushagj/LTE-OFDM-SYSTEM-master | demodulator_QAM.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/demodulator_QAM.m | 1,401 | utf_8 | 9af0263825da7032b0898c0bfec2b569 | % This function demodulates the QAM symbol into 4 corresponding bits
function demodulated_data=demodulator_QAM(input_data)
demodulated_data=zeros(length(input_data),4);
input_data=input_data.*sqrt(10);
for i=1:length(input_data)
real_part(i)=real(input_data(i));
imag_part(i)=imag(input_data(... |
github | anushagj/LTE-OFDM-SYSTEM-master | cyclic_prefix_remove.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/cyclic_prefix_remove.m | 397 | utf_8 | 270f2393e29d21db1c613e4ef664455e | %This function removes the first 36 bits of every symbol which belong to
%the cyclic prefix
function received_ncp=cyclic_prefix_remove(downsampled_data)
received_matrix=reshape(downsampled_data,548,ceil(length(downsampled_data)/548));
size_rx=size(received_matrix);
rows=size_rx(1);
columns=size_rx(2);
... |
github | anushagj/LTE-OFDM-SYSTEM-master | image_data_receiver.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/image_data_receiver.m | 474 | utf_8 | bf23917ca2dbfbf1bb98e7b3d337af70 | % This function receives the binary data and converts it back to an image
function image_data_receiver(data_generated)
imdata_resized=reshape(data_generated,400, 400);
for i=1:1:400
for j=1:1:400
if(imdata_resized(i,j)==1)
imdata_resized(i,j)=255;
else
imdata_resized(... |
github | anushagj/LTE-OFDM-SYSTEM-master | image_data_generator.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/image_data_generator.m | 507 | utf_8 | a1f0fa40bdf3eed75df01f44cb912679 | % This function converts a grey image into binary and sends for
% transmission
function data_generated=image_data_generator()
path=pwd;
change=cd(path);
imdata=imread('\Checkered_box.jpg');
imdata=imdata(:,:,1);
disp('Image before transmitting');
pause
figure;
title('Image before transmitting');
imshow(imdata)... |
github | anushagj/LTE-OFDM-SYSTEM-master | ifft_block.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/ifft_block.m | 179 | utf_8 | 9fe31d7d6c6464c160de38d116cef99f | % This function performs iift on the mapped data
function output_ifft=ifft_block(mapped_data)
mapped_data=fftshift(mapped_data);
output_ifft=ifft(mapped_data,512);
end |
github | anushagj/LTE-OFDM-SYSTEM-master | demodulator_QPSK.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/demodulator_QPSK.m | 1,055 | utf_8 | c8db8e79520325ce7172ba8386870808 | %This function demoulates the QPSK symbol into correspondijng bits
function pilot_demodulated=demodulator_QPSK(pilot_modulated)
length_pilot_modulated=length(pilot_modulated)
length_pilot=2*length_pilot_modulated;
pilot_demodulated=zeros(1,length_pilot);
jj=1;
for kk=1:1:length(pilot_demodulated)/2
... |
github | anushagj/LTE-OFDM-SYSTEM-master | frequency_response.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/frequency_response.m | 501 | utf_8 | eef6efae2562f0cba3b661aba097ff3b | %%% Plots the frequency response %%%
function []=frequency_response(data,tit,col)
N=512;
delta_f=15*10^3; %subcarrier spacing
fs=N*delta_f; %sampling frequency
ts=1/fs; %sampling period
data_sampled=fft(data)*ts;
data_ss=fftshift(data_sampled);
len=length(data_sampled)-1;
ff... |
github | anushagj/LTE-OFDM-SYSTEM-master | time.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/time.m | 184 | utf_8 | eeb322cf4510585721fbea2572939a13 | % This function plots the time domain response
function []= time(inp,titled,col)
stem(inp,col);
title(titled);
xlabel('index');
ylabel('amplitude');
axis tight;
end |
github | anushagj/LTE-OFDM-SYSTEM-master | subcarrier_mapping.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/subcarrier_mapping.m | 482 | utf_8 | c3ac72cf09d0a85a75504e86729b66b6 | % This function maps the every 300 symbols to 300 subcarriers
function mapped_data=subcarrier_mapping(data_multiplexed)
%Zero padding to get length of new multiplexed data equal to that of
%rows*columns
%new_data_multiplexed=reshape(data_multiplexed,rows,columns);
subcarrier_data=zeros(512,1);
... |
github | anushagj/LTE-OFDM-SYSTEM-master | modulator_QPSK.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/modulator_QPSK.m | 516 | utf_8 | 297555bcf6f82cee86daa96c2b460d66 | %This function maps every two pilot bits to a QPSK symbol
function pilot_modulated=modulator_QPSK(pilot)
length_pilot=length(pilot); % length of the data stream
ip=zeros(1,floor(length_pilot/2)); % Intializing a matrix with zeros
% Gray coded Mapping
% 00 -1-j 01 -1+j 10 1-j 11-1+j
for ii=1... |
github | anushagj/LTE-OFDM-SYSTEM-master | awgnChannel.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/awgnChannel.m | 768 | utf_8 | 367bb1c77a75ad37ede94b708b0585bd | %simulates AWGN channel using SNR value
%the output of the transmit filter is passed as a parameter and the desired signal to noise ratio in decibel
function channel_Op=awgnChannel(input_matrix,snr_Db)
fs=7.68*10^6;
bw=5*10^6;
no_of_samples=2192;
power = var(abs(input_matrix)); %determing the power of t... |
github | anushagj/LTE-OFDM-SYSTEM-master | multiplexing.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/multiplexing.m | 1,169 | utf_8 | 10de2c400ea07e40d9fe6ed61a071aad | % This function multiplexes the data and the pilot bits. Five bits of
% data are followed by one bit of pilot
function data_multiplexed=multiplexing(data_modulated, pilot_modulated,each_symbol)
pilot_counter=1;
dat_counter=1;
loop_variable=length(data_modulated)+length(pilot_modulated);
if(numel(pilot_m... |
github | anushagj/LTE-OFDM-SYSTEM-master | Pilot.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/Pilot.m | 1,005 | utf_8 | 6c36298d09c1058624847ea3aa145c10 | %%% Pilot Generator %%%
function pilot_matrix=Pilot(cell_id)
% N_slots_frame=20;
% N_pilots_slot=2;
% cell_id=100;
% total_slots=N_slots_frame*N_pilots_slot;
Nc=1600;
N_CP=1; %for normal CP
x1=zeros(1,1701);
x2=zeros(1,1701);
c=zeros(1,101);
temp_matrix=zeros(1,50);
pilot_matrix=[];
x1(1)=1;% Intializing the firs... |
github | anushagj/LTE-OFDM-SYSTEM-master | demultiplexing.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/demultiplexing.m | 960 | utf_8 | 8de6e20c45e53ede972c6cb1eb1152ed | % This function multiplexes the data and the pilot bits. Five bits of
% data are followed by one bit of pilot
function [data, pilot]=demultiplexing(demapped_data,each_symbol)
pilot=[];
data=[];
pilot_counter=1;
data_counter=1;
% We have 3 cases--
% (1)When symbol is in the 1st slot
... |
github | anushagj/LTE-OFDM-SYSTEM-master | dec2bin2.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/dec2bin2.m | 541 | utf_8 | 56b555702d85422898dd499bc4ce81fb | % This function converts a decimal number to a biinary vector
function bin = dec2bin2(dec)
i=0;
p=1;
%calculate
while i == 0
if dec/2 > 0
if dec/2 ~= round(dec/2)
bin(p) = 1;
end
if dec/2 == round(dec/2)
bin(p) = 0;
end
end
if dec/2 < ... |
github | anushagj/LTE-OFDM-SYSTEM-master | modulator_QAM.m | .m | LTE-OFDM-SYSTEM-master/OFDM_FINAL/modulator_QAM.m | 1,665 | utf_8 | 0cfd2aafd8421fc6e5848f20224718e9 | % This function performs mapping of every 4 data bits into one QAM symbol
function data_modulated=modulator_QAM(data_generated)
temp_matrix=zeros(ceil(length(data_generated)/4),4);
size_matrix=size(temp_matrix);
data_counter=1;
for m=1:1:size_matrix(1)
for n=1:1:size_matrix(2)
temp_m... |
github | joduss/Appspy-master | setDateAxes.m | .m | Appspy-master/data-collected/data-processing/dynamicDateTicks/setDateAxes.m | 3,722 | utf_8 | 097bf3e833eb2c95cc78f6f76630eb32 | function varargout = setDateAxes(varargin)
% setDateAxes is a convenience function that allows you to programmatically
% set properties of axes that contain dates and automatically update the
% date ticks. This function should be used in lieu of SET for date axes.
%
% This function is intended to be used after an ... |
github | joduss/Appspy-master | test_sqlite3.m | .m | Appspy-master/data-collected/data-processing/matlab-sqlite3-driver-master/test/test_sqlite3.m | 1,905 | utf_8 | 1a7d070e698f6cc66757560b3923ea95 | function test_sqlite3
%TEST_SQLITE3 Test the functionality of the sqlite3 driver.
tests = {@test_functional_1, @test_functional_2, @test_functional_3};
for i = 1:numel(tests)
try
tests{i}();
fprintf('PASS: %s\n', func2str(tests{i}));
catch e
fprintf('FAIL: %s\n', func2str(tests{i}));
... |
github | joduss/Appspy-master | benchmarkSQLite3.m | .m | Appspy-master/data-collected/data-processing/matlab-sqlite3-driver-master/test/benchmarkSQLite3.m | 1,307 | utf_8 | 016705f8b8b484822d16673427eb4eb6 | function benchmarkSQLite3
%BENCHMARKSQLITE3 Benchmark the performance.
tests = { ...
@benchmark1 ...
};
for i = 1:numel(tests)
try
fprintf('%s\n', func2str(tests{i}));
tests{i}();
catch e
fprintf('%s\n', e.getReport);
end
end
end
function time = measureTime(function_handle, ... |
github | joduss/Appspy-master | make.m | .m | Appspy-master/data-collected/data-processing/matlab-sqlite3-driver-master/+sqlite3/make.m | 941 | utf_8 | cbcdc517e51c69553394f78fd09faeca | function make(action, varargin)
%MAKE Build a driver mex file.
if nargin < 1
action = 'all';
end
switch action
case 'all'
options = '';
if isunix() && ~ismac()
options = ' -ldl -lboost_regex';
end
dispAndEval('mex -c -Iinclude src/sqlite3/sqlite3.c -outdir src/sqlite3');
... |
github | menpo/menpobench-master | yzt_iccv_2013.m | .m | menpobench-master/menpobench/predefined/trainable_method/yzt_iccv_2013.m | 6,078 | utf_8 | a7e31943bda482e6fd3683adfd1ba8e9 | function funcs = menpobench_namespace()
% Use a struct in matlab to simulate a Python namespace
funcs.train = @train;
funcs.setup = @setup;
funcs.fit = @fit;
end
%% Fill in the functions below. These functions are then wired up into a struct
% above to simulate a Python namespace. There are three func... |
github | menpo/menpobench-master | menpobench_addpath_recurse.m | .m | menpobench-master/menpobench/method/matlab/menpobench_addpath_recurse.m | 8,685 | utf_8 | 8482f8633333cad2a073b71be5c78c98 | function menpobench_addpath_recurse(strStartDir, caStrsIgnoreDirs, strXorIntAddpathMode, blnRemDirs, blnDebug)
%ADDPATH_RECURSE Adds (or removes) the specified directory and its subfolders
% addpath_recurse(strStartDir, caStrsIgnoreDirs, strXorIntAddpathMode, blnRemDirs, blnDebug)
%
% By default, all hidden direct... |
github | bjornph/lsd_files-master | absor.m | .m | lsd_files-master/absor.m | 7,168 | utf_8 | e01247bc07f3aa28780a4d6a89e68943 | function [regParams,Bfit,ErrorStats]=absor(A,B,varargin)
%ABSOR - a tool for solving the absolute orientation problem using Horn's
%quaternion-based method, that is, for finding the rotation, translation, and
%optionally also the scaling, that best maps one collection of point coordinates
%to another in a least s... |
github | ISCAS007/backgroundDetector-master | ShowStaticMotion_pic3.m | .m | backgroundDetector-master/ShowStaticMotion_pic3.m | 1,697 | utf_8 | 3865aa31980b983cd0ef5bf8cd054ec4 | function ShowStaticMotion_pic3()
datatype={'baseline-highway','dynamicBackground-boats'};
len=length(datatype);
close all;
for i=1:len
matname=[datatype{i},'.mat']
data=load(matname);
showmat(data,matname,i);
end
for i=1:len
h=figure(i);
saveas(h,[datatype{i},'-Sphere'],'jpg');
% print(h,'-djpeg'... |
github | ISCAS007/backgroundDetector-master | BS_picFrame_yzbx.m | .m | backgroundDetector-master/BS_picFrame_yzbx.m | 18,178 | utf_8 | 68fb1352e4742f26260c4a381b02dc44 | %base function from matlab
%use pic frame as input, compare to BS_BaseFunction_yzbx.m
function BS_picFrame_yzbx()
% create system objects used for reading video, detecting moving objects,
% and displaying the results
obj = setupSystemObjects();
tracks = initializeTracks(); % create an empty array of tracks
... |
github | ISCAS007/backgroundDetector-master | ReverseMatching.m | .m | backgroundDetector-master/ReverseMatching.m | 4,973 | utf_8 | c198231da33410f1231850f6f1e8896b | function layer=ReverseMatching(root)
% reverse Matching and reverse learn by groundtruth.
% global var ***************
roiframeNum=load([root,'\temporalROI.txt']);
pathlist3=dir([root,'\input']);
filenamelist3={pathlist3.name};
pathlist4=dir([root,'\groundtruth']);
filenamelist4={pathlist4.name};
inpu... |
github | ISCAS007/backgroundDetector-master | layer_All_yzbx.m | .m | backgroundDetector-master/layer_All_yzbx.m | 11,358 | utf_8 | 3b045a03c34aefe64ce4cc20c959a9f1 | function layer_All_yzbx()
% layerUpdate_yzbx()
% tmp3()-->getVecgapMask()
% ...... find in lyaerUpdate_yzbx()
% load data from the .mat file extracted by function dataExtract
% run algrithm to fit the data
root='D:\firefoxDownload\matlab\dataset2012\dataset';
% layernum=3;
pathlist1=dir(root);
filenum1=lengt... |
github | ISCAS007/backgroundDetector-master | layerUpdate_yzbx.m | .m | backgroundDetector-master/layerUpdate_yzbx.m | 6,166 | utf_8 | 358004fc773b6bc51f93ac79956c632d | function layer=layerUpdate_yzbx(layer,frame)
frameNum=layer.frameNum;
[a,b,c]=size(frame);
areaThreshold=round(a*b/1000);
learnRate=layer.a;
%%%%%%%%%%%%%%%%%%%%%%%%gap update
if(frameNum==1)
dif1=max(double(frame)-layer.max,layer.min-double(frame));
minarea=areaThersh... |
github | ISCAS007/backgroundDetector-master | BS_BaseFunction_yzbx.m | .m | backgroundDetector-master/BS_BaseFunction_yzbx.m | 19,960 | utf_8 | 57b6ae4023c76fcee96745f5302df9b1 | %% Motion-Based Multiple Object Tracking
% This example shows how to perform automatic detection and motion-based
% tracking of moving objects in a video from a stationary camera.
%
% Copyright 2012 The MathWorks, Inc.
%%
% Detection of moving objects and motion-based tracking are important
% components of ma... |
github | ISCAS007/backgroundDetector-master | getVecgapMask.m | .m | backgroundDetector-master/getVecgapMask.m | 886 | utf_8 | b8a78ea03283969d2c64350920ef567b | function [mask,vecdif]=getVecgapMask(layer,frame)
layermean=layer.mean;
layermean=norm_yzbx(layermean);
ff=norm_yzbx(frame);
vecgap=layer.vecgap;
% layerlight=sqrt(max(sum(layermean.^2,3),1));
% framelight=sqrt(max(sum(frame.^2,3),1));
% ff=double(frame);
% for i=3:-1:1
% % layermean(:,:,i)=layer.mean(:... |
github | ISCAS007/backgroundDetector-master | ShowRGBPlus_pic4.m | .m | backgroundDetector-master/ShowRGBPlus_pic4.m | 1,664 | utf_8 | 26304d5276afa8869dd64ff00d4ceece | function ShowRGBPlus_pic4()
datatype={'dynamicBackground-boats'};
len=length(datatype);
close all;
for i=1:len
matname=[datatype{i},'.mat']
data=load(matname);
showmat(data,matname,i*2);
end
for i=1:len
h=figure(2*i);
saveas(h,[datatype{i},'-RGBPlus1'],'jpg');
h=figure(2*i+1);
saveas(h,[datatype{... |
github | ISCAS007/backgroundDetector-master | datafit.m | .m | backgroundDetector-master/datafit.m | 6,615 | utf_8 | 42c03d7a22d7b610a7dab0fca68f7a5e | function datafit()
% load data from the .mat file extracted by function dataExtract
% run algrithm to fit the data
root='D:\firefoxDownload\matlab\dataset2012\dataset';
% layernum=3;
pathlist1=dir(root);
filenum1=length(pathlist1);
filenamelist1={pathlist1.name};
layers={};
layers(8,8)={10};
hits=zeros(8,8,... |
github | ISCAS007/backgroundDetector-master | localWave.m | .m | backgroundDetector-master/localWave.m | 12,876 | utf_8 | 7b11a5fda7123f367ba0bce65f2623f9 | <<<<<<< HEAD
function localWave()
% root='D:\firefoxDownload\matlab\dataset2012\dataset\shadow\bungalows';
% root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\fall';
root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats';
roi=load([root,'\temporalROI.txt']);
motionK=getMotionK... |
github | ISCAS007/backgroundDetector-master | baseFunction_yzbx.m | .m | backgroundDetector-master/baseFunction_yzbx.m | 8,923 | utf_8 | 64902808aba928e5767de499f25eb13d | %use framedif to detect backgroud
%write by yzbx
function baseFunction_yzbx()
%init
frameNum=0;
filepath='D:\firefoxDownload\matlab\dataset2014\dataset\dynamicBackground\boats\input';
filelist=dir(filepath);
filenum=length(filelist)-2;
filename={filelist.name};
colorTransform = makecform('srgb2lab');
frame=... |
github | ISCAS007/backgroundDetector-master | ShowFrameDif_pic5.m | .m | backgroundDetector-master/ShowFrameDif_pic5.m | 1,598 | utf_8 | e235b7eae8a9e2b37b0d314b28e7ac5f | function ShowRGBPlus_pic4()
datatype={'dynamicBackground-boats'};
len=length(datatype);
close all;
for i=1:len
matname=[datatype{i},'.mat']
data=load(matname);
showmat(data,matname,i);
end
for i=1:len
h=figure(i);
saveas(h,[datatype{i},'-FrameDifference'],'jpg');
end
function showmat(data,matname,i)
r... |
github | ISCAS007/backgroundDetector-master | baseFunction_evaluation_yzbx.m | .m | backgroundDetector-master/baseFunction_evaluation_yzbx.m | 2,739 | utf_8 | c936ba19db7ff28bc819a1f38fa6b5a3 | %use layer to detect backgroud
%write by yzbx
%the detection function change to point-wise, not region-wise;
function baseFunction_evaluation_yzbx()
%init
frameNum=0;
filepath='E:\yzbx_programe\Matlab\Data\boats\input';
otherpath='E:\yzbx_programe\Matlab\Data\boats\groundtruth';
filelist=dir(filepath);
other... |
github | ISCAS007/backgroundDetector-master | dataAnalyze.m | .m | backgroundDetector-master/dataAnalyze.m | 10,248 | utf_8 | 484c7457717b4db4bd389f8a6f05f60e | %拟合分析根目录dataset2014,dataset2012下的所有数据
% dataset2014 包含dataset2012, 但新加的视频类groundtruth只提供前面一半
% groundtruth 有5类
% outside roi=85,unknown=170,motion=255,hard shadow=50,static=0
% 突然停止的目标将逐渐融入背景
function dataAnalyze()
% root='D:\firefoxDownload\matlab\dataset2012\dataset';
root='D:\Program\matlab\dataset2012\datase... |
github | ISCAS007/backgroundDetector-master | run.m | .m | backgroundDetector-master/run.m | 2,192 | utf_8 | 67b3435aeb52078e00bfa6b29a50ebd5 | % inputpath='D:\firefoxDownload\matlab';
% % D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats\input
% filename='dataset2012\dataset\dynamicBackground\boats';
% outputpath=strrep(filename,'\','.');
% layerAlgrithm([inputpath,'\',filename],['analyze\',outputpath,'.mat']);
function run()
root='D... |
github | ISCAS007/backgroundDetector-master | baseFunction_analayze_yzbx.m | .m | backgroundDetector-master/baseFunction_analayze_yzbx.m | 1,336 | utf_8 | 513e90fb6ea41fe5d55bf70beba44b0c | %use framedif to detect backgroud
%write by yzbx
function baseFunction_analayze_yzbx()
%init
frameNum=0;
filepath='D:\firefoxDownload\matlab\dataset2014\dataset\dynamicBackground\boats\input';
filelist=dir(filepath);
filenum=length(filelist)-2;
filename={filelist.name};
colorTransform = makecform('srgb2lab')... |
github | ISCAS007/backgroundDetector-master | dataset2012.m | .m | backgroundDetector-master/dataset2012.m | 4,989 | utf_8 | 4276cacb20be90617c7281321fd2a57c | function dataset2012()
% 对数据集dataset2012进行遍历的标准设置
root='D:\firefoxDownload\matlab\dataset2012\dataset';
% layernum=3;
pathlist1=dir(root);
filenum1=length(pathlist1);
filenamelist1={pathlist1.name};
for i=7:filenum1
% if(i<6)
% continue;
% end
pathlist2=dir([root,'\',filenameli... |
github | ISCAS007/backgroundDetector-master | ShowDynamicBackground_pic7.m | .m | backgroundDetector-master/ShowDynamicBackground_pic7.m | 3,083 | utf_8 | 5b98862eb6f66adbe5483db0d68bace4 | function ShowDynamicBackground_pic7()
root='/media/yzbx/Windows7_OS/ComputerVision/Dataset/dataset';
% datatype={'dynamicBackground'};
% subtype={'boats','canoe','fall','overpass','fountain01','fountain02'};
datatype={'shadow'};
subtype={'bungalows'};
% subtype={'backdoor','bungalows','busStation','copyMachine','cubic... |
github | ISCAS007/backgroundDetector-master | layerAlgrithm.m | .m | backgroundDetector-master/layerAlgrithm.m | 2,375 | utf_8 | 17e91e2b699498e61a1aba160bd80391 | %use layer to detect backgroud
%write by yzbx
%the detection function change to point-wise, not region-wise;
function layerAlgrithm(inputpath,outputpath)
%init
% filepath='E:\yzbx_programe\Matlab\Data\boats\input';
filepath=[inputpath,'\','input'];
% ROIbmp=imread([inputpath,'\ROI.bmp']);
ROIframeNum=load([... |
github | ISCAS007/backgroundDetector-master | dataExtract.m | .m | backgroundDetector-master/dataExtract.m | 3,692 | utf_8 | 646fd615ae24688317622665598ea70f | %拟合分析根目录dataset2014,dataset2012下的所有数据
% dataset2014 包含dataset2012, 但新加的视频类groundtruth只提供前面一半
% groundtruth 有5类
% outside roi=85,unknown=170,motion=255,hard shadow=50,static=0
% 突然停止的目标将逐渐融入背景
function dataExtract()
% windows
% root='D:\firefoxDownload\matlab\dataset2012\dataset';
% linux
% root='/media/yzbx/... |
github | ISCAS007/backgroundDetector-master | edgeAnalyse.m | .m | backgroundDetector-master/edgeAnalyse.m | 6,460 | utf_8 | 97479c0c98e55d6a4f8d1ea377fde02c | <<<<<<< HEAD
function edgeAnalyse()
% D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\overpass
root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\overpass';
roi=load([root,'\temporalROI.txt']);
motionK=getMotionK();
h=figure;
imshow(motionK);
saveas(h,'edgeAnalyse','bmp');
close(h);
... |
github | ISCAS007/backgroundDetector-master | baseFunction3_yzbx.m | .m | backgroundDetector-master/baseFunction3_yzbx.m | 9,771 | utf_8 | 8bc073e85ed0c456790751a7e4777c69 | %use framedif to detect backgroud
%write by yzbx
%the detection function change to point-wise, not region-wise;
function baseFunction3_yzbx()
%init
frameNum=1800;
% filepath='E:\yzbx_programe\Matlab\Data\boats\input';
% otherpath='E:\yzbx_programe\Matlab\Data\boats\groundtruth';
filepath='D:\firefoxDownload\m... |
github | ISCAS007/backgroundDetector-master | get_point_info.m | .m | backgroundDetector-master/get_point_info.m | 1,321 | utf_8 | ab42f8fcab0c24556d6eae67dc9a7380 | %use framedif to detect backgroud
%write by yzbx
function record=get_point_info(pos,pathname,maxfilenum)
%init
frameNum=0;
filelist=dir(pathname);
filenum=length(filelist)-2;
filenum=min(filenum,maxfilenum);
filename={filelist.name};
% colorTransform = makecform('srgb2lab');
frame=getNextFrame();
[width,he... |
github | ISCAS007/backgroundDetector-master | baseFunction4_yzbx.m | .m | backgroundDetector-master/baseFunction4_yzbx.m | 2,781 | utf_8 | 90b91739aa7085346e34d102b76d8236 | %use layer to detect backgroud
%write by yzbx
%the detection function change to point-wise, not region-wise;
function baseFunction4_yzbx()
%init
frameNum=0;
filepath='E:\yzbx_programe\Matlab\Data\boats\input';
otherpath='E:\yzbx_programe\Matlab\Data\boats\groundtruth';
if(size(dir(filepath),1)==0)
filepa... |
github | ISCAS007/backgroundDetector-master | codebook2.m | .m | backgroundDetector-master/codebook2.m | 6,698 | utf_8 | 05d79df809dee6543bed298bcee46650 | function mask=codebook2()
frameNum=0;
% filepath='D:\firefoxDownload\matlab\dataset2014\dataset\dynamicBackground\boats\input';
filepath='D:\firefoxDownload\matlab\dataset2014\dataset\baseline\highway\input';
filelist=dir(filepath);
filenum=length(filelist)-2;
filename={filelist.name};
frame=getNextFrame();
[wi... |
github | ISCAS007/backgroundDetector-master | ShowRGB_pic2.m | .m | backgroundDetector-master/ShowRGB_pic2.m | 1,386 | utf_8 | cd786786baebfb666c407dcfccc35d6b | function ShowRGB_pic2()
datatype={'baseline-highway','dynamicBackground-boats'};
len=length(datatype);
close all;
for i=1:len
matname=[datatype{i},'.mat']
data=load(matname);
showmat(data,matname,i);
end
for i=1:len
h=figure(i);
saveas(h,[datatype{i},'-RGB'],'jpg');
% print(h,'-djpeg','-r300',[da... |
github | ISCAS007/backgroundDetector-master | codebook.m | .m | backgroundDetector-master/codebook.m | 5,426 | utf_8 | 8705b6adbd002ac51b1a87fb51087ad3 | function mask=codebook()
frameNum=0;
% filepath='D:\firefoxDownload\matlab\dataset2014\dataset\dynamicBackground\boats\input';
filepath='D:\firefoxDownload\matlab\dataset2014\dataset\baseline\highway\input';
filelist=dir(filepath);
filenum=length(filelist)-2;
filename={filelist.name};
frame=getNextFrame();
[wid... |
github | ISCAS007/backgroundDetector-master | mixtureSubstractionTest.m | .m | backgroundDetector-master/mixtureSubstractionTest.m | 2,177 | utf_8 | ae6253724f1cc77b6e7fc914b92b775f | % inputpath='D:\firefoxDownload\matlab';
% % D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats\input
% filename='dataset2012\dataset\dynamicBackground\boats';
% outputpath=strrep(filename,'\','.');
% layerAlgrithm([inputpath,'\',filename],['analyze\',outputpath,'.mat']);
function mixtureSubstra... |
github | ISCAS007/backgroundDetector-master | dataAnalyze_run.m | .m | backgroundDetector-master/dataAnalyze_run.m | 4,500 | utf_8 | 68e58d8b92cbf6791cc3715982afbac5 | %拟合分析根目录dataset2014,dataset2012下的所有数据
% dataset2014 包含dataset2012, 但新加的视频类groundtruth只提供前面一半
% groundtruth 有5类
% outside roi=85,unknown=170,motion=255,hard shadow=50,static=0
% 突然停止的目标将逐渐融入背景
% % % 严重有问题，各种问题，rgb的值不对。。。！
function dataAnalyze_run()
% root='D:\firefoxDownload\matlab\dataset2012\dataset';
root='... |
github | ISCAS007/backgroundDetector-master | ShowStaticGray_pic1.m | .m | backgroundDetector-master/ShowStaticGray_pic1.m | 1,563 | utf_8 | bc5c3543b131c89b1f5ce5f35ec53b0a | function ShowStaticGray_pic1()
datatype='baseline';
datasubtype={'highway','office','pedestrians','PETS2006'};
imagetype={'scatter','hist','plot'};
close all;
for i=1:4
for j=1:3
matname=[datatype,'-',datasubtype{i},'.mat']
data=load(matname);
showmat(data,matname,i,j);
end
end
for j=1:3
h... |
github | ISCAS007/backgroundDetector-master | ShowStaticGray.m | .m | backgroundDetector-master/ShowStaticGray.m | 2,078 | utf_8 | 9e8e500cb7089bf1a1a431e618330f94 | function ShowStaticGray()
% windows
% root='D:\firefoxDownload\matlab\dataset2012\dataset';
% linux
% root='/media/yzbx/Windows7_OS/ComputerVision/Dataset/dataset';
datacfg
pathlist1=dir(root);
filenum1=length(pathlist1);
filenamelist1={pathlist1.name};
for i=3:filenum1
% if(i~=6)
% continue;
% end
... |
github | ISCAS007/backgroundDetector-master | baseFunction2_yzbx.m | .m | backgroundDetector-master/baseFunction2_yzbx.m | 7,425 | utf_8 | 8421f96cc8553064310d7ca049f50dbb | %use framedif to detect backgroud
%write by yzbx
%the detection function change to point-wise, not region-wise;
function baseFunction2_yzbx()
%init
frameNum=0;
filepath='D:\firefoxDownload\matlab\dataset2014\dataset\dynamicBackground\boats\input';
filelist=dir(filepath);
filenum=length(filelist)-2;
filename=... |
github | ISCAS007/backgroundDetector-master | bgs_seven.m | .m | backgroundDetector-master/opticalFlow/bgs_seven.m | 3,432 | utf_8 | 104eefc15cb0e299ddd2c2ed9314120a | ## Copyright (C) 2015 yzbx
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 3 of the License, or
## (at your option) any later version.
##
## This program is distrib... |
github | ISCAS007/backgroundDetector-master | readPathPic.m | .m | backgroundDetector-master/visulization/readPathPic.m | 3,352 | utf_8 | bf408ca0f619a80237153410bbaa6f4b | % [I,map,alpha] = imread('im.png');
% h = imshow(I);
% set(h,'AlphaData',alpha)
function readPathPic()
% loadpath();
data=load('path.mat');
pathdata=data.pathdata;
figure,imshow(path2mask(pathdata(1)));
figure,imshow(path2mask(pathdata(2)));
figure,imshow(path2mask(pathlinke... |
github | ISCAS007/backgroundDetector-master | yzbx.m | .m | backgroundDetector-master/subsense/yzbx.m | 1,615 | utf_8 | 13616515698f8e1a8ca1d710841caf1f | function yzbx()
frameNum=6900;
% model is background
% 0,50=background, 170,255=foreground, 85=out roi
input1=getInput(frameNum-1);
[height,width,channel]=size(input1);
model=subsensePlusOpticalFlow();
for i=1:300
tic;
disp(['frameNum=',num2str(frameNum)]);
input=getInput(frameNum);
foreground=getForeground(fra... |
github | ISCAS007/backgroundDetector-master | opticalFlow.m | .m | backgroundDetector-master/subsense/opticalFlow.m | 267 | utf_8 | cfefdc24e0544c9f8717cb47d7cdef10 | function [vx,vy]=opticalFlow(input1,input2)
[vx,vy]=getVxVy(input1,input2);
end
function [ux,uy]=getVxVy(input0,input)
im1=double(rgb2gray(input0))/256.0;
im2=double(rgb2gray(input))/256.0;
winSize = 21;
[ux, uy, l1, l2] = LucasKanade(im1, im2, winSize);
end |
github | ISCAS007/backgroundDetector-master | select.m | .m | backgroundDetector-master/tracking/select.m | 672 | utf_8 | 17602a1b59e64368fcef65761311600a | % Adam Kukucka
% Zach Clay
% Marcelo Molina
% CSE 486 Project 3
function [ cmin, cmax, rmin, rmax ] = select( I )
%UNTITLED1 Summary of this function goes here
% Detailed explanation goes here
% for array... x is cols, y is rows
image(I);
k = waitforbuttonpress;
point1 = get(gca,'CurrentPoint'); %... |
github | ISCAS007/backgroundDetector-master | camshift.m | .m | backgroundDetector-master/tracking/camshift.m | 5,928 | utf_8 | 7d7fa7af1f94e56567008880c47af281 | % Adam Kukucka
% Zach Clay
% Marcelo Molina
% CSE 486 Project 3
function [ trackmov probmov centers ] = camshift
% ******************************************************************
% initialize vari ables
% ******************************************************************
rmin = 0; %min row value... |
github | ISCAS007/backgroundDetector-master | meanshift.m | .m | backgroundDetector-master/tracking/meanshift.m | 1,328 | utf_8 | 4a23eb33df7946627d9f2ea5ad309e55 | % Adam Kukucka
% Zach Clay
% Marcelo Molina
% CSE 486 Project 3
function [ rowcenter colcenter M00 ] = meanshift(I, rmin, rmax, cmin,...
cmax, probmap)
%inputs
% rmin, rmax, cmin, cmax are the coordiantes of the window
% I is the image
%outputs
% colcenter rowcenter are the new center coordina... |
github | ISCAS007/backgroundDetector-master | processVideoFolder.m | .m | backgroundDetector-master/CDNet/processVideoFolder.m | 3,676 | utf_8 | 127033bf6571423c78e0eeb3d83f0b5a | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | Stats.m | .m | backgroundDetector-master/CDNet/Stats.m | 6,730 | utf_8 | 1b45102a2d483441801fa326bf137458 | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | processFolder.m | .m | backgroundDetector-master/CDNet/processFolder.m | 2,185 | utf_8 | 9bb3b54dadab19379b5a5c617bb7027c | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | mixtureSubstraction3_run.m | .m | backgroundDetector-master/CDNet/mixtureSubstraction3_run.m | 2,262 | utf_8 | cac8c99c5ccf290d7d7011128dda1ea0 | % inputpath='D:\firefoxDownload\matlab';
% % D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats\input
% filename='dataset2012\dataset\dynamicBackground\boats';
% outputpath=strrep(filename,'\','.');
% layerAlgrithm([inputpath,'\',filename],['analyze\',outputpath,'.mat']);
function mixtureSubstra... |
github | ISCAS007/backgroundDetector-master | filesys.m | .m | backgroundDetector-master/CDNet/filesys.m | 2,131 | utf_8 | 666c247369d2f4e18c5cea8af54af4bf | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | difModel_run.m | .m | backgroundDetector-master/CDNet/difModel_run.m | 2,273 | utf_8 | cd064e2409947d4babe043e2cf2ca22f | % inputpath='D:\firefoxDownload\matlab';
% % D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats\input
% filename='dataset2012\dataset\dynamicBackground\boats';
% outputpath=strrep(filename,'\','.');
% layerAlgrithm([inputpath,'\',filename],['analyze\',outputpath,'.mat']);
function difModel_run()... |
github | ISCAS007/backgroundDetector-master | processVideoFolder.m | .m | backgroundDetector-master/CDNet/MatlabCode2012/matlab/processVideoFolder.m | 4,201 | utf_8 | 61970bc1777eac103fe2b555dfcbbaa3 | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | Stats.m | .m | backgroundDetector-master/CDNet/MatlabCode2012/matlab/Stats.m | 6,730 | utf_8 | 1b45102a2d483441801fa326bf137458 | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | processFolder.m | .m | backgroundDetector-master/CDNet/MatlabCode2012/matlab/processFolder.m | 2,450 | utf_8 | 203d864d5c6cfe58f288298ac4a32e6f | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | filesys.m | .m | backgroundDetector-master/CDNet/MatlabCode2012/matlab/filesys.m | 2,131 | utf_8 | 666c247369d2f4e18c5cea8af54af4bf | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | parameterOptimal.m | .m | backgroundDetector-master/CDNet/MatlabCode2012/matlab/parameterOptimal.m | 9,870 | utf_8 | f58a7c244caf94f26decacc135c43358 | function OptParam=parameterOptimal()
% inputPath: input path
% groundtruePath: groundtrue path
% resultPath: restore the result
% inputPath,groundtruePath,resultPath
countMax=10:20;
floatValue=3:10;
path='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\fall';
resultPath='E:\yzbx_programe\Matla... |
github | ISCAS007/backgroundDetector-master | maxmin_bgs_run.m | .m | backgroundDetector-master/CDNet/maxmin/maxmin_bgs_run.m | 2,199 | utf_8 | 7f644c0eb6dee4f4eec78622587580a4 | %% base on subsenseErrorShow
function maxmin_bgs_run()
root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats';
resultPath='E:\matlab\subsense\results\dynamicBackground\boats\';
roiImg=imread([root,'\ROI.bmp']);
roiMask=(roiImg~=0);
[height,width]=size(roiMask);
fp=zeros(height,width);
... |
github | ISCAS007/backgroundDetector-master | svmBgs1.m | .m | backgroundDetector-master/CDNet/SVM/svmBgs1/svmBgs1.m | 9,394 | utf_8 | 746b4017663349cfd68b897465541f78 | function [mask,kernel]=svmBgs1(input,kernel)
[mask,kernel]=basicBgs(input,kernel);
mask=bwareaopen(mask,20);
[mask,kernel]=svmBgs(input,mask,kernel,200);
kernel=updateKernel(mask,kernel);
fprintf('frameNum is %d \n',kernel.frameNum);
end
function [mask,kernel]=basicBgs(input,kernel)
[a,b,c]=size(input);
if(i... |
github | ISCAS007/backgroundDetector-master | bgslibrary.m | .m | backgroundDetector-master/CDNet/SVM/svmBgs3/bgslibrary.m | 3,283 | utf_8 | 1f3e608a10c1f23ad67753e71a14507c | function [mask,kernel]=bgslibrary(input,kernel)
end
function [kernel]=bgslibraryUpdate(input,mask,kernel)
end
function [mask,kernel]=frameDif(input,kernel)
%copy from E:\yzbx_programe\Matlab\gmm\backgroundDetector\CDNet\difModel.m
% init and update layer at the same time
[a,b,c]=size(input);
... |
github | ISCAS007/backgroundDetector-master | PBASErrorShow.m | .m | backgroundDetector-master/CDNet/SVM/svmBgs3/PBASErrorShow.m | 1,721 | utf_8 | d0065e683f89a4b78a72259d52b6b863 | function PBASErrorShow()
root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats';
resultPath='E:\matlab\subsense\results\dynamicBackground\boats\';
roiImg=imread([root,'\ROI.bmp']);
roiMask=(roiImg~=0);
[height,width]=size(roiMask);
fp=zeros(height,width);
fn=zeros(height,width);
grou... |
github | ISCAS007/backgroundDetector-master | subsenseErrorShow.m | .m | backgroundDetector-master/CDNet/SVM/svmBgs3/subsenseErrorShow.m | 1,888 | utf_8 | ee6005fb2a103c8617ea8fe22c8461ba | function subsenseErrorShow()
root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats';
resultPath='E:\matlab\subsense\results\dynamicBackground\boats\';
roiImg=imread([root,'\ROI.bmp']);
roiMask=(roiImg~=0);
[height,width]=size(roiMask);
fp=zeros(height,width);
fn=zeros(height,width);
... |
github | ISCAS007/backgroundDetector-master | graySVMBgsTrain.m | .m | backgroundDetector-master/CDNet/SVM/svmBgs2/graySVMBgsTrain.m | 10,133 | utf_8 | b72ce3a7532a2975cd7f7886fb9e2fb8 | function svmModel=graySVMBgsTrain(CDNetDir,featureRootDir)
% featureGenerate(CDNetDir,featureRootDir);
svmModel=svmLearn(CDNetDir,featureRootDir);
end
function featureGenerate(CDNetDir,featureRootDir)
% use CDNet image dataset to generate svm features
% CDNetDir: the dir for CDNet dataset, eg: D:\firefoxDow... |
github | ISCAS007/backgroundDetector-master | svmBgs2.m | .m | backgroundDetector-master/CDNet/SVM/svmBgs2/svmBgs2.m | 6,860 | utf_8 | 70d185dd1e86ec42a7ac1eb2e9cc9733 | function [mask,kernel]=svmBgs2(input,kernel)
if(isempty(kernel))
kernel=struct(...
'gray',[],...
'color',[]);
end
[mask,kernel.gray]=graySVMBgs(input,kernel.gray);
mask=bwareaopen(mask,20);
if(kernel.gray.frameNum>=kernel.gray.historyNum)
[mask,kernel.color]=colorSVMBgs(input,mask,k... |
github | ISCAS007/backgroundDetector-master | colorSVMBgsTrain.m | .m | backgroundDetector-master/CDNet/SVM/svmBgs2/colorSVMBgsTrain.m | 12,007 | utf_8 | 7b9d5a2c2cb8cd949f3dfcccaec9f9a0 | function svmModel=colorSVMBgsTrain(CDNetDir,featureRootDir)
featureGenerate(CDNetDir,featureRootDir);
svmModel=svmLearn(CDNetDir,featureRootDir);
end
function featureGenerate(CDNetDir,featureRootDir)
% use CDNet image dataset to generate svm features
% CDNetDir: the dir for CDNet dataset, eg: D:\firefox... |
github | ISCAS007/backgroundDetector-master | bgs_sigma.m | .m | backgroundDetector-master/CDNet/sigma/bgs_sigma.m | 560 | utf_8 | d43c3164dec97ff757d001739fe80def | function [mask,kernel]=bgs_sigma(input,kernel)
[a,b,c]=size(input);
if(~isempty(kernel))
else
kernel=initKernel(input);
mask=zeros(a,b);
end
end
function kernel=initKernel(input)
[aa,bb,cc]=size(input);
dd=3;
kernel=struct(...
'u',zeros(aa,bb... |
github | ISCAS007/backgroundDetector-master | subsense_improve_test2.m | .m | backgroundDetector-master/CDNet/subsense/subsense_improve_test2.m | 2,602 | utf_8 | b4f6c9523e0e8a49d5e979025216378d | function subsense_improve_test2()
root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats';
resultPath='E:\matlab\subsense\results\dynamicBackground\boats\';
roiImg=imread([root,'\ROI.bmp']);
roiMask=(roiImg~=0);
[height,width]=size(roiMask);
groundTruthPath=[root,'\groundtruth\'];
inpu... |
github | ISCAS007/backgroundDetector-master | subsense_improve_test.m | .m | backgroundDetector-master/CDNet/subsense/subsense_improve_test.m | 3,150 | utf_8 | fe4d977a32b5d36c995b944fd5c09f58 | %% base on subsenseErrorShow
function subsense_improve_test()
root='D:\firefoxDownload\matlab\dataset2012\dataset\dynamicBackground\boats';
resultPath='E:\matlab\subsense\results\dynamicBackground\boats\';
roiImg=imread([root,'\ROI.bmp']);
roiMask=(roiImg~=0);
[height,width]=size(roiMask);
fp=zeros(height,wi... |
github | ISCAS007/backgroundDetector-master | processVideoFolder.m | .m | backgroundDetector-master/CDNet/MatlabCode2014/matlab/processVideoFolder.m | 4,201 | utf_8 | 61970bc1777eac103fe2b555dfcbbaa3 | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | Stats.m | .m | backgroundDetector-master/CDNet/MatlabCode2014/matlab/Stats.m | 6,730 | utf_8 | 1b45102a2d483441801fa326bf137458 | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | processFolder.m | .m | backgroundDetector-master/CDNet/MatlabCode2014/matlab/processFolder.m | 2,760 | utf_8 | b035e27a226b4a4f4c5f2ac6cc91522a | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | ISCAS007/backgroundDetector-master | filesys.m | .m | backgroundDetector-master/CDNet/MatlabCode2014/matlab/filesys.m | 2,198 | utf_8 | 5c24cde1675d190e4b276e047642098a | %THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
%DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
%FOR A... |
github | jingdao/Computational-Photography-master | mask2chain.m | .m | Computational-Photography-master/proj2/mask2chain.m | 15,715 | utf_8 | efd5cd29353ac38181da45395a525150 | function [x, y] = mask2chain_tmp(mask)
crack_img = seg2cracks(double(mask));
fragments = cracks2fragments(crack_img, mask, 1);
x = round(fragments{1}(:, 1));
y = round(fragments{1}(:, 2));
% x = fragments{1}(:, 1);
% y = fragments{1}(:, 2);
[gy, gx] = gradient(double(mask));
epix = (gy.^2+gx.^2>0) & mask;
... |
github | fryjustinc/sunset-detecting-with-SVM-and-ANN-master | demsvm2.m | .m | sunset-detecting-with-SVM-and-ANN-master/demsvm2.m | 10,878 | utf_8 | 36427c53822acf405dc1c62730ebe38a | function demsvm2()
% DEMSVM2 - Demonstrate advanced Support Vector Machine features
%
% DEMSVM2 demonstrates the classification of a simple artificial data
% set by a Support Vector Machine classifier. The features of the SVM
% routines that make it useful for large data sets are shown.
%
% See also
% SVM, S... |
github | fryjustinc/sunset-detecting-with-SVM-and-ANN-master | normalizeFeatures01.m | .m | sunset-detecting-with-SVM-and-ANN-master/normalizeFeatures01.m | 1,174 | utf_8 | 16f5c22e2890b3752a74a4ae67e6f1a6 | % This function normalizes the features to the range [0,1]. For each feature type,
% for example, Lmean, the min becomes 0 and max becomes 1. This isn't that robust, because
% a single outlier could compress the rest of the data too much.
% The data is assumed to be in the the format specified in the paper.
% Featur... |
github | fryjustinc/sunset-detecting-with-SVM-and-ANN-master | svmtrain.m | .m | sunset-detecting-with-SVM-and-ANN-master/svmtrain.m | 21,731 | utf_8 | 85340357d47285ad2f64255366ba67d7 | function net = svmtrain(net, X, Y, alpha0, dodisplay)
% SVMTRAIN - Train a Support Vector Machine classifier
%
% NET = SVMTRAIN(NET, X, Y)
% Train the SVM given by NET using the training data X with target values
% Y. X is a matrix of size (N,NET.nin) with N training examples (one per
% row). Y is a column vect... |
github | fryjustinc/sunset-detecting-with-SVM-and-ANN-master | demsvm1.m | .m | sunset-detecting-with-SVM-and-ANN-master/demsvm1.m | 8,180 | utf_8 | 81ad6488ed4152cba3f99a41786ef76d | function demsvm1()
% DEMSVM1 - Demonstrate basic Support Vector Machine classification
%
% DEMSVM1 demonstrates the classification of a simple artificial data
% set by a Support Vector Machine classifier, using different kernel
% functions.
%
% See also
% SVM, SVMTRAIN, SVMFWD, SVMKERNEL, DEMSVM2
%
%
% Cop... |
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