diff --git a/generate_cropped_notfaces.m b/generate_cropped_notfaces.m index f71c0ea..6f093a5 100644 --- a/generate_cropped_notfaces.m +++ b/generate_cropped_notfaces.m @@ -32,7 +32,7 @@ % Crop image croppedImage = img(startRow:startRow+dim-1, ... - startCol:startCol+dim-1); + startCol:startCol+dim-1, :); % Save image imgPath = strcat(new_imageDir, '/', int2str(n_have), '.jpg'); @@ -42,4 +42,45 @@ % list of uncropped images n_have = n_have + 1; i = i + 1; -end \ No newline at end of file +end + +%% Split training images into a training set and validation set +percentTraining = 80; +numOfTraining = floor((percentTraining/100)*n_have); + +% Making the directories +facesDir = 'cropped_training_images_faces'; +facesList = dir(sprintf('%s/*.jpg',facesDir)); + +notFacesDir = 'cropped_training_images_notfaces'; +notFacesList = dir(sprintf('%s/*.jpg',notFacesDir)); + +[~,~,~] = mkdir(strcat(facesDir,'/validation')); +[~,~,~] = mkdir(strcat(facesDir,'/training')); +[~,~,~] = mkdir(strcat(notFacesDir,'/validation')); +[~,~,~] = mkdir(strcat(notFacesDir,'/training')); + +for i = 1:numOfTraining + % Copy faces training images + source = strcat(facesDir,'/',facesList(i).name); + dest = strcat(facesDir,'/training/',facesList(i).name); + copyfile(source, dest); + + % Copy not faces training images + source = strcat(notFacesDir,'/',notFacesList(i).name); + dest = strcat(notFacesDir,'/training/',notFacesList(i).name); + copyfile(source, dest); +end + +for i = numOfTraining+1:n_have + % Copy faces validation images + source = strcat(facesDir,'/',facesList(i).name); + dest = strcat(facesDir,'/validation/',facesList(i).name); + copyfile(source, dest); + + % Copy not faces validation images + source = strcat(notFacesDir,'/',notFacesList(i).name); + dest = strcat(notFacesDir,'/validation/',notFacesList(i).name); + copyfile(source, dest); +end + \ No newline at end of file diff --git a/get_features.m b/get_features.m index 80e4b9a..2f13108 100644 --- a/get_features.m +++ b/get_features.m @@ -1,6 +1,9 @@ -close all -clear -run('../vlfeat-0.9.20/toolbox/vl_setup') +%% Run if VLFeat is not set up +run('vlfeat-0.9.21/toolbox/vl_setup'); + +%% Get Features +close all; +clear; pos_imageDir = 'cropped_training_images_faces'; pos_imageList = dir(sprintf('%s/*.jpg',pos_imageDir)); @@ -10,15 +13,18 @@ neg_imageList = dir(sprintf('%s/*.jpg',neg_imageDir)); neg_nImages = length(neg_imageList); -cellSize = 6; -featSize = 31*cellSize^2; +% cellSize needs to be a factor of 36 +cellSize = 4; +im = imread(sprintf('%s/%s',pos_imageDir,pos_imageList(1).name)); +[imRows, imCols, ~] = size(im); +featSize = 31*(imRows/cellSize)*(imCols/cellSize); pos_feats = zeros(pos_nImages,featSize); for i=1:pos_nImages im = im2single(imread(sprintf('%s/%s',pos_imageDir,pos_imageList(i).name))); feat = vl_hog(im,cellSize); pos_feats(i,:) = feat(:); - fprintf('got feat for pos image %d/%d\n',i,pos_nImages); +% fprintf('got feat for pos image %d/%d\n',i,pos_nImages); % imhog = vl_hog('render', feat); % subplot(1,2,1); % imshow(im); @@ -32,7 +38,7 @@ im = im2single(imread(sprintf('%s/%s',neg_imageDir,neg_imageList(i).name))); feat = vl_hog(im,cellSize); neg_feats(i,:) = feat(:); - fprintf('got feat for neg image %d/%d\n',i,neg_nImages); +% fprintf('got feat for neg image %d/%d\n',i,neg_nImages); % imhog = vl_hog('render', feat); % subplot(1,2,1); % imshow(im); @@ -41,4 +47,4 @@ % pause; end -save('pos_neg_feats.mat','pos_feats','neg_feats','pos_nImages','neg_nImages') \ No newline at end of file +save('pos_neg_feats.mat','pos_feats','neg_feats','pos_nImages','neg_nImages'); \ No newline at end of file diff --git a/train_svm.m b/train_svm.m index 6501bf6..5752ec1 100644 --- a/train_svm.m +++ b/train_svm.m @@ -1,13 +1,33 @@ -run('../vlfeat-0.9.20/toolbox/vl_setup') -load('pos_neg_feats.mat') +%% Run if VLFeat is not set up +run('vlfeat-0.9.20/toolbox/vl_setup'); -feats = cat(1,pos_feats,neg_feats); -labels = cat(1,ones(pos_nImages,1),-1*ones(neg_nImages,1)); +%% Split into training and validation +close all; +clear; -lambda = 0.1; -[w,b] = vl_svmtrain(feats',labels',lambda); +load('pos_neg_feats.mat'); + +percentTraining = 80; +numOfTraining = floor((percentTraining/100)*pos_nImages); + +trainFeats = cat(1,pos_feats(1:numOfTraining,:), ... + neg_feats(1:numOfTraining,:)); +validFeats = cat(1,pos_feats(1+numOfTraining:end,:), ... + neg_feats(1+numOfTraining:end,:)); +trainLabels = cat(1,ones(numOfTraining,1), ... + -1*ones(numOfTraining,1)); +validLabels = cat(1,ones(pos_nImages-numOfTraining,1), ... + -1*ones(pos_nImages-numOfTraining,1)); + +%% Train + +lambda = 0.06; +[w,b] = vl_svmtrain(trainFeats',trainLabels',lambda); fprintf('Classifier performance on train data:\n') -confidences = [pos_feats; neg_feats]*w + b; +confidences = [pos_feats(1:numOfTraining,:); neg_feats(1:numOfTraining,:)]*w + b; +[tp_rate, fp_rate, tn_rate, fn_rate] = report_accuracy(confidences, trainLabels); -[tp_rate, fp_rate, tn_rate, fn_rate] = report_accuracy(confidences, labels); +fprintf('Classifier performance on validation data:\n') +confidences = [pos_feats(1+numOfTraining:end,:); neg_feats(1+numOfTraining:end,:)]*w + b; +[tp_rate, fp_rate, tn_rate, fn_rate] = report_accuracy(confidences, validLabels); diff --git a/vlfeat-0.9.21/.gitattributes b/vlfeat-0.9.21/.gitattributes new file mode 100644 index 0000000..cdb3555 --- /dev/null +++ b/vlfeat-0.9.21/.gitattributes @@ -0,0 +1,3 @@ +*.manifest -crlf -diff -merge +*.vcproj binary +*.sln binary diff --git a/vlfeat-0.9.21/.gitignore b/vlfeat-0.9.21/.gitignore new file mode 100644 index 0000000..d96aef8 --- /dev/null +++ b/vlfeat-0.9.21/.gitignore @@ -0,0 +1,57 @@ +# Mac OS X Finder +.DS_Store + +# MEX files +*.mexglx +*.mexmac +*.mexmaci +*.mexmaci64 +*.mexa64 +*.mex + +# Python +*.pyc + +# Other generated files and directories +VERSION +docsrc/version.html +bin +results +doc +build +toolbox/mexw32 +toolbox/mexmaci +toolbox/mexmaci64 +toolbox/mexmac +toolbox/mexglx +toolbox/mexa64 +toolbox/mexw64 +toolbox/mex +toolbox/noprefix + +# Xcode +vlfeat.xcodeproj/*.mode1 +vlfeat.xcodeproj/*.mode1v3 +vlfeat.xcodeproj/*.mode2v3 +vlfeat.xcodeproj/*.pbxuser +vlfeat.xcodeproj/*.perspective* +vlfeat.xcodeproj/*.xcworkspace +vlfeat.xcodeproj/xcuserdata + +# Visual C++ +vlfeat.suo +vlfeat.ncb +vlfeat.vcproj.*.user +vc/* + +# Emacs backups +*~ + +# Vim swap files +.*.swp + +# Opt directory +opt/* + +# iDraw files +*.idraw diff --git a/vlfeat-0.9.21/COPYING b/vlfeat-0.9.21/COPYING new file mode 100644 index 0000000..1a1fb2e --- /dev/null +++ b/vlfeat-0.9.21/COPYING @@ -0,0 +1,25 @@ +Copyright (C) 2007-11, Andrea Vedaldi and Brian Fulkerson +Copyright (C) 2012-13, The VLFeat Team +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are +met: +1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. +2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the + distribution. + +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 +HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, +SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT +LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, +DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY +THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT +(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/vlfeat-0.9.21/Makefile b/vlfeat-0.9.21/Makefile new file mode 100644 index 0000000..908c578 --- /dev/null +++ b/vlfeat-0.9.21/Makefile @@ -0,0 +1,385 @@ +# file: Makefile +# description: Build everything +# author: Andrea Vedaldi + +# Copyright (C) 2014,18 Andrea Vedaldi. +# Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. +# All rights reserved. +# +# This file is part of the VLFeat library and is made available under +# the terms of the BSD license (see the COPYING file). + +# VLFEAT BUILDING INSTRUCTIONS +# +# This makefile builds VLFeat on standard Unix installations with the +# GNU toolchain. Mac OS X and GNU-Linux are explicitly +# supported. Usually, compiling VLFeat reduces to typing +# +# > cd PATH_TO_VLFEAT_SOURCE_TREE +# > make +# +# The makefile attempts to automatically determine the host +# architecture. If this fails, or if the architecture is ambiguous, +# the architecture can be set by specifying the ARCH variable. For +# instance: +# +# > make ARCH=maci64 +# +# builds VLFeat for Mac OS X Intel 64 bit. Pease +# see http://www.vlfeat.org/compiling.html +# for troubleshooting and details. +# +# Other useful variables are listed below (their default value is in +# square brackets). +# +# ARCH [not defined] - Active architecture. The supported +# architectures are maci, maci64, glnx86, or glnxa64 (these are +# the same architecture identifiers used by MATLAB: +# http://www.mathworks.com/help/techdoc/ref/computer.html). If +# undefined, the makefile attempts to automatically detect the +# architecture. +# +# DEBUG [not defined] - If defined, turns on debugging symbols and +# turns off optimizations +# +# PROFILE [not defined] - If defined, turns on debugging symbols but +# does NOT turn off optimizations. +# +# VERB [not defined] - If defined, display in full the command +# executed and their output. +# +# MEX [mex]- Path to MATLAB MEX compiler. If undefined, MATLAB support +# is disabled. +# +# MKOCTFILE [not defined] - Path to Octave MKOCTFILE compiler. If undefined, +# Octave support is disabled. +# +# If defined to anything other than "no", the following falgs disable +# specific features in the library. By defaults, all the features are +# enabled. If the makefile finds that the environment is unable to +# support some of them, it may decide to disable them automatically +# (in this case it will print a message). This behaviour can be +# overriden by defining the flag to be "no". +# +# DISABLE_SSE2 - SSE2 vector instructions support. +# DISABLE_AVX - AVX vector instructions support. +# DISABLE_THREADS - Supprot for multithreded library client. +# DISABLE_OPENMP - OpenMP-based multithreaded computations. +# +# To completely remove all build products use +# +# > make distclean +# +# Other useful targets include: +# +# clean - Removes intermediate build products for the active architecture. +# archclean - Removes all build products for the active architecture. +# distclean - Removes all build products. +# info - Display a list of the variables defined by the Makefile. +# help - Print this message. +# +# VLFeat is compsed of different parts (DLL, command line utilities, +# MATLAB interface, Octave interface) so the makefile is divided in +# components, located in make/*.mak. Please check out the +# corresponding files in order to adjust parameters. + +# Copyright (C) 2014,18 Andrea Vedaldi. +# Copyright (C) 2007-13 Andrea Vedaldi and Brian Fulkerson. +# All rights reserved. +# +# This file is part of the VLFeat library and is made available under +# the terms of the BSD license (see the COPYING file). + +SHELL = /bin/bash + +.PHONY : all +all: + +# Select which features to disable +# DISABLE_SSE2=yes +# DISABLE_AVX=yes +# DISABLE_THREADS=yes +# DISABLE_OPENMP=yes + +# -------------------------------------------------------------------- +# Error Messages +# -------------------------------------------------------------------- + +err_no_arch = +err_no_arch +=$(shell echo "** Unknown host architecture '$(UNAME)'. This identifier" 1>&2) +err_no_arch +=$(shell echo "** was obtained by running 'uname -sm'. Edit the Makefile " 1>&2) +err_no_arch +=$(shell echo "** to add the appropriate configuration." 1>&2) +err_no_arch +=config + +err_internal =$(shell echo Internal error) +err_internal +=internal + +err_spaces = $(shell echo "** VLFeat root dir VLDIR='$(VLDIR)' contains spaces." 1>&2) +err_spaces += $(shell echo "** This is not supported due to GNU Make limitations." 1>&2) +err_spaces +=spaces + +# -------------------------------------------------------------------- +# Auto-detect architecture +# -------------------------------------------------------------------- + +Darwin_PPC_ARCH := mac +Darwin_Power_Macintosh_ARCH := mac +Darwin_i386_ARCH := maci64 +Darwin_x86_64_ARCH := maci64 +Linux_i386_ARCH := glnx86 +Linux_i686_ARCH := glnx86 +Linux_unknown_ARCH := glnx86 +Linux_x86_64_ARCH := glnxa64 + +UNAME := $(shell uname -sm) +ARCH ?= $($(shell echo "$(UNAME)" | tr \ _)_ARCH) + +# sanity check +ifeq ($(ARCH),) +die:=$(error $(err_no_arch)) +endif + +ifneq ($(VLDIR),$(shell echo "$(VLDIR)" | sed 's/ //g')) +die:=$(error $(err_spaces)) +endif + +# -------------------------------------------------------------------- +# Configuration +# -------------------------------------------------------------------- + +VLDIR ?= . +LIBTOOL ?= libtool + +STD_CLFAGS = $(CFLAGS) +STD_CFLAGS += -std=c99 +STD_CFLAGS += -Wall -Wextra +STD_CFLAGS += -Wno-unused-function -Wno-long-long -Wno-variadic-macros +STD_CFLAGS += $(if $(DEBUG), -DDEBUG -O0 -g, -DNDEBUG -O3) +STD_CFLAGS += $(if $(PROFILE), -g) + +STD_LDFLAGS = $(LDFLAGS) + +# Architecture specific ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +# Detect compiler +COMPILER_VER_STRING:=$(shell $(CC) --version) $(shell $(CC) -v 2>&1) +COMPILER:=other + +ifneq ($(shell echo "$(COMPILER_VER_STRING)" | grep "gcc"),) +COMPILER:=gcc +COMPILER_VER:=$(shell \ +$(CC) -dumpversion | \ +sed -e 's/\.\([0-9][0-9]\)/\1/g' \ + -e 's/\.\([0-9]\)/0\1/g' \ + -e 's/^[0-9]\{3,4\}$$/&00/' ) +endif + +ifeq "$(findstring clang,$(COMPILER_VER_STRING))" "clang" +COMPILER:=clang +COMPILER_VER:=$(shell \ +echo "$(COMPILER_VER_STRING)" | \ +sed -n -e 's/.*version *\([0-9.][0-9.]*\).*/\1/p;' | \ +sed -e 's/\.\([0-9][0-9]\)/\1/g' \ + -e 's/\.\([0-9]\)/0\1/g' \ + -e 's/^[0-9]\{3,4\}$$/&00/' ) +endif + +$(info Detected compiler: $(COMPILER) $(COMPILER_VER)) +ifeq "$(COMPILER_VER)" "other" +$(warning Unsupported compiler detected, use at your own risk!) +endif + +ifeq "$(COMPILER)" "gcc" +ifeq "$(shell expr $(COMPILER_VER) \<= 40600)" "1" +ifneq "$(DISABLE_AVX)" "no" +$(info GCC <= 4.6.0 detected, disabling AVX.) +DISABLE_AVX:=yes +endif +endif +endif + +ifeq "$(COMPILER)" "clang" +ifneq "$(DISABLE_OPENMP)" "no" +$(info Apple Clang does not support OpenMP yet, disabling.) +$(info Alternatively, use brew llvm clang and specify DISABLE_OPENMP=no.) +DISABLE_OPENMP:=yes +endif +endif + +# Mac OS X Intel +ifeq "$(ARCH)" "$(filter $(ARCH),maci maci64)" +ifeq "$(ARCH)" "maci" +march=32 +else +march=64 +endif +SDKROOT ?= $(shell xcrun -sdk macosx --show-sdk-path) +MACOSX_DEPLOYMENT_TARGET ?= 10.4 +STD_CFLAGS += -m$(march) -isysroot $(SDKROOT) -mmacosx-version-min=$(MACOSX_DEPLOYMENT_TARGET) +STD_LDFLAGS += -Wl,-syslibroot,$(SDKROOT) -mmacosx-version-min=$(MACOSX_DEPLOYMENT_TARGET) +endif + +# Linux +ifeq "$(ARCH)" "$(filter $(ARCH),glnx86 glnxa64)" +ifeq "$(ARCH)" "glnx86" +march=32 +else +march=64 +endif +# Target compatibility with GLIBC 2.3.4 +# 1) _GNU_SOURCE avoids using isoc99_fscanf, limiting binary portability to recent GLIBC. +# 2) -fno-stack-protector avoids using a feature requiring GLBIC 2.4 +STD_CFLAGS += -m$(march) -D_GNU_SOURCE -fno-stack-protector +STD_LDFLAGS += -m$(march) -Wl,--rpath,\$$ORIGIN/ -Wl,--as-needed +endif + +# Convert back DISALBE_*="no" flags to be empty +ifeq "$(DISABLE_SSE2)" "no" +override DISABLE_SSE2:= +endif +ifeq "$(DISABLE_AVX)" "no" +override DISABLE_AVX:= +endif +ifeq "$(DISABLE_THREADS)" "no" +override DISABLE_THREADS:= +endif +ifeq "$(DISABLE_OPENMP)" "no" +override DISABLE_OPENMP:= +endif + +# -------------------------------------------------------------------- +# Functions +# -------------------------------------------------------------------- + +# $(call if-like,FILTER,WHY,WHAT) +define if-like +$(if $(filter $(1),$(2)),$(3)) +endef + +# $(call dump-var,VAR) pretty-prints the content of a variable VAR on +# multiple columns +ifdef VERB +define dump-var +@echo "$(1) =" +@echo "$($(1))" | sed 's/\([^ ][^ ]* [^ ][^ ]*\) */\1#/g' | \ +tr '#' '\n' | column -t | sed 's/\(.*\)/ \1/g' +endef +else +define dump-var +@printf "%15s = %s\n" "$(1)" \ +"$$(echo '$($(1))' | sed -e 's/[^ ][^ ]* /\.\.\./3' -e 's/\.\.\..*$$/\.\.\./g')" +endef +endif + +# $(call echo-var,VAR) pretty-prints the content of a variable VAR on +# one line +define echo-var +@printf "%15s = %s\n" '$(1)' '$($(1))' +endef + +# $(call echo-title,TITLE) pretty-prints TITLE as a title +define echo-title +@printf "** %s\n" '$(1)' +endef + +# $(call C, CMD) runs $(CMD) silently +define C +@printf "%15s %s\n" '$(1)' '$(@)' +$(Q)"$($(1))" +endef + +# If verbose print everything +ifdef VERB +Q= +else +Q=@ +endif + +# Greater or equal: returns the empty string if $1 >= $2, otherwise returns 'false', +# where the arguments are integer numbers +gt = $(shell if [ "$(1)" -lt "$(2)" ] ; then echo false ; fi) + +# rule to create a directory +.PRECIOUS: %/.dirstamp +%/.dirstamp : + @printf "%15s %s\n" MK "$(dir $@)" + @mkdir -p $(dir $@) + @echo "Directory generated by make." > $@ + +# $(call gendir, TARGET, DIR1 DIR2 ...) creates a target TARGET-dir that +# triggers the creation of the directories DIR1, DIR2 +define gendir +$(1)-dir=$(foreach x,$(2),$(x)/.dirstamp) +endef + +# -------------------------------------------------------------------- +# Build +# -------------------------------------------------------------------- + +# Each Makefile submodule appends appropriate dependencies to the all, +# clean, archclean, distclean, and info targets. In addition, it +# appends to the deps and bins variables the list of .d files (to be +# inclued by make as auto-dependencies) and the list of files to be +# added to the binary distribution. + +.PHONY: clean, archclean, distclean, info, help +no_dep_targets := clean archclean distclean help + +include make/dll.mak +include make/bin.mak +include make/matlab.mak +include make/octave.mak +include make/doc.mak +include make/dist.mak + +clean: + rm -f `find . -name '*~'` + rm -f `find . -name '.DS_Store'` + rm -f `find . -name '.gdb_history'` + rm -f `find . -name '._*'` + rm -rf ./results + +archclean: clean + +distclean: + +info: + $(call echo-title,General settings) + $(call dump-var,deps) + $(call echo-var,PROFILE) + $(call echo-var,DEBUG) + $(call echo-var,VER) + $(call echo-var,ARCH) + $(call echo-var,CC) + $(call echo-var,COMPILER) + $(call echo-var,COMPILER_VER) + $(call echo-var,STD_CFLAGS) + $(call echo-var,STD_LDFLAGS) + $(call echo-var,DISABLE_SSE2) + $(call echo-var,DISABLE_AVX) + $(call echo-var,DISABLE_THREADS) + $(call echo-var,DISABLE_OPENMP) + @printf "\nThere are %s lines of code.\n" \ + `cat $(m_src) $(mex_src) $(dll_src) $(dll_hdr) $(bin_src) | wc -l` + +# Holw help works: cat this file, +# skip the first block until an empty line is found (twice) +# print the first block until an empty line, +# remove the `# ' prefix from each remaining line + +help: + @cat Makefile | \ + sed -n '1,/^$$/!p' | \ + sed -n '1,/^$$/!p' | \ + sed -n '1,/^$$/p' | \ + sed 's/^# \{0,1\}\(.*\)$$/\1/' + +# -------------------------------------------------------------------- +# Include dependencies +# -------------------------------------------------------------------- + +.PRECIOUS: $(deps) + +ifneq ($(filter-out $(no_dep_targets), $(MAKECMDGOALS)),) +-include $(deps) +endif diff --git a/vlfeat-0.9.21/Makefile.mak b/vlfeat-0.9.21/Makefile.mak new file mode 100644 index 0000000..1275ecb --- /dev/null +++ b/vlfeat-0.9.21/Makefile.mak @@ -0,0 +1,586 @@ +# file: Makefile.mak +# descrption: Microsoft NMake makefile +# authors: Andrea Vedaldi, Brian Fulkerson, Mircea Cimpoi + +# Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson. +# All rights reserved. +# +# This file is part of the VLFeat library and is made available under +# the terms of the BSD license (see the COPYING file). + +# -------------------------------------------------------------------- +# Customization +# -------------------------------------------------------------------- +# To modify this script to run on your platform it is usually +# sufficient to modify the following variables: +# +# ARCH: Either win32 or win64 [win64] +# DEBUG: Set to yes to ativate debugging [no] +# MATLABROOT: Path to MATLAB +# MATLABVER: MATLAB version (e.g. 90200 for 9.2.0 - 2017a) +# MSVSVER: Visual Studio version (e.g. 80, 90, 100) [90 for VS 9.0] +# MSVCROOT: Visual C++ location [$(VCInstallDir)]. +# WINSDKROOT: Windows SDK location [$(WindowsSdkDir)] +# +# Note that some of these variables depend on the architecture +# (either win32 or win64). + +VER = 0.9.21 +ARCH = win64 +DEBUG = no +BRANCH = v$(VER)-$(ARCH) +MSVSVER = +MSVCROOT = $(VCINSTALLDIR) +WINSDKROOT = $(WINDOWSSDKDIR) +GIT = git + +!if "$(MSVCROOT)" == "" +MSVCROOT = C:\Program Files\Microsoft Visual Studio 10.0\VC +!endif + +!if "$(WINSDKROOT)" == "" +WINSDKROOT = C:\Program Files\Microsoft SDKs\Windows\v7.0A +!endif + +!include make/nmake_helper.mak + +MATLABROOT = C:\Program Files\MATLAB\R2017a +MATLABVER = 90200 +MEX = "$(MATLABROOT)\bin\mex.bat" + +# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 32-bit +!if "$(ARCH)" == "win32" +!message === COMPILING FOR 32-BIT +!if $(MATLABVER) <= 80500 +MEXOPT = "$(MATLABROOT)\bin\win32\mexopts\msvc$(MSVSVER)opts.bat" +!else +MEXOPT = "$(MATLABROOT)\bin\win32\mexopts\msvc$(MSVSYEAR).xml" +!endif +MEXEXT = mexw32 +MEX_FLAGS = + +CC = "$(MSVCROOT)\bin\cl.exe" +LINK = "$(MSVCROOT)\bin\link.exe" +MSVCR_PATH = $(MSVCROOT)\redist\x86\Microsoft.VC$(MSVSVER).CRT + +LFLAGS = /MACHINE:X86 \ + /LIBPATH:"$(MSVCROOT)\lib" \ + /LIBPATH:"$(WINSDKROOT)\lib" + +# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64-bit +!elseif "$(ARCH)" == "win64" +!message === COMPILING FOR 64-BIT +MEX = "$(MATLABROOT)\bin\mex.bat" +!if $(MATLABVER) <= 80500 +MEXOPT = "$(MATLABROOT)\bin\win64\mexopts\msvc$(MSVSVER)opts.bat" +!else +MEXOPT = "$(MATLABROOT)\bin\win64\mexopts\msvc$(MSVSYEAR).xml" +!endif +MEXEXT = mexw64 +MEX_FLAGS = -largeArrayDims + +CC = "$(MSVCROOT)\bin\amd64\cl.exe" +LINK = "$(MSVCROOT)\bin\amd64\link.exe" +!if $(MSVSVER) >= 100 +MSVCR_PATH = $(MSVCROOT)\redist\x64\Microsoft.VC$(MSVSVER).CRT +!else +MSVCR_PATH = $(MSVCROOT)\redist\amd64\Microsoft.VC$(MSVSVER).CRT +!endif + +LFLAGS = /MACHINE:X64 \ + /LIBPATH:"$(MSVCROOT)\lib\amd64" \ + /LIBPATH:"$(WINSDKROOT)\lib\x64" +!else +!error ARCH = $(ARCH) is an unknown architecture. +!endif + +# -------------------------------------------------------------------- +# Flags +# -------------------------------------------------------------------- +# Debug info is embedded in .obj and .lib files (CodeView /Z7 option) +# but in .pdb files for .exe and .dll (since the linker does not +# produce CodeView output anymore). +# +# CFLAGS +# /nologo : CL does not display splash +# _CRT_NO_DEPRECATE : Do not deprecate `insecure' fscanf, snprintf, ... +# __LITTLE_ENDIAN__ : Signal little endian architecture +# /I. : Add VLROOT to include search path +# /MD : Multi-thread run-time library dynamically linked +# /TC : Source code is C (not C++) +# /W3 : Usa all warnings +# /Zp8 : Align structures to 8 bytes +# /Ox : Turn on optimizations +# /D"DEBUG" : [DEBUG] Turn on debugging in VLFeat +# /Z7 : [DEBUG] Embedded CodeView debug info in .obj +# /D"NDEBUG" : [NO DEBUG] Switches off asserts +# +# LFLAGS +# /NOLOGO : LINK does not display splash +# /INCREMENTAL:NO : No incremental linking +# /MANIFEST : See DLL HELL below +# /DEBUG : [DEBUG] Generate debug info (.pdb files) +# +# MEX_FLAGS +# -I : Include VLFeat +# -L : Add a library search path +# -l : Link a dll +# +# ======================= ABOUT THE DLL HELL ========================= +# +# This makefile compiles VLFeat to make use of the side-by-side +# deployment model, redestribtin the appropraite Visual C runtime +# library with the library and executables. In Visual Studio < 10.0 +# this meant including a manifest file, while in version >= 10.0 this +# requirement has been relaxed. +# +# References: +# http://www.codeguru.com/forum/showthread.php?t=408061 +# http://mariusbancila.ro/blog/2010/03/24/visual-studio-2010-changes-for-vc-part-5 +# http://social.msdn.microsoft.com/Forums/is/vcgeneral/thread/ca9177b2-2d02-42d8-8892-c6a25e6cfadb +# + +bindir = bin\$(ARCH) +mexdir = toolbox\mex\$(MEXEXT) +objdir = $(bindir)\objs + +CFLAGS = /nologo /TC /MD \ + /D"_CRT_SECURE_NO_DEPRECATE" \ + /D"__LITTLE_ENDIAN__" \ + /D"VL_DISABLE_AVX" \ + /I. \ + /W1 /Zp8 /openmp + +LFLAGS = $(LFLAGS) /NOLOGO \ + /INCREMENTAL:NO \ + /MANIFEST + +!if "$(DEBUG)" != "no" +!message === DEBUGGING ON +CFLAGS = $(CFLAGS) /Z7 /D"DEBUG" +LFLAGS = $(LFLAGS) /DEBUG +MEX_FLAGS = $(MEX_FLAGS) -g +!else +!message === DEBUGGING OFF +CFLAGS = $(CFLAGS) /D"NDEBUG" /Ox +!endif + +DLL_CFLAGS = /D"VL_BUILD_DLL" +EXE_LFLAGS = $(LFLAGS) /LIBPATH:"$(bindir)" vl.lib +MEX_FLAGS = $(MEX_FLAGS) -f $(MEXOPT) -I. -Itoolbox -L"$(bindir)" -lvl + +libsrc = \ + vl\aib.c \ + vl\array.c \ + vl\covdet.c \ + vl\dsift.c \ + vl\fisher.c \ + vl\generic.c \ + vl\getopt_long.c \ + vl\gmm.c \ + vl\hikmeans.c \ + vl\hog.c \ + vl\homkermap.c \ + vl\host.c \ + vl\ikmeans.c \ + vl\imopv.c \ + vl\imopv_sse2.c \ + vl\kdtree.c \ + vl\kmeans.c \ + vl\lbp.c \ + vl\liop.c \ + vl\mathop.c \ + vl\mathop_avx.c \ + vl\mathop_sse2.c \ + vl\mser.c \ + vl\pgm.c \ + vl\quickshift.c \ + vl\random.c \ + vl\rodrigues.c \ + vl\scalespace.c \ + vl\sift.c \ + vl\slic.c \ + vl\stringop.c \ + vl\svm.c \ + vl\svmdataset.c \ + vl\vlad.c + +cmdsrc = \ + src\aib.c \ + src\mser.c \ + src\sift.c \ + src\test_gauss_elimination.c \ + src\test_getopt_long.c \ + src\test_gmm.c \ + src\test_heap-def.c \ + src\test_host.c \ + src\test_imopv.c \ + src\test_kmeans.c \ + src\test_liop.c \ + src\test_mathop.c \ + src\test_mathop_abs.c \ + src\test_nan.c \ + src\test_qsort-def.c \ + src\test_rand.c \ + src\test_sqrti.c \ + src\test_stringop.c \ + src\test_svd2.c \ + src\test_threads.c \ + src\test_vec_comp.c + +cmdsrc = \ + src\aib.c \ + src\mser.c \ + src\sift.c \ + src\test_gauss_elimination.c \ + src\test_getopt_long.c \ + src\test_gmm.c \ + src\test_heap-def.c \ + src\test_host.c \ + src\test_imopv.c \ + src\test_kmeans.c \ + src\test_liop.c \ + src\test_mathop.c \ + src\test_mathop_abs.c \ + src\test_nan.c \ + src\test_qsort-def.c \ + src\test_rand.c \ + src\test_sqrti.c \ + src\test_stringop.c \ + src\test_svd2.c \ + src\test_threads.c \ + src\test_vec_comp.c + +mexsrc = \ + toolbox\aib\vl_aib.c \ + toolbox\aib\vl_aibhist.c \ + toolbox\fisher\vl_fisher.c \ + toolbox\geometry\vl_irodr.c \ + toolbox\geometry\vl_rodr.c \ + toolbox\gmm\vl_gmm.c \ + toolbox\imop\vl_imdisttf.c \ + toolbox\imop\vl_imintegral.c \ + toolbox\imop\vl_imsmooth.c \ + toolbox\imop\vl_imwbackwardmx.c \ + toolbox\imop\vl_tpsumx.c \ + toolbox\kmeans\vl_hikmeans.c \ + toolbox\kmeans\vl_hikmeanspush.c \ + toolbox\kmeans\vl_ikmeans.c \ + toolbox\kmeans\vl_ikmeanspush.c \ + toolbox\kmeans\vl_kmeans.c \ + toolbox\misc\vl_alldist.c \ + toolbox\misc\vl_alldist2.c \ + toolbox\misc\vl_binsearch.c \ + toolbox\misc\vl_binsum.c \ + toolbox\misc\vl_cummax.c \ + toolbox\misc\vl_getpid.c \ + toolbox\misc\vl_hog.c \ + toolbox\misc\vl_homkermap.c \ + toolbox\misc\vl_ihashfind.c \ + toolbox\misc\vl_ihashsum.c \ + toolbox\misc\vl_inthist.c \ + toolbox\misc\vl_kdtreebuild.c \ + toolbox\misc\vl_kdtreequery.c \ + toolbox\misc\vl_lbp.c \ + toolbox\misc\vl_localmax.c \ + toolbox\misc\vl_sampleinthist.c \ + toolbox\misc\vl_simdctrl.c \ + toolbox\misc\vl_svmtrain.c \ + toolbox\misc\vl_threads.c \ + toolbox\misc\vl_twister.c \ + toolbox\misc\vl_version.c \ + toolbox\mser\vl_erfill.c \ + toolbox\mser\vl_mser.c \ + toolbox\quickshift\vl_quickshift.c \ + toolbox\sift\vl_covdet.c \ + toolbox\sift\vl_dsift.c \ + toolbox\sift\vl_liop.c \ + toolbox\sift\vl_sift.c \ + toolbox\sift\vl_siftdescriptor.c \ + toolbox\sift\vl_ubcmatch.c \ + toolbox\slic\vl_slic.c \ + toolbox\vlad\vl_vlad.c + +!if "$(ARCH)" == "win32" +libobj = $(libsrc:vl\=bin\win32\objs\) +cmdexe = $(cmdsrc:src\=bin\win32\) +mexdll = $(mexsrc:.c=.mexw32) +mexdll = $(mexdll:toolbox\fisher=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\sift=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\mser=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\imop=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\geometry=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\gmm=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\kmeans=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\misc=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\aib=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\quickshift=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\slic=toolbox\mex\mexw32) +mexdll = $(mexdll:toolbox\vlad=toolbox\mex\mexw32) +mexpdb = $(mexdll:.dll=.pdb) + +!elseif "$(ARCH)" == "win64" +libobj = $(libsrc:vl\=bin\win64\objs\) +cmdexe = $(cmdsrc:src\=bin\win64\) +mexdll = $(mexsrc:.c=.mexw64) +mexdll = $(mexdll:toolbox\fisher=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\sift=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\mser=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\imop=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\geometry=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\gmm=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\kmeans=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\misc=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\aib=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\quickshift=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\slic=toolbox\mex\mexw64) +mexdll = $(mexdll:toolbox\vlad=toolbox\mex\mexw64) +mexpdb = $(mexdll:.mexw64=.pdb) +!endif + +libobj = $(libobj:.c=.obj) +cmdexe = $(cmdexe:.c=.exe) +cmdpdb = $(cmdexe:.exe=.pdb) + +# Visual Studio redistributable files +MSVCR = Microsoft.VC$(MSVSVER).CRT +!if $(MSVSVER) <= 90 +# VS <= 2008 needs a manifest too +bincrt = $(bindir)\msvcr$(MSVSVER).dll $(bindir)\$(MSVCR).manifest +mexcrt = $(mexdir)\msvcr$(MSVSVER).dll $(mexdir)\$(MSVCR).manifest +!else if $(MSVSVER) <= 120 +bincrt = $(bindir)\msvcr$(MSVSVER).dll +mexcrt = $(mexdir)\msvcr$(MSVSVER).dll +!else +# With Visual Studio 2015 the universal run time does not need to be redistributed? +# https://blogs.msdn.microsoft.com/vcblog/2015/03/03/introducing-the-universal-crt/ +bincrt = +mexcrt = +!endif + +!ifdef MATLABROOT +all: $(bindir) $(objdir) $(mexdir) \ + $(bincrt) $(bindir)\vl.lib $(bindir)\vl.dll \ + $(cmdexe) \ + $(mexcrt) $(mexdir)\vl.dll $(mexdll) +!else +all: $(bindir) $(objdir) \ + $(bincrt) $(bindir)\vl.lib $(bindir)\vl.dll \ + $(cmdexe) +!endif + +BUILD_MEX=@echo .... CC [MEX] $(@) && \ + $(MEX) $(MEX_FLAGS) "$(<)" -output $(@) + +# -------------------------------------------------------------------- +# Maintenance rules +# -------------------------------------------------------------------- + +clean: + del /f /Q $(libobj) + del /f /Q $(objdir) + del /f /Q $(cmdpdb) + del /f /Q $(mexpdb) + +archclean: + if exist bin\$(ARCH) rmdir /S /Q bin\$(ARCH) + if exist $(mexdir) rmdir /S /Q $(mexdir) + +distclean: + if exist bin rmdir /S /Q bin + if exist toolbox\mex rmdir /S /Q toolbox\mex + +info: + @echo $(mexx) + @echo ** bindir = $(bindir) + @echo ** mexdir = $(mexdir) + @echo ** objdir = $(objdir) + @echo ** libsrc = $(libsrc) + @echo ** libobj = $(libobj) + @echo ** cmdsrc = $(cmdsrc) + @echo ** cmdexe = $(cmdexe) + @echo ** mexsrc = $(mexsrc) + @echo ** mexdll = $(mexdll) + @echo ** CC = $(CC) + @echo ** CFLAGS = $(CFLAGS) + @echo ** DLL_CFLAGS = $(DLL_CFLAGS) + @echo ** MEX_FLAGS = $(MEX_FLAGS) + @echo ** BUILD_MEX = "$(BUILD_MEX)" + @echo ** MATLABROOT = $(MATLABROOT) + @echo ** MEX = $(MEX) + @echo ** MEXEXT = $(MEXEXT) + @echo ** MEXOPT = $(MEXOPT) + @echo ** MSVSVER = $(MSVSVER) + @echo ** MSVCROOT = $(MSVCROOT) + @echo ** MSVCR = $(MSVCR) + @echo ** MSVCR_PATH = $(MSVCR_PATH) + @echo ** bincrt = $(bincrt) + @echo ** mexcrt = $(mexcrt) + @echo ** WINSDKROOT = $(WINSDKROOT) + @echo ** DEBUG = $(DEBUG) + +# -------------------------------------------------------------------- +# Build rules +# -------------------------------------------------------------------- + +# create directory if missing +$(bindir) : + mkdir $(bindir) + +$(objdir) : + mkdir $(objdir) + +$(mexdir) : + mkdir $(mexdir) + +# -------------------------------------------------------------------- +# Rules to compile the VLFeat DLL +# -------------------------------------------------------------------- + +# special sources with SSE2 support +$(objdir)\mathop_sse2.obj : vl\mathop_sse2.c + @echo .... CC [+SSE2] $(@) + @$(CC) $(CFLAGS) $(DLL_CFLAGS) /arch:SSE2 /D"__SSE2__" /c /Fo"$(@)" "vl\$(@B).c" + +$(objdir)\imopv_sse2.obj : vl\imopv_sse2.c + @echo .... CC [+SSE2] $(@) + @$(CC) $(CFLAGS) $(DLL_CFLAGS) /arch:SSE2 /D"__SSE2__" /c /Fo"$(@)" "vl\$(@B).c" + +# vl\*.c -> $objdir\*.obj +{vl}.c{$(objdir)}.obj: + @echo .... CC $(@) + @$(CC) $(CFLAGS) $(DLL_CFLAGS) /c /Fo"$(@)" "$(<)" + +# Link VLFeat DLL +$(bindir)\vl.dll : $(libobj) + @echo .. LINK [DLL] $(@R).dll + $(LINK) /DLL $(LFLAGS) $(**) /OUT:"$(@)" + @mt /nologo /outputresource:"$(@);#2" /manifest "$(@R).dll.manifest" + @-del "$(@R).dll.manifest" + +# *.obj -> *.lib +$(bindir)\vl.lib : $(libobj) + @echo ... LIB $(@R).lib + @lib $(**) /OUT:"$(@)" /NOLOGO + +# redistributable: msvcr__.dll => bin/win{32,64}/msvcr__.dll +$(bindir)\$(MSVCR).manifest : "$(MSVCR_PATH)\$(MSVCR).manifest" + copy $(**) "$(@)" + +$(bindir)\msvcr$(MSVSVER).dll: "$(MSVCR_PATH)\msvcr$(MSVSVER).dll" + copy $(**) "$(@)" + +# -------------------------------------------------------------------- +# Rules to compile the VLFeat EXE files +# -------------------------------------------------------------------- + +# src\*.c -> $bindir\*.exe +{src}.c{$(bindir)}.exe: + @echo .... CC [EXE] $(@) + @$(CC) $(CFLAGS) /Fe"$(@)" /Fo"$(@R).obj" "$(<)" /link $(EXE_LFLAGS) + @MT /nologo /outputresource:"$(@);#1" /manifest "$(@).manifest" + @-del "$(@).manifest" + @-del "$(@R).obj" + +# -------------------------------------------------------------------- +# Rules to compile the VLFeat MEX files +# -------------------------------------------------------------------- + +startmatlab: + "$(MATLABROOT)/bin/matlab.exe" -nodesktop + +# toolbox\*.c -> toolbox\*.dll +{toolbox\sift}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\mser}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\imop}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\gmm}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\geometry}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\kmeans}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\aib}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\quickshift}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\misc}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\slic}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\vlad}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +{toolbox\fisher}.c{$(mexdir)}.$(MEXEXT): + $(BUILD_MEX) + +# vl.dll => mexw{32,64}\vl.dll +$(mexdir)\vl.dll : $(bindir)\vl.dll + copy "$(**)" "$(@)" + +# Ideally, the DLL should be linked to Intel compatibility library libiomp5md.dll that +# ships with MATLAB. However, there does not seem to be a clean way to do so without +# the .lib file. This is suboptimal as it casues two OMP libraries to be used (vcomp and iomp5). +# Possible work arounds that did not work yet: generate the .lib file from the .dll file, +# redirect somehow vcomp to iomp5. + +#$(LINK) /LIBPATH:"$(MATLABROOT)\extern\lib\win64\microsoft" /DLL $(LFLAGS) $(**) libmwblas.lib /nodefaultlib:vcomp /OUT:"$(@)" +#$(mexdir)\vl.dll : $(libobj) +# @echo .. LINK [DLL] $(@R).dll +# $(LINK) /DLL $(LFLAGS) $(**) /OUT:"$(@)" +# @-del "$(@R).dll.manifest" + +# redistributable: msvcr__.dll => bin/win{32,64}/msvcr__.dll +$(mexdir)\$(MSVCR).manifest : "$(MSVCR_PATH)\$(MSVCR).manifest" + copy $(**) "$(@)" + +$(mexdir)\msvcr$(MSVSVER).dll: "$(MSVCR_PATH)\msvcr$(MSVSVER).dll" + copy $(**) "$(@)" + +# -------------------------------------------------------------------- +# Rules to post the binary files +# -------------------------------------------------------------------- + +bin-release: + echo Fetching remote tags && \ + $(GIT) fetch --tags && \ + echo Checking out v$(VER) && \ + $(GIT) checkout v$(VER) + echo Rebuilding binaries for release + if exist "bin\$(ARCH)" del /f /Q "bin\$(ARCH)" + if exist "bin\mex\$(ARCH)" del /f /Q "toolbox\mex$(ARCH)" + nmake /f Makefile.mak ARCH=$(ARCH) + +bin-commit: bin-release + @echo Fetching remote tags && \ + $(GIT) fetch --tags + @echo Crearing/resetting and checking out branch $(BRANCH) to v$(VER) && \ + $(GIT) branch -f $(BRANCH) v$(VER) && \ + $(GIT) checkout $(BRANCH) + @echo Adding binaries && \ + $(GIT) add -f $(bincrt) && \ + $(GIT) add -f "$(bindir)\vl.lib" && \ + $(GIT) add -f "$(bindir)\vl.dll" && \ + $(GIT) add -f $(cmdexe) && \ + @echo Adding MEX files && \ + $(GIT) add -f $(mexcrt) && \ + $(GIT) add -f "$(mexdir)\vl.dll" && \ + $(GIT) add -f $(mexdll) && \ + @echo Commiting changes && \ + $(GIT) commit -m "$(ARCH) binaries for version $(VER)" + @echo Commiting and pushing to server the binaries && \ + $(GIT) push -v --force bin $(BRANCH):refs/heads/$(BRANCH) && \ + $(GIT) checkout v$(VER) && \ + $(GIT) branch -D $(BRANCH) diff --git a/vlfeat-0.9.21/README.md b/vlfeat-0.9.21/README.md new file mode 100644 index 0000000..51147b1 --- /dev/null +++ b/vlfeat-0.9.21/README.md @@ -0,0 +1,122 @@ +# VLFeat -- Vision Lab Features Library + +> Version 0.9.20 + +The VLFeat open source library implements popular computer vision +algorithms specialising in image understanding and local featurexs +extraction and matching. Algorithms incldue Fisher Vector, VLAD, +SIFT, MSER, k-means, hierarchical k-means, agglomerative information +bottleneck, SLIC superpixes, quick shift superpixels, large scale SVM +training, and many others. It is written in C for efficiency and +compatibility, with interfaces in MATLAB for ease of use, and detailed +documentation throughout. It supports Windows, Mac OS X, and Linux. + +VLFeat is distributed under the BSD license (see the `COPYING` file). + +The documentation is +[available online](http://www.vlfeat.org/index.html) and shipped with +the library as `doc/index.html`. See also: + +* [Using with MATLAB](http://www.vlfeat.org/install-matlab.html) +* [Using the command line utilities](http://www.vlfeat.org/install-shell.html) +* [Using the C API](http://www.vlfeat.org/install-c.html) +* [Compiling from source](http://www.vlfeat.org/compiling.html) + +## Quick start with MATLAB + +To start using VLFeat as a MATLAB toolbox, download the latest VLFeat +[binary package](http://www.vlfeat.org/download/). Note that the +pre-compiled binaries require MATLAB 2009B and later. Unpack it, for +example by using WinZIP (Windows), by double clicking on the archive +(Mac), or by using the command line (Linux and Mac): + + > tar xzf vlfeat-X.Y.Z-bin.tar.gz + +Here X.Y.Z denotes the latest version. Start MATLAB and run the +VLFeat setup command: + + > run /toolbox/vl_setup + +Here `` should be replaced with the path to the VLFeat +directory created by unpacking the archive. All VLFeat demos can now +be run in a row by the command: + + > vl_demo + +Check out the individual demos by editing this file: `edit vl_demo`. + +## Octave support + +The toolbox should be laregly compatible with GNU Octave, an open +source MATLAB equivalent. However, the binary distribution does not +ship with pre-built GNU Octave MEX files. To compile them use + + > cd + > make MKOCTFILE= + +# Changes + +- **0.9.21** Maintenance release. Bugfixes. +- **0.9.20** Maintenance release. Bugfixes. +- **0.9.19** Maintenance release. Minor bugfixes and fixes compilation + with MATLAB 2014a. +- **0.9.18** Several bugfixes. Improved documentation, particularly of + the covariant detectors. Minor enhancements of the Fisher vectors. +- **0.9.17** Rewritten SVM implementation, adding support for SGD and + SDCA optimisers and various loss functions (hinge, squared hinge, + logistic, etc.) and improving the interface. Added infrastructure to + support multi-core computations using OpenMP (MATLAB 2009B or later + required). Added OpenMP support to KD-trees and KMeans. Added new + Gaussian Mixture Models, VLAD encoding, and Fisher Vector encodings + (also with OpenMP support). Added LIOP feature descriptors. Added + new object category recognition example code, supporting several + standard benchmarks off-the-shelf. +- **0.9.16** Added `VL_COVDET`. This function implements the following + detectors: DoG, Hessian, Harris Laplace, Hessian Laplace, Multiscale + Hessian, Multiscale Harris. It also implements affine adaptation, + estiamtion of feature orientation, computation of descriptors on the + affine patches (including raw patches), and sourcing of custom + feature frame. +- **0.9.15** Added `VL_HOG` (HOG features). Added `VL_SVMPEGASOS` and + a vastly improved SVM implementation. Added `VL_IHASHSUM` (hashed + counting). Improved INTHIST (integral histogram). Added + `VL_CUMMAX`. Improved the implementation of `VL_ROC` and + VL_PR(). Added VL_DET() (Detection Error Trade-off (DET) + curves). Improved the verbosity control to AIB. Added support for + Xcode 4.3, improved support for past and future Xcode + versions. Completed the migration of the old test code in + `toolbox/test`, moving the functionality to the new unit tests + `toolbox/xtest`. +- **0.9.14** Added SLIC superpixels. Added VL_ALPHANUM(). Improved + Windows binary package and added support for Visual + Studio 2010. Improved the documentation layout and added a proper + bibliography. Bugfixes and other minor improvements. Moved from the + GPL to the less restrictive BSD license. +- **0.9.13** Fixed Windows binary package. +- **0.9.12** Fixes `vl_compile` and the architecture string on Linux 32 bit. +- **0.9.11** Fixes a compatibility problem on older Mac OS X versions. + A few bugfixes are included too. +- **0.9.10** Improves the homogeneous kernel map. Plenty of small + tweaks and improvements. Make maci64 the default architecture on the + Mac. +- **0.9.9** Added: sift matching example. Extended Caltech-101 + classification example to use kd-trees. +- **0.9.8** Added: image distance transform, PEGASOS, floating point + K-means, homogeneous kernel maps, a Caltech-101 classification + example. Improved documentation. +- **0.9.7** Changed the Mac OS X binary distribution to require a less + recent version of Mac OS X (10.5). +- **0.9.6** Changed the GNU/Linux binary distribution to require a + less recent version of the C library. +- **0.9.5** Added kd-tree and new SSE-accelerated vector/histogram + comparison code. Improved dense SIFT (dsift) implementation. Added + Snow Leopard and MATLAB R2009b support. +- **0.9.4** Added quick shift. Renamed dhog to dsift and improved + implementation and documentation. Improved tutorials. Added 64 bit + Windows binaries. Many other small changes. +- **0.9.3** Namespace change (everything begins with a vl_ prefix + now). Many other changes to provide compilation support on Windows + with MATLAB 7. +- **beta-3** Completes to the ikmeans code. +- **beta-2** Many additions. +- **beta-1** Initial public release. diff --git a/vlfeat-0.9.21/apps/phow_caltech101.m b/vlfeat-0.9.21/apps/phow_caltech101.m new file mode 100644 index 0000000..df90581 --- /dev/null +++ b/vlfeat-0.9.21/apps/phow_caltech101.m @@ -0,0 +1,320 @@ +function phow_caltech101() +% PHOW_CALTECH101 Image classification in the Caltech-101 dataset +% This program demonstrates how to use VLFeat to construct an image +% classifier on the Caltech-101 data. The classifier uses PHOW +% features (dense SIFT), spatial histograms of visual words, and a +% Chi2 SVM. To speedup computation it uses VLFeat fast dense SIFT, +% kd-trees, and homogeneous kernel map. The program also +% demonstrates VLFeat PEGASOS SVM solver, although for this small +% dataset other solvers such as LIBLINEAR can be more efficient. +% +% By default 15 training images are used, which should result in +% about 64% performance (a good performance considering that only a +% single feature type is being used). +% +% Call PHOW_CALTECH101 to train and test a classifier on a small +% subset of the Caltech-101 data. Note that the program +% automatically downloads a copy of the Caltech-101 data from the +% Internet if it cannot find a local copy. +% +% Edit the PHOW_CALTECH101 file to change the program configuration. +% +% To run on the entire dataset change CONF.TINYPROBLEM to FALSE. +% +% The Caltech-101 data is saved into CONF.CALDIR, which defaults to +% 'data/caltech-101'. Change this path to the desired location, for +% instance to point to an existing copy of the Caltech-101 data. +% +% The program can also be used to train a model on custom data by +% pointing CONF.CALDIR to it. Just create a subdirectory for each +% class and put the training images there. Make sure to adjust +% CONF.NUMTRAIN accordingly. +% +% Intermediate files are stored in the directory CONF.DATADIR. All +% such files begin with the prefix CONF.PREFIX, which can be changed +% to test different parameter settings without overriding previous +% results. +% +% The program saves the trained model in +% /-model.mat. This model can be used to +% test novel images independently of the Caltech data. +% +% load('data/baseline-model.mat') ; # change to the model path +% label = model.classify(model, im) ; +% + +% Author: Andrea Vedaldi + +% Copyright (C) 2011-2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +conf.calDir = 'data/caltech-101' ; +conf.dataDir = 'data/' ; +conf.autoDownloadData = true ; +conf.numTrain = 15 ; +conf.numTest = 15 ; +conf.numClasses = 102 ; +conf.numWords = 600 ; +conf.numSpatialX = [2 4] ; +conf.numSpatialY = [2 4] ; +conf.quantizer = 'kdtree' ; +conf.svm.C = 10 ; + +conf.svm.solver = 'sdca' ; +%conf.svm.solver = 'sgd' ; +%conf.svm.solver = 'liblinear' ; + +conf.svm.biasMultiplier = 1 ; +conf.phowOpts = {'Step', 3} ; +conf.clobber = false ; +conf.tinyProblem = true ; +conf.prefix = 'baseline' ; +conf.randSeed = 1 ; + +if conf.tinyProblem + conf.prefix = 'tiny' ; + conf.numClasses = 5 ; + conf.numSpatialX = 2 ; + conf.numSpatialY = 2 ; + conf.numWords = 300 ; + conf.phowOpts = {'Verbose', 2, 'Sizes', 7, 'Step', 5} ; +end + +conf.vocabPath = fullfile(conf.dataDir, [conf.prefix '-vocab.mat']) ; +conf.histPath = fullfile(conf.dataDir, [conf.prefix '-hists.mat']) ; +conf.modelPath = fullfile(conf.dataDir, [conf.prefix '-model.mat']) ; +conf.resultPath = fullfile(conf.dataDir, [conf.prefix '-result']) ; + +randn('state',conf.randSeed) ; +rand('state',conf.randSeed) ; +vl_twister('state',conf.randSeed) ; + +% -------------------------------------------------------------------- +% Download Caltech-101 data +% -------------------------------------------------------------------- + +if ~exist(conf.calDir, 'dir') || ... + (~exist(fullfile(conf.calDir, 'airplanes'),'dir') && ... + ~exist(fullfile(conf.calDir, '101_ObjectCategories', 'airplanes'))) + if ~conf.autoDownloadData + error(... + ['Caltech-101 data not found. ' ... + 'Set conf.autoDownloadData=true to download the required data.']) ; + end + vl_xmkdir(conf.calDir) ; + calUrl = ['http://www.vision.caltech.edu/Image_Datasets/' ... + 'Caltech101/101_ObjectCategories.tar.gz'] ; + fprintf('Downloading Caltech-101 data to ''%s''. This will take a while.', conf.calDir) ; + untar(calUrl, conf.calDir) ; +end + +if ~exist(fullfile(conf.calDir, 'airplanes'),'dir') + conf.calDir = fullfile(conf.calDir, '101_ObjectCategories') ; +end + +% -------------------------------------------------------------------- +% Setup data +% -------------------------------------------------------------------- +classes = dir(conf.calDir) ; +classes = classes([classes.isdir]) ; +classes = {classes(3:conf.numClasses+2).name} ; + +images = {} ; +imageClass = {} ; +for ci = 1:length(classes) + ims = dir(fullfile(conf.calDir, classes{ci}, '*.jpg'))' ; + ims = vl_colsubset(ims, conf.numTrain + conf.numTest) ; + ims = cellfun(@(x)fullfile(classes{ci},x),{ims.name},'UniformOutput',false) ; + images = {images{:}, ims{:}} ; + imageClass{end+1} = ci * ones(1,length(ims)) ; +end +selTrain = find(mod(0:length(images)-1, conf.numTrain+conf.numTest) < conf.numTrain) ; +selTest = setdiff(1:length(images), selTrain) ; +imageClass = cat(2, imageClass{:}) ; + +model.classes = classes ; +model.phowOpts = conf.phowOpts ; +model.numSpatialX = conf.numSpatialX ; +model.numSpatialY = conf.numSpatialY ; +model.quantizer = conf.quantizer ; +model.vocab = [] ; +model.w = [] ; +model.b = [] ; +model.classify = @classify ; + +% -------------------------------------------------------------------- +% Train vocabulary +% -------------------------------------------------------------------- + +if ~exist(conf.vocabPath) || conf.clobber + + % Get some PHOW descriptors to train the dictionary + selTrainFeats = vl_colsubset(selTrain, 30) ; + descrs = {} ; + %for ii = 1:length(selTrainFeats) + parfor ii = 1:length(selTrainFeats) + im = imread(fullfile(conf.calDir, images{selTrainFeats(ii)})) ; + im = standarizeImage(im) ; + [drop, descrs{ii}] = vl_phow(im, model.phowOpts{:}) ; + end + + descrs = vl_colsubset(cat(2, descrs{:}), 10e4) ; + descrs = single(descrs) ; + + % Quantize the descriptors to get the visual words + vocab = vl_kmeans(descrs, conf.numWords, 'verbose', 'algorithm', 'elkan', 'MaxNumIterations', 50) ; + save(conf.vocabPath, 'vocab') ; +else + load(conf.vocabPath) ; +end + +model.vocab = vocab ; + +if strcmp(model.quantizer, 'kdtree') + model.kdtree = vl_kdtreebuild(vocab) ; +end + +% -------------------------------------------------------------------- +% Compute spatial histograms +% -------------------------------------------------------------------- + +if ~exist(conf.histPath) || conf.clobber + hists = {} ; + parfor ii = 1:length(images) + % for ii = 1:length(images) + fprintf('Processing %s (%.2f %%)\n', images{ii}, 100 * ii / length(images)) ; + im = imread(fullfile(conf.calDir, images{ii})) ; + hists{ii} = getImageDescriptor(model, im); + end + + hists = cat(2, hists{:}) ; + save(conf.histPath, 'hists') ; +else + load(conf.histPath) ; +end + +% -------------------------------------------------------------------- +% Compute feature map +% -------------------------------------------------------------------- + +psix = vl_homkermap(hists, 1, 'kchi2', 'gamma', .5) ; + +% -------------------------------------------------------------------- +% Train SVM +% -------------------------------------------------------------------- + +if ~exist(conf.modelPath) || conf.clobber + switch conf.svm.solver + case {'sgd', 'sdca'} + lambda = 1 / (conf.svm.C * length(selTrain)) ; + w = [] ; + parfor ci = 1:length(classes) + perm = randperm(length(selTrain)) ; + fprintf('Training model for class %s\n', classes{ci}) ; + y = 2 * (imageClass(selTrain) == ci) - 1 ; + [w(:,ci) b(ci) info] = vl_svmtrain(psix(:, selTrain(perm)), y(perm), lambda, ... + 'Solver', conf.svm.solver, ... + 'MaxNumIterations', 50/lambda, ... + 'BiasMultiplier', conf.svm.biasMultiplier, ... + 'Epsilon', 1e-3); + end + + case 'liblinear' + svm = train(imageClass(selTrain)', ... + sparse(double(psix(:,selTrain))), ... + sprintf(' -s 3 -B %f -c %f', ... + conf.svm.biasMultiplier, conf.svm.C), ... + 'col') ; + w = svm.w(:,1:end-1)' ; + b = svm.w(:,end)' ; + end + + model.b = conf.svm.biasMultiplier * b ; + model.w = w ; + + save(conf.modelPath, 'model') ; +else + load(conf.modelPath) ; +end + +% -------------------------------------------------------------------- +% Test SVM and evaluate +% -------------------------------------------------------------------- + +% Estimate the class of the test images +scores = model.w' * psix + model.b' * ones(1,size(psix,2)) ; +[drop, imageEstClass] = max(scores, [], 1) ; + +% Compute the confusion matrix +idx = sub2ind([length(classes), length(classes)], ... + imageClass(selTest), imageEstClass(selTest)) ; +confus = zeros(length(classes)) ; +confus = vl_binsum(confus, ones(size(idx)), idx) ; + +% Plots +figure(1) ; clf; +subplot(1,2,1) ; +imagesc(scores(:,[selTrain selTest])) ; title('Scores') ; +set(gca, 'ytick', 1:length(classes), 'yticklabel', classes) ; +subplot(1,2,2) ; +imagesc(confus) ; +title(sprintf('Confusion matrix (%.2f %% accuracy)', ... + 100 * mean(diag(confus)/conf.numTest) )) ; +print('-depsc2', [conf.resultPath '.ps']) ; +save([conf.resultPath '.mat'], 'confus', 'conf') ; + +% ------------------------------------------------------------------------- +function im = standarizeImage(im) +% ------------------------------------------------------------------------- + +im = im2single(im) ; +if size(im,1) > 480, im = imresize(im, [480 NaN]) ; end + +% ------------------------------------------------------------------------- +function hist = getImageDescriptor(model, im) +% ------------------------------------------------------------------------- + +im = standarizeImage(im) ; +width = size(im,2) ; +height = size(im,1) ; +numWords = size(model.vocab, 2) ; + +% get PHOW features +[frames, descrs] = vl_phow(im, model.phowOpts{:}) ; + +% quantize local descriptors into visual words +switch model.quantizer + case 'vq' + [drop, binsa] = min(vl_alldist(model.vocab, single(descrs)), [], 1) ; + case 'kdtree' + binsa = double(vl_kdtreequery(model.kdtree, model.vocab, ... + single(descrs), ... + 'MaxComparisons', 50)) ; +end + +for i = 1:length(model.numSpatialX) + binsx = vl_binsearch(linspace(1,width,model.numSpatialX(i)+1), frames(1,:)) ; + binsy = vl_binsearch(linspace(1,height,model.numSpatialY(i)+1), frames(2,:)) ; + + % combined quantization + bins = sub2ind([model.numSpatialY(i), model.numSpatialX(i), numWords], ... + binsy,binsx,binsa) ; + hist = zeros(model.numSpatialY(i) * model.numSpatialX(i) * numWords, 1) ; + hist = vl_binsum(hist, ones(size(bins)), bins) ; + hists{i} = single(hist / sum(hist)) ; +end +hist = cat(1,hists{:}) ; +hist = hist / sum(hist) ; + +% ------------------------------------------------------------------------- +function [className, score] = classify(model, im) +% ------------------------------------------------------------------------- + +hist = getImageDescriptor(model, im) ; +psix = vl_homkermap(hist, 1, 'kchi2', 'gamma', .5) ; +scores = model.w' * psix + model.b' ; +[score, best] = max(scores) ; +className = model.classes{best} ; diff --git a/vlfeat-0.9.21/apps/recognition/encodeImage.m b/vlfeat-0.9.21/apps/recognition/encodeImage.m new file mode 100644 index 0000000..b10abbb --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/encodeImage.m @@ -0,0 +1,155 @@ +function descrs = encodeImage(encoder, im, varargin) +% ENCODEIMAGE Apply an encoder to an image +% DESCRS = ENCODEIMAGE(ENCODER, IM) applies the ENCODER +% to image IM, returning a corresponding code vector PSI. +% +% IM can be an image, the path to an image, or a cell array of +% the same, to operate on multiple images. +% +% ENCODEIMAGE(ENCODER, IM, CACHE) utilizes the specified CACHE +% directory to store encodings for the given images. The cache +% is used only if the images are specified as file names. +% +% See also: TRAINENCODER(). + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.cacheDir = [] ; +opts.cacheChunkSize = 512 ; +opts = vl_argparse(opts,varargin) ; + +if ~iscell(im), im = {im} ; end + +% break the computation into cached chunks +startTime = tic ; +descrs = cell(1, numel(im)) ; +numChunks = ceil(numel(im) / opts.cacheChunkSize) ; + +for c = 1:numChunks + n = min(opts.cacheChunkSize, numel(im) - (c-1)*opts.cacheChunkSize) ; + chunkPath = fullfile(opts.cacheDir, sprintf('chunk-%03d.mat',c)) ; + if ~isempty(opts.cacheDir) && exist(chunkPath) + fprintf('%s: loading descriptors from %s\n', mfilename, chunkPath) ; + load(chunkPath, 'data') ; + else + range = (c-1)*opts.cacheChunkSize + (1:n) ; + fprintf('%s: processing a chunk of %d images (%3d of %3d, %5.1fs to go)\n', ... + mfilename, numel(range), ... + c, numChunks, toc(startTime) / (c - 1) * (numChunks - c + 1)) ; + data = processChunk(encoder, im(range)) ; + if ~isempty(opts.cacheDir) + save(chunkPath, 'data') ; + end + end + descrs{c} = data ; + clear data ; +end +descrs = cat(2,descrs{:}) ; + +% -------------------------------------------------------------------- +function psi = processChunk(encoder, im) +% -------------------------------------------------------------------- +psi = cell(1,numel(im)) ; +if numel(im) > 1 & matlabpool('size') > 1 + parfor i = 1:numel(im) + psi{i} = encodeOne(encoder, im{i}) ; + end +else + % avoiding parfor makes debugging easier + for i = 1:numel(im) + psi{i} = encodeOne(encoder, im{i}) ; + end +end +psi = cat(2, psi{:}) ; + +% -------------------------------------------------------------------- +function psi = encodeOne(encoder, im) +% -------------------------------------------------------------------- + +im = encoder.readImageFn(im) ; + +features = encoder.extractorFn(im) ; + +imageSize = size(im) ; +psi = {} ; +for i = 1:size(encoder.subdivisions,2) + minx = encoder.subdivisions(1,i) * imageSize(2) ; + miny = encoder.subdivisions(2,i) * imageSize(1) ; + maxx = encoder.subdivisions(3,i) * imageSize(2) ; + maxy = encoder.subdivisions(4,i) * imageSize(1) ; + + ok = ... + minx <= features.frame(1,:) & features.frame(1,:) < maxx & ... + miny <= features.frame(2,:) & features.frame(2,:) < maxy ; + + descrs = encoder.projection * bsxfun(@minus, ... + features.descr(:,ok), ... + encoder.projectionCenter) ; + if encoder.renormalize + descrs = bsxfun(@times, descrs, 1./max(1e-12, sqrt(sum(descrs.^2)))) ; + end + + w = size(im,2) ; + h = size(im,1) ; + frames = features.frame(1:2,:) ; + frames = bsxfun(@times, bsxfun(@minus, frames, [w;h]/2), 1./[w;h]) ; + + descrs = extendDescriptorsWithGeometry(encoder.geometricExtension, frames, descrs) ; + + switch encoder.type + case 'bovw' + [words,distances] = vl_kdtreequery(encoder.kdtree, encoder.words, ... + descrs, ... + 'MaxComparisons', 100) ; + z = vl_binsum(zeros(encoder.numWords,1), 1, double(words)) ; + z = sqrt(z) ; + + case 'fv' + z = vl_fisher(descrs, ... + encoder.means, ... + encoder.covariances, ... + encoder.priors, ... + 'Improved') ; + case 'vlad' + [words,distances] = vl_kdtreequery(encoder.kdtree, encoder.words, ... + descrs, ... + 'MaxComparisons', 15) ; + assign = zeros(encoder.numWords, numel(words), 'single') ; + assign(sub2ind(size(assign), double(words), 1:numel(words))) = 1 ; + z = vl_vlad(descrs, ... + encoder.words, ... + assign, ... + 'SquareRoot', ... + 'NormalizeComponents') ; + end + z = z / max(sqrt(sum(z.^2)), 1e-12) ; + psi{i} = z(:) ; +end +psi = cat(1, psi{:}) ; + +% -------------------------------------------------------------------- +function psi = getFromCache(name, cache) +% -------------------------------------------------------------------- +[drop, name] = fileparts(name) ; +cachePath = fullfile(cache, [name '.mat']) ; +if exist(cachePath, 'file') + data = load(cachePath) ; + psi = data.psi ; +else + psi = [] ; +end + +% -------------------------------------------------------------------- +function storeToCache(name, cache, psi) +% -------------------------------------------------------------------- +[drop, name] = fileparts(name) ; +cachePath = fullfile(cache, [name '.mat']) ; +vl_xmkdir(cache) ; +data.psi = psi ; +save(cachePath, '-STRUCT', 'data') ; diff --git a/vlfeat-0.9.21/apps/recognition/experiments.m b/vlfeat-0.9.21/apps/recognition/experiments.m new file mode 100644 index 0000000..789fcac --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/experiments.m @@ -0,0 +1,237 @@ +function experiments() +% EXPERIMENTS Run image classification experiments +% The experimens download a number of benchmark datasets in the +% 'data/' subfolder. Make sure that there are several GBs of +% space available. +% +% By default, experiments run with a lite option turned on. This +% quickly runs all of them on tiny subsets of the actual data. +% This is used only for testing; to run the actual experiments, +% set the lite variable to false. +% +% Running all the experiments is a slow process. Using parallel +% MATLAB and several cores/machiens is suggested. + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +lite = true ; +clear ex ; + +ex(1).prefix = 'fv-aug' ; +ex(1).trainOpts = {'C', 10} ; +ex(1).datasets = {'fmd', 'scene67'} ; +ex(1).seed = 1 ; +ex(1).opts = {... + 'type', 'fv', ... + 'numWords', 256, ... + 'layouts', {'1x1'}, ... + 'geometricExtension', 'xy', ... + 'numPcaDimensions', 80, ... + 'extractorFn', @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(1:-.5:-3))}; + +ex(2) = ex(1) ; +ex(2).datasets = {'caltech101'} ; +ex(2).opts{end} = @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(0:-.5:-3)) ; + +ex(3) = ex(1) ; +ex(3).datasets = {'voc07'} ; +ex(3).C = 1 ; + +ex(4) = ex(1) ; +ex(4).prefix = 'vlad-aug' ; +ex(4).opts = {... + 'type', 'vlad', ... + 'numWords', 256, ... + 'layouts', {'1x1'}, ... + 'geometricExtension', 'xy', ... + 'numPcaDimensions', 100, ... + 'whitening', true, ... + 'whiteningRegul', 0.01, ... + 'renormalize', true, ... + 'extractorFn', @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(1:-.5:-3))}; +ex(5) = ex(4) ; +ex(5).datasets = {'caltech101'} ; +ex(5).opts{end} = ex(2).opts{end} ; + +ex(6) = ex(4) ; +ex(6).datasets = {'voc07'} ; +ex(6).C = 1 ; + +ex(7) = ex(1) ; +ex(7).prefix = 'bovw-aug' ; +ex(7).opts = {... + 'type', 'bovw', ... + 'numWords', 4096, ... + 'layouts', {'1x1'}, ... + 'geometricExtension', 'xy', ... + 'numPcaDimensions', 100, ... + 'whitening', true, ... + 'whiteningRegul', 0.01, ... + 'renormalize', true, ... + 'extractorFn', @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(1:-.5:-3))}; + +ex(8) = ex(7) ; +ex(8).datasets = {'caltech101'} ; +ex(8).opts{end} = ex(2).opts{end} ; + +ex(9) = ex(7) ; +ex(9).datasets = {'voc07'} ; +ex(9).C = 1 ; + +ex(10).prefix = 'fv' ; +ex(10).trainOpts = {'C', 10} ; +ex(10).datasets = {'fmd', 'scene67'} ; +ex(10).seed = 1 ; +ex(10).opts = {... + 'type', 'fv', ... + 'numWords', 256, ... + 'layouts', {'1x1'}, ... + 'geometricExtension', 'none', ... + 'numPcaDimensions', 80, ... + 'extractorFn', @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(1:-.5:-3))}; + +ex(11) = ex(10) ; +ex(11).datasets = {'caltech101'} ; +ex(11).opts{end} = @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(0:-.5:-3)) ; + +ex(12) = ex(10) ; +ex(12).datasets = {'voc07'} ; +ex(12).C = 1 ; + + +ex(13).prefix = 'fv-sp' ; +ex(13).trainOpts = {'C', 10} ; +ex(13).datasets = {'fmd', 'scene67'} ; +ex(13).seed = 1 ; +ex(13).opts = {... + 'type', 'fv', ... + 'numWords', 256, ... + 'layouts', {'1x1', '3x1'}, ... + 'geometricExtension', 'none', ... + 'numPcaDimensions', 80, ... + 'extractorFn', @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(1:-.5:-3))}; + +ex(14) = ex(13) ; +ex(14).datasets = {'caltech101'} ; +ex(14).opts{6} = {'1x1', '2x2'} ; +ex(14).opts{end} = @(x) getDenseSIFT(x, ... + 'step', 4, ... + 'scales', 2.^(0:-.5:-3)) ; + +ex(15) = ex(13) ; +ex(15).datasets = {'voc07'} ; +ex(15).C = 1 ; + + +if lite, tag = 'lite' ; +else, tag = 'ex' ; end + +for i=1:numel(ex) + for j=1:numel(ex(i).datasets) + dataset = ex(i).datasets{j} ; + if ~isfield(ex(i), 'trainOpts') || ~iscell(ex(i).trainOpts) + ex(i).trainOpts = {} ; + end + traintest(... + 'prefix', [tag '-' dataset '-' ex(i).prefix], ... + 'seed', ex(i).seed, ... + 'dataset', char(dataset), ... + 'datasetDir', fullfile('data', dataset), ... + 'lite', lite, ... + ex(i).trainOpts{:}, ... + 'encoderParams', ex(i).opts) ; + end +end + +% print HTML table +pf('\n') ; +ph('method', 'VOC07', 'Caltech 101', 'Scene 67', 'FMD') ; +pr('FV', ... + ge([tag '-voc07-fv'],'ap11'), ... + ge([tag '-caltech101-fv']), ... + ge([tag '-scene67-fv']), ... + ge([tag '-fmd-fv'])) ; +pr('FV + aug.', ... + ge([tag '-voc07-fv-aug'],'ap11'), ... + ge([tag '-caltech101-fv-aug']), ... + ge([tag '-scene67-fv-aug']), ... + ge([tag '-fmd-fv-aug'])) ; +pr('FV + s.p.', ... + ge([tag '-voc07-fv-sp'],'ap11'), ... + ge([tag '-caltech101-fv-sp']), ... + ge([tag '-scene67-fv-sp']), ... + ge([tag '-fmd-fv-sp'])) ; +%pr('VLAD', ... +% ge([tag '-voc07-vlad'],'ap11'), ... +% ge([tag '-caltech101-vlad']), ... +% ge([tag '-scene67-vlad']), ... +% ge([tag '-fmd-vlad'])) ; +pr('VLAD + aug.', ... + ge([tag '-voc07-vlad-aug'],'ap11'), ... + ge([tag '-caltech101-vlad-aug']), ... + ge([tag '-scene67-vlad-aug']), ... + ge([tag '-fmd-vlad-aug'])) ; +%pr('VLAD+sp', ... +% ge([tag '-voc07-vlad-sp'],'ap11'), ... +% ge([tag '-caltech101-vlad-sp']), ... +% ge([tag '-scene67-vlad-sp']), ... +% ge([tag '-fmd-vlad-sp'])) ; +%pr('BOVW', ... +% ge([tag '-voc07-bovw'],'ap11'), ... +% ge([tag '-caltech101-bovw']), ... +% ge([tag '-scene67-bovw']), ... +% ge([tag '-fmd-bovw'])) ; +pr('BOVW + aug.', ... + ge([tag '-voc07-bovw-aug'],'ap11'), ... + ge([tag '-caltech101-bovw-aug']), ... + ge([tag '-scene67-bovw-aug']), ... + ge([tag '-fmd-bovw-aug'])) ; +%pr('BOVW+sp', ... +% ge([tag '-voc07-bovw-sp'],'ap11'), ... +% ge([tag '-caltech101-bovw-sp']), ... +% ge([tag '-scene67-bovw-sp']), ... +% ge([tag '-fmd-bovw-sp'])) ; +pf('
\n'); + +function pf(str) +fprintf(str) ; + +function str = ge(name, format) +if nargin == 1, format = 'acc'; end +data = load(fullfile('data', name, 'result.mat')) ; +switch format + case 'acc' + str = sprintf('%.2f%% Acc', mean(diag(data.confusion)) * 100) ; + case 'ap11' + str = sprintf('%.2f%% mAP', mean(data.ap11) * 100) ; +end + +function pr(varargin) +fprintf('') ; +for i=1:numel(varargin), fprintf('%s',varargin{i}) ; end +fprintf('\n') ; + +function ph(varargin) +fprintf('') ; +for i=1:numel(varargin), fprintf('%s',varargin{i}) ; end +fprintf('\n') ; diff --git a/vlfeat-0.9.21/apps/recognition/extendDescriptorsWithGeometry.m b/vlfeat-0.9.21/apps/recognition/extendDescriptorsWithGeometry.m new file mode 100644 index 0000000..44e4b4e --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/extendDescriptorsWithGeometry.m @@ -0,0 +1,24 @@ +function descrs = extendDescriptorsWithGeometry(type, frames, descrs) +% EXTENDDESCRIPTORSWITHGEOMETRY Extend feature descriptors with geometric components +% DESCRS = EXTENDDESCRIPTORSWITHGEOMETRY(TYPE, FRAMES, DESCRS) +% extends the descriptorss DESCRS with either nothing (TYPE = +% 'none') or XY (TYPE = 'xy') from the FRAMES matrix. Note that, +% for this to make sense, DESCRS and FRAMES should be properly normalized. + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + + +switch lower(type) + case 'none' + case 'xy' + z = frames(1:2,:) ; + descrs = cat(1, descrs, z) ; + otherwise + error('Uknown geometric extension ''%s''.', type) ; +end diff --git a/vlfeat-0.9.21/apps/recognition/getDenseSIFT.m b/vlfeat-0.9.21/apps/recognition/getDenseSIFT.m new file mode 100644 index 0000000..8aff60e --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/getDenseSIFT.m @@ -0,0 +1,61 @@ +function features = getDenseSIFT(im, varargin) +% GETDENSESIFT Extract dense SIFT features +% FEATURES = GETDENSESIFT(IM) extract dense SIFT features from +% image IM. + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.scales = logspace(log10(1), log10(.25), 5) ; +opts.contrastthreshold = 0 ; +opts.step = 3 ; +opts.rootSift = false ; +opts.normalizeSift = true ; +opts.binSize = 8 ; +opts.geometry = [4 4 8] ; +opts.sigma = 0 ; +opts = vl_argparse(opts, varargin) ; + +dsiftOpts = {'norm', 'fast', 'floatdescriptors', ... + 'step', opts.step, ... + 'size', opts.binSize, ... + 'geometry', opts.geometry} ; + +if size(im,3)>1, im = rgb2gray(im) ; end +im = im2single(im) ; +im = vl_imsmooth(im, opts.sigma) ; + +for si = 1:numel(opts.scales) + im_ = imresize(im, opts.scales(si)) ; + + [frames{si}, descrs{si}] = vl_dsift(im_, dsiftOpts{:}) ; + + % root SIFT + if opts.rootSift + descrs{si} = sqrt(descrs{si}) ; + end + if opts.normalizeSift + descrs{si} = snorm(descrs{si}) ; + end + + % zero low contrast descriptors + info.contrast{si} = frames{si}(3,:) ; + kill = info.contrast{si} < opts.contrastthreshold ; + descrs{si}(:,kill) = 0 ; + + % store frames + frames{si}(1:2,:) = (frames{si}(1:2,:)-1) / opts.scales(si) + 1 ; + frames{si}(3,:) = opts.binSize / opts.scales(si) / 3 ; +end + +features.frame = cat(2, frames{:}) ; +features.descr = cat(2, descrs{:}) ; +features.contrast = cat(2, info.contrast{:}) ; + +function x = snorm(x) +x = bsxfun(@times, x, 1./max(1e-5,sqrt(sum(x.^2,1)))) ; diff --git a/vlfeat-0.9.21/apps/recognition/readImage.m b/vlfeat-0.9.21/apps/recognition/readImage.m new file mode 100644 index 0000000..627e9d8 --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/readImage.m @@ -0,0 +1,37 @@ +function [im, scale] = readImage(imagePath) +% READIMAGE Read and standardize image +% [IM, SCALE] = READIMAGE(IMAGEPATH) reads the specified image file, +% converts the result to SINGLE class, and rescales the image +% to have a maximum height of 480 pixels, returing the corresponding +% scaling factor SCALE. +% +% READIMAGE(IM) where IM is already an image applies only the +% standardization to it. + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +if ischar(imagePath) + try + im = imread(imagePath) ; + catch + error('Corrupted image %s', imagePath) ; + end +else + im = imagePath ; +end + +im = im2single(im) ; + +scale = 1 ; +if (size(im,1) > 480) + scale = 480 / size(im,1) ; + im = imresize(im, scale) ; + im = min(max(im,0),1) ; +end + diff --git a/vlfeat-0.9.21/apps/recognition/setupCaltech256.m b/vlfeat-0.9.21/apps/recognition/setupCaltech256.m new file mode 100644 index 0000000..cd4921d --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/setupCaltech256.m @@ -0,0 +1,78 @@ +function imdb = setupCaltech256(datasetDir, varargin) +% SETUPCALTECH256 Setup Caltech 256 and 101 datasets +% This is similar to SETUPGENERIC(), with modifications to setup +% Caltech-101 and Caltech-256 according to the standard +% evaluation protocols. Specific options include: +% +% Variant:: 'caltech256' +% Either 'caltech101' or 'caltech256'. +% +% AutoDownload:: true +% Automatically download the data from the Internet if not +% found at DATASETDIR. +% +% See:: SETUPGENERIC(). + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.lite = false ; +opts.numTrain = 30 ; +opts.numTest = 25 ; +opts.seed = 1 ; +opts.variant = 'caltech256' ; +opts.autoDownload = true ; +opts = vl_argparse(opts, varargin) ; + +% Download and unpack +vl_xmkdir(datasetDir) ; +switch opts.variant + case 'caltech101' + name = '101_ObjectCategories' ; + checkClassName = 'airplanes' ; + url = 'http://www.vision.caltech.edu/Image_Datasets/Caltech101/101_ObjectCategories.tar.gz' ; + numClasses = 102 ; + case 'caltech256' + name = '256_ObjectCategories' ; + checkClassName = '001.ak47' ; + url = 'http://www.vision.caltech.edu/Image_Datasets/Caltech256/256_ObjectCategories.tar' ; + numClasses = 257 ; + otherwise + error('Uknown dataset variant ''%s''.', opts.variant) ; +end + +if exist(fullfile(datasetDir, checkClassName), 'file') + % ok +elseif exist(fullfile(datasetDir, name, checkClassName), 'file') + datasetDir = fullfile(datasetDir, name) ; +elseif opts.autoDownload + fprintf('Downloading %s data to ''%s''. This will take a while.', opts.variant, datasetDir) ; + untar(url, datasetDir) ; + datasetDir = fullfile(datasetDir, name) ; +else + error('Could not find %s dataset in ''%s''', opts.variant, datasetDir) ; +end + +% Read classes +imdb = setupGeneric(datasetDir, ... + 'numTrain', opts.numTrain, 'numVal', 0, 'numTest', opts.numTest, ... + 'expectedNumClasses', numClasses, ... + 'seed', opts.seed, 'lite', opts.lite) ; + +% In Caltech 256 background is not evaluated +switch opts.variant + case 'caltech101' + case 'caltech256' + imdb.images.set(imdb.images.class == 257) = 0 ; + ok = find(imdb.images.set ~= 0) ; + imdb.images.id = imdb.images.id(ok) ; + imdb.images.name = imdb.images.name(ok) ; + imdb.images.set = imdb.images.set(ok) ; + imdb.images.class = imdb.images.class(ok) ; +end + diff --git a/vlfeat-0.9.21/apps/recognition/setupFMD.m b/vlfeat-0.9.21/apps/recognition/setupFMD.m new file mode 100644 index 0000000..4a74322 --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/setupFMD.m @@ -0,0 +1,39 @@ +function imdb = setupFMD(datasetDir, varargin) +% SETUPSCENE67 Setup Flickr Material Dataset +% This is similar to SETUPCALTECH101(), with modifications to setup +% the Flickr Material Dataset accroding to the standard +% evaluation protocols. +% +% See: SETUPCALTECH101(). + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.lite = false ; +opts.seed = 1 ; +opts.numTrain = 50 ; +opts.numTest = 50 ; +opts.autoDownload = true ; +opts = vl_argparse(opts, varargin) ; + +% Download and unpack +vl_xmkdir(datasetDir) ; +if exist(fullfile(datasetDir, 'image', 'wood')) + % ok +elseif opts.autoDownload + url = 'http://people.csail.mit.edu/celiu/CVPR2010/FMD/FMD.zip' ; + fprintf('Downloading FMD data to ''%s''. This will take a while.', datasetDir) ; + unzip(url, datasetDir) ; +else + error('FMD not found in %s', datasetDir) ; +end + +imdb = setupGeneric(fullfile(datasetDir,'image'), ... + 'numTrain', opts.numTrain, 'numVal', 0, 'numTest', opts.numTest, ... + 'expectedNumClasses', 10, ... + 'seed', opts.seed, 'lite', opts.lite) ; diff --git a/vlfeat-0.9.21/apps/recognition/setupGeneric.m b/vlfeat-0.9.21/apps/recognition/setupGeneric.m new file mode 100644 index 0000000..94525be --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/setupGeneric.m @@ -0,0 +1,135 @@ +function imdb = setupGeneric(datasetDir, varargin) +% SETUPGENERIC Setup a Caltech-101-like dataset +% IMDB = SETUPGENERIC(DATASETDIR) initializes a IMDB structure +% representing the dataset located at DATASETDIR. The dataset +% is supposed to be organized similarly to Caltech-101, i.e. +% to have one directory per image class, with a number of +% image files in each directory. +% +% SETUPGENERIC(..., 'OPT', VAL, ...) accepts the following +% options: +% +% Lite:: false +% If set to TRUE, use at most 3 classes and at most 5 images +% in each of TRAIN, VAL, and TEST. +% +% Seed:: 1 +% The random seed used to generate the partitions. +% +% NumTrain:: 50 +% Maximum number of training images per class. +% +% NumVal:: 0 +% Maximum number of validation images per class. +% +% NumTest:: 50 +% Maximum number of test images per class. +% +% ExpectedNumClasses:: [] +% If set to a number, generate an error if the number +% of classes found in DATASETDIR differs. This is only +% used as a sanity check. +% +% IMDB is a structure with the following fields: +% +% IMDB.IMAGES:: +% A structure of arrays representing the images in the +% dataset. +% +% IMDB.IMAGES.ID:: +% Vector of image numeric IDs. +% +% IMDB.IMAGES.NAME:: +% Cell array with the image names. +% +% IMDB.IMAGES.SET:: +% Vector of subset IDs for each image (train, val, test). +% +% IMDB.IMAGES.CLASS:: +% Vector of class IDs for each image. +% +% IMDB.META:: +% A substructure with meta information on the data. +% +% IMDB.META.CLASSES:: +% Cell array of class names. +% +% IMDB.IMAGEDIR:: +% Image directory. Join the image name to this directory to +% access an image file. + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.lite = false ; +opts.numTrain = 50 ; +opts.numVal = 0 ; +opts.numTest = 50 ; +opts.seed = 1 ; +opts.expectedNumClasses = [] ; +opts = vl_argparse(opts, varargin) ; + +% Construct image database imdb structure +imdb.meta.sets = {'train', 'val', 'test'} ; +names = dir(datasetDir) ; +names = {names([names.isdir]).name} ; +names = setdiff(names, {'.', '..'}) ; +imdb.meta.classes = names ; + +names = {} ; +classes = {} ; +for c = 1:numel(imdb.meta.classes) + class = imdb.meta.classes{c} ; + tmp = dir(fullfile(datasetDir, [class filesep '*.jpg'])) ; + names{c} = strcat([class filesep], {tmp.name}) ; + classes{c} = repmat(c, 1, numel(names{c})) ; +end + +names = cat(2,names{:}) ; +classes = cat(2,classes{:}) ; +sets = zeros(1,numel(names)) ; +ids = 1:numel(names) ; + +numClasses = numel(imdb.meta.classes) ; +if ~isempty(opts.expectedNumClasses) && numClasses ~= opts.expectedNumClasses + error('Expected %d classes in image database at %s.', opts.expectedNumClasses, datasetDir) ; +end + +for c = 1:numClasses + sel = find(classes == c) ; + randn('state', opts.seed) ; + rand('state', opts.seed) ; + selTrain = vl_colsubset(sel, opts.numTrain) ; + selVal = vl_colsubset(setdiff(sel, selTrain), opts.numVal) ; + selTest = vl_colsubset(setdiff(sel, [selTrain selVal]), opts.numTest) ; + sets(selTrain) = 1 ; + sets(selVal) = 2 ; + sets(selTest) = 3 ; +end + +ok = find(sets ~= 0) ; +imdb.images.id = ids(ok) ; +imdb.images.name = names(ok) ; +imdb.images.set = sets(ok) ; +imdb.images.class = classes(ok) ; +imdb.imageDir = datasetDir ; + +if opts.lite + ok = {} ; + for c = 1:3 + ok{end+1} = vl_colsubset(find(imdb.images.class == c & imdb.images.set == 1), 5) ; + ok{end+1} = vl_colsubset(find(imdb.images.class == c & imdb.images.set == 2), 5) ; + ok{end+1} = vl_colsubset(find(imdb.images.class == c & imdb.images.set == 3), 5) ; + end + ok = cat(2, ok{:}) ; + imdb.meta.classes = imdb.meta.classes(1:3) ; + imdb.images.id = imdb.images.id(ok) ; + imdb.images.name = imdb.images.name(ok) ; + imdb.images.set = imdb.images.set(ok) ; + imdb.images.class = imdb.images.class(ok) ; +end diff --git a/vlfeat-0.9.21/apps/recognition/setupScene67.m b/vlfeat-0.9.21/apps/recognition/setupScene67.m new file mode 100644 index 0000000..df1d43d --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/setupScene67.m @@ -0,0 +1,65 @@ +function imdb = setupScene67(datasetDir, varargin) +% SETUPSCENE67 Setup MIT Scene 67 dataset +% This is similar to SETUPGENERIC(), with modifications to setup +% MIT Scene 67 according to the standard evaluation protocols. The +% function supports only the LITE option. +% +% See: SETUPGENERIC(). + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.lite = false ; +opts = vl_argparse(opts, varargin) ; + +% Download and unpack +vl_xmkdir(datasetDir) ; +if exist(fullfile(datasetDir, 'Images', 'airport_inside')) + % ok +else + url = 'http://groups.csail.mit.edu/vision/LabelMe/NewImages/indoorCVPR_09.tar' ; + trainImagesUrl = 'http://web.mit.edu/torralba/www/TrainImages.txt' ; + testImagesUrl = 'http://web.mit.edu/torralba/www/TestImages.txt' ; + fprintf('Downloading MIT Scene 67 data to ''%s''. This will take a while.', datasetDir) ; + urlwrite(trainImagesUrl, fullfile(datasetDir, 'TrainImages.txt')) ; + urlwrite(testImagesUrl, fullfile(datasetDir, 'TestImages.txt')) ; + untar(url, datasetDir) ; +end + +% Construct image database imdb structure +imdb.meta.sets = {'train', 'val', 'test'} ; + +trainNames = textread(fullfile(datasetDir, 'TrainImages.txt'),'%s','delimiter','\n') ; +testNames = textread(fullfile(datasetDir, 'TestImages.txt'),'%s','delimiter','\n') ; +names = [trainNames; testNames]' ; +sets = [ones(1,numel(trainNames)), 3*ones(1,numel(testNames))] ; +imdb.images.id = 1:numel(names) ; +[imdb.images.name,perm] = sort(names) ; +imdb.images.set = sets(perm) ; + +a = regexp(imdb.images.name, '^([^/]+)*/.*$', 'tokens') ; +for i = 1:numel(names) + a{i} = a{i}{1}{1} ; +end +[imdb.meta.classes, ~, imdb.images.class] = unique(a) ; +imdb.images.class = imdb.images.class(:)' ; +imdb.imageDir = fullfile(datasetDir, 'Images') ; + +if opts.lite + ok = {} ; + for c = 1:3 + ok{end+1} = vl_colsubset(find(imdb.images.class == c & imdb.images.set == 1), 5) ; + ok{end+1} = vl_colsubset(find(imdb.images.class == c & imdb.images.set == 3), 5) ; + end + ok = cat(2, ok{:}) ; + imdb.meta.classes = imdb.meta.classes(1:3) ; + imdb.images.id = imdb.images.id(ok) ; + imdb.images.name = imdb.images.name(ok) ; + imdb.images.set = imdb.images.set(ok) ; + imdb.images.class = imdb.images.class(ok) ; +end diff --git a/vlfeat-0.9.21/apps/recognition/setupVoc.m b/vlfeat-0.9.21/apps/recognition/setupVoc.m new file mode 100644 index 0000000..7cc36b3 --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/setupVoc.m @@ -0,0 +1,141 @@ +function imdb = setupVoc(datasetDir, varargin) +% SETUPVOC Setup PASCAL VOC data +% IMDB = SETUPVOC(DATASETDIR, 'EDITION', '2007') setups the +% PASCAL VOC 2007 data. This is similar to SETUPGENERIC(), but adapted +% to the peculiarities of this dataset. In particular, the +% difficult image flag and the fact that multiple labels apply to +% each image are supported. +% +% Note that only the PASCAL VOC 2007 data comes with test images +% and labels. For the other editions, setting up the test images +% cannot be automatized due to restrictions in the distribution. +% +% See also: SETUPGENERIC(). + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.edition = '2007' ; +opts.autoDownload = true ; +opts.lite = false ; +opts = vl_argparse(opts, varargin) ; + +switch opts.edition + case '2007' + urls = {'http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCtrainval_06-Nov-2007.tar', ... + 'http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCtest_06-Nov-2007.tar'} ; + case '2008' + urls = {'http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2008/VOCtrainval_14-Jul-2008.tar'} ; + case '2009' + urls = {'http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2009/VOCtrainval_11-May-2009.tar'} ; + case '2010' + urls = {'http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2010/VOCtrainval_03-May-2010.tar'} ; + case '2011' + urls = {'http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2011/VOCtrainval_25-May-2011.tar'} ; + case '2012' + urls = {'http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2012/VOCtrainval_11-May-2012.tar'} ; + otherwise + error('Unknown PASCAL VOC edition ''%s''.', opts.edition) ; +end + +% Download and unpack +vl_xmkdir(datasetDir) ; +if exist(fullfile(datasetDir, ['VOC' opts.edition], 'Annotations')) + % ok +elseif exist(fullfile(datasetDir, 'VOCdevkit', ['VOC' opts.edition], 'Annotations')) + % ok + datasetDir = fullfile(datasetDir, 'VOCdevkit') ; +elseif opts.autoDownload + for i = 1:length(urls) + fprintf('Downloading VOC data ''%s'' to ''%s''. This will take a while.', urls{i}, datasetDir) ; + untar(urls{i}, datasetDir) ; + end + datasetDir = fullfile(datasetDir, 'VOCdevkit') ; +else + error('VOC data not found in %s', datasetDir) ; +end + +imdb.images.id = [] ; +imdb.images.set = uint8([]) ; +imdb.images.name = {} ; +imdb.images.size = zeros(2,0) ; +imdb.meta.sets = {'train', 'val', 'test'} ; +imdb.meta.classes = {'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', ... + 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', ... + 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'} ; +imdb.imageDir = fullfile(datasetDir, ['VOC', opts.edition], 'JPEGImages') ; + +% Get the list of images +map = containers.Map() ; +j = 0 ; +for si = 1:numel(imdb.meta.sets) + setName = imdb.meta.sets{si} ; + annoPath = fullfile(datasetDir, ['VOC' opts.edition], ... + 'ImageSets', 'Main', ... + [setName '.txt']) ; + fprintf('%s: reading %s\n', mfilename, annoPath) ; + [names,labels] = textread(annoPath, '%s %f') ; + for i=1:length(names) + j = j + 1 ; + map(names{i}) = j ; + imdb.images.id(j) = j ; + imdb.images.set(j) = si ; + imdb.images.name{j} = [names{i} '.jpg'] ; + %info = imfinfo(fullfile(imdb.imageDir, imdb.images.name{j})) ; + %imdb.images.size(:,j) = [info.Width ; info.Height] ; + %fprintf('\radded %s', imdb.images.name{j}) ; + end +end + +% Get class labels +for ci = 1:length(imdb.meta.classes) + imdb.classes.imageIds{ci} = [] ; + imdb.classes.difficult{ci} = false(0) ; +end +for si = 1:numel(imdb.meta.sets) + for ci = 1:length(imdb.meta.classes) + setName = imdb.meta.sets{si} ; + className = imdb.meta.classes{ci} ; + annoPath = fullfile(datasetDir, ['VOC' opts.edition], ... + 'ImageSets', 'Main', ... + [className '_' setName '.txt']) ; + fprintf('%s: reading %s\n', mfilename, annoPath) ; + [names,labels] = textread(annoPath, '%s %f') ; + for i = 1:numel(names) + j = map(names{i}) ; + if labels(i) >= 0 + imdb.classes.imageIds{ci}(end+1) = j ; + imdb.classes.difficult{ci}(end+1) = (labels(i) == 0) ; + end + end + end +end + +if opts.lite + ok = {} ; + for c = 1:3 + trainIds = intersect(imdb.images.id(imdb.images.set == 1), imdb.classes.imageIds{c}) ; + testIds = intersect(imdb.images.id(imdb.images.set == 3), imdb.classes.imageIds{c}) ; + + ok{end+1} = vl_colsubset(find(ismember(imdb.images.id, trainIds)), 5) ; + ok{end+1} = vl_colsubset(find(ismember(imdb.images.id, testIds)), 5) ; + end + ok = unique(cat(2, ok{:})) ; + imdb.meta.classes = imdb.meta.classes(1:3) ; + imdb.classes.imageIds = imdb.classes.imageIds(1:3) ; + imdb.classes.difficult = imdb.classes.difficult(1:3) ; + imdb.images.id = imdb.images.id(ok) ; + imdb.images.name = imdb.images.name(ok) ; + imdb.images.set = imdb.images.set(ok) ; + for c = 1:3 + ok = ismember(imdb.classes.imageIds{c}, imdb.images.id) ; + imdb.classes.imageIds{c} = imdb.classes.imageIds{c}(ok) ; + imdb.classes.difficult{c} = imdb.classes.difficult{c}(ok) ; + end +end + diff --git a/vlfeat-0.9.21/apps/recognition/trainEncoder.m b/vlfeat-0.9.21/apps/recognition/trainEncoder.m new file mode 100644 index 0000000..c8dcbfa --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/trainEncoder.m @@ -0,0 +1,209 @@ +function encoder = trainEncoder(images, varargin) +% TRAINENCODER Train image encoder: BoVW, VLAD, FV +% ENCODER = TRAINENCOER(IMAGES) trains a BoVW encoder from the +% specified list of images IMAGES. +% +% TRAINENCODER(..., 'OPT', VAL, ...) accepts the following options: +% +% Type:: 'bovw' +% Bag of visual words ('bovw'), VLAD ('vlad') or Fisher Vector +% ('fv'). +% +% numPcaDimension:: +inf +% Use PCA to reduce the descriptor dimensionality to this +% dimension. Use +inf to deactivate PCA. +% +% Whitening:: false +% Set to true to divide the principal components by the +% corresponding standard deviation s_i. +% +% WhiteningRegul:: 0 +% When using whitening, divide by s_max * WhiteningRegul + s_i +% instead of s_i alone. +% +% Renormalize:: false +% If true, descriptors are L2 normalized after PCA or +% whitening. +% +% +% Subdivisions:: [] +% A list of spatial subdivisions. Each column is a rectangle +% [XMIN YMIN XMAX YMAX]. The spatial subdivisions are +% +% Layouts:: {'1x1'} +% A list of strings representing regular spatial subdivisions +% in the format MxN, where M is the number of vertical +% subdivisions and N the number of horizontal ones. For +% example {'1x1', 2x2'} uses 5 partitions: the whole image and +% four quadrants. The subdivisions are appended to the ones +% specified by the SUBDIVISIONS option. +% +% ReadImageFn:: @readImage +% The function used to load an image. +% +% ExtractorFn:: @getDenseSIFT +% The function used to extract the feature frames and +% descriptors from an image. + +% Author: Andrea Vedaldi + +% Copyright (C) 2013 Andrea Vedaldi +% All rights reserved. +% +% This file is part of the VLFeat library and is made available under +% the terms of the BSD license (see the COPYING file). + +opts.type = 'bovw' ; +opts.numWords = [] ; +opts.seed = 1 ; +opts.numPcaDimensions = +inf ; +opts.whitening = false ; +opts.whiteningRegul = 0 ; +opts.numSamplesPerWord = [] ; +opts.renormalize = false ; +opts.layouts = {'1x1'} ; +opts.geometricExtension = 'none' ; +opts.subdivisions = zeros(4,0) ; +opts.readImageFn = @readImage ; +opts.extractorFn = @getDenseSIFT ; +opts.lite = false ; +opts = vl_argparse(opts, varargin) ; + +for i = 1:numel(opts.layouts) + t = sscanf(opts.layouts{i},'%dx%d') ; + m = t(1) ; + n = t(2) ; + [x,y] = meshgrid(... + linspace(0,1,n+1), ... + linspace(0,1,m+1)) ; + x1 = x(1:end-1,1:end-1) ; + y1 = y(1:end-1,1:end-1) ; + x2 = x(2:end,2:end) ; + y2 = y(2:end,2:end) ; + opts.subdivisions = cat(2, opts.subdivisions, ... + [x1(:)' ; + y1(:)' ; + x2(:)' ; + y2(:)'] ) ; +end + +if isempty(opts.numWords) + switch opts.type + case {'bovw'} + opts.numWords = 1024 ; + case {'fv'} + opts.numWords = 64 ; + opts.numPcaDimensions = 80 ; + case {'vlad'} + opts.numWords = 64 ; + opts.numPcaDimensions = 100 ; + opts.whitening = true ; + opts.whiteninRegul = 0.01 ; + otherwise + assert(false) ; + end +end + +if isempty(opts.numSamplesPerWord) + switch opts.type + case {'bovw'} + opts.numSamplesPerWord = 200 ; + case {'vlad','fv'} + opts.numSamplesPerWord = 1000 ; + otherwise + assert(false) ; + end + if opts.lite + opts.numSamplesPerWord = 10 ; + end +end + +disp(opts) ; + +encoder.type = opts.type ; +encoder.subdivisions = opts.subdivisions ; +encoder.readImageFn = opts.readImageFn ; +encoder.extractorFn = opts.extractorFn ; +encoder.numWords = opts.numWords ; +encoder.renormalize = opts.renormalize ; +encoder.geometricExtension = opts.geometricExtension ; + +%% Step 0: obtain sample image descriptors +numImages = numel(images) ; +numDescrsPerImage = ceil(opts.numWords * opts.numSamplesPerWord / numImages) ; +parfor i = 1:numImages + fprintf('%s: reading: %s\n', mfilename, images{i}) ; + im = encoder.readImageFn(images{i}) ; + w = size(im,2) ; + h = size(im,1) ; + features = encoder.extractorFn(im) ; + randn('state',0) ; + rand('state',0) ; + sel = vl_colsubset(1:size(features.descr,2), single(numDescrsPerImage)) ; + descrs{i} = features.descr(:,sel) ; + frames{i} = features.frame(:,sel) ; + frames{i} = bsxfun(@times, bsxfun(@minus, frames{i}(1:2,:), [w;h]/2), 1./[w;h]) ; +end +descrs = cat(2, descrs{:}) ; +frames = cat(2, frames{:}) ; + +%% Step 1 (optional): learn PCA projection +if opts.numPcaDimensions < inf || opts.whitening + fprintf('%s: learning PCA rotation/projection\n', mfilename) ; + encoder.projectionCenter = mean(descrs,2) ; + x = bsxfun(@minus, descrs, encoder.projectionCenter) ; + X = x*x' / size(x,2) ; + [V,D] = eig(X) ; + d = diag(D) ; + [d,perm] = sort(d,'descend') ; + d = d + opts.whiteningRegul * max(d) ; + m = min(opts.numPcaDimensions, size(descrs,1)) ; + V = V(:,perm) ; + if opts.whitening + encoder.projection = diag(1./sqrt(d(1:m))) * V(:,1:m)' ; + else + encoder.projection = V(:,1:m)' ; + end + clear X V D d ; +else + encoder.projection = 1 ; + encoder.projectionCenter = 0 ; +end +descrs = encoder.projection * bsxfun(@minus, descrs, encoder.projectionCenter) ; +if encoder.renormalize + descrs = bsxfun(@times, descrs, 1./max(1e-12, sqrt(sum(descrs.^2)))) ; +end + + +%% Step 2 (optional): geometrically augment the features + +descrs = extendDescriptorsWithGeometry(opts.geometricExtension, frames, descrs) ; + +%% Step 3: learn a VQ or GMM vocabulary +dimension = size(descrs,1) ; +numDescriptors = size(descrs,2) ; + +switch encoder.type + case {'bovw', 'vlad'} + vl_twister('state', opts.seed) ; + encoder.words = vl_kmeans(descrs, opts.numWords, 'verbose', 'algorithm', 'elkan') ; + encoder.kdtree = vl_kdtreebuild(encoder.words, 'numTrees', 2) ; + + case {'fv'} ; + vl_twister('state', opts.seed) ; + if 1 + v = var(descrs')' ; + [encoder.means, encoder.covariances, encoder.priors] = ... + vl_gmm(descrs, opts.numWords, 'verbose', ... + 'Initialization', 'kmeans', ... + 'CovarianceBound', double(max(v)*0.0001), ... + 'NumRepetitions', 1) ; + else + addpath lib/yael/matlab + [a,b,c] = ... + yael_gmm(descrs, opts.numWords, 'verbose', 2) ; + encoder.priors = single(a) ; + encoder.means = single(b) ; + encoder.covariances = single(c) ; + end +end diff --git a/vlfeat-0.9.21/apps/recognition/traintest.m b/vlfeat-0.9.21/apps/recognition/traintest.m new file mode 100644 index 0000000..21f501c --- /dev/null +++ b/vlfeat-0.9.21/apps/recognition/traintest.m @@ -0,0 +1,185 @@ +function recognition_demo(varargin) +% RECOGNITION_DEMO Demonstrates using VLFeat for image classification + +if ~exist('vl_version') + run(fullfile(fileparts(which(mfilename)), ... + '..', '..', 'toolbox', 'vl_setup.m')) ; +end + +opts.dataset = 'caltech101' ; +opts.prefix = 'bovw' ; +opts.encoderParams = {'type', 'bovw'} ; +opts.seed = 1 ; +opts.lite = true ; +opts.C = 1 ; +opts.kernel = 'linear' ; +opts.dataDir = 'data'; +for pass = 1:2 + opts.datasetDir = fullfile(opts.dataDir, opts.dataset) ; + opts.resultDir = fullfile(opts.dataDir, opts.prefix) ; + opts.imdbPath = fullfile(opts.resultDir, 'imdb.mat') ; + opts.encoderPath = fullfile(opts.resultDir, 'encoder.mat') ; + opts.modelPath = fullfile(opts.resultDir, 'model.mat') ; + opts.diaryPath = fullfile(opts.resultDir, 'diary.txt') ; + opts.cacheDir = fullfile(opts.resultDir, 'cache') ; + opts = vl_argparse(opts,varargin) ; +end + +% do not do anything if the result data already exist +if exist(fullfile(opts.resultDir,'result.mat')), + load(fullfile(opts.resultDir,'result.mat'), 'ap', 'confusion') ; + fprintf('%35s mAP = %04.1f, mean acc = %04.1f\n', opts.prefix, ... + 100*mean(ap), 100*mean(diag(confusion))) ; + return ; +end + +vl_xmkdir(opts.cacheDir) ; +diary(opts.diaryPath) ; diary on ; +disp('options:' ); disp(opts) ; + +% -------------------------------------------------------------------- +% Get image database +% -------------------------------------------------------------------- + +if exist(opts.imdbPath) + imdb = load(opts.imdbPath); +else + switch opts.dataset + case 'scene67', imdb = setupScene67(opts.datasetDir, 'lite', opts.lite) ; + case 'caltech101', imdb = setupCaltech256(opts.datasetDir, 'lite', opts.lite, ... + 'variant', 'caltech101', 'seed', opts.seed) ; + case 'caltech256', imdb = setupCaltech256(opts.datasetDir, 'lite', opts.lite) ; + case 'voc07', imdb = setupVoc(opts.datasetDir, 'lite', opts.lite, 'edition', '2007') ; + case 'fmd', imdb = setupFMD(opts.datasetDir, 'lite', opts.lite) ; + otherwise, error('Unknown dataset type.') ; + end + save(opts.imdbPath, '-struct', 'imdb') ; +end + +% -------------------------------------------------------------------- +% Train encoder and encode images +% -------------------------------------------------------------------- + +if exist(opts.encoderPath) + encoder = load(opts.encoderPath) ; +else + numTrain = 5000 ; + if opts.lite, numTrain = 10 ; end + train = vl_colsubset(find(imdb.images.set <= 2), numTrain, 'uniform') ; + encoder = trainEncoder(fullfile(imdb.imageDir,imdb.images.name(train)), ... + opts.encoderParams{:}, ... + 'lite', opts.lite) ; + save(opts.encoderPath, '-struct', 'encoder') ; + diary off ; + diary on ; +end + +descrs = encodeImage(encoder, fullfile(imdb.imageDir, imdb.images.name), ... + 'cacheDir', opts.cacheDir) ; +diary off ; +diary on ; + +% -------------------------------------------------------------------- +% Train and evaluate models +% -------------------------------------------------------------------- + +if isfield(imdb.images, 'class') + classRange = unique(imdb.images.class) ; +else + classRange = 1:numel(imdb.classes.imageIds) ; +end +numClasses = numel(classRange) ; + +% apply kernel maps +switch opts.kernel + case 'linear' + case 'hell' + descrs = sign(descrs) .* sqrt(abs(descrs)) ; + case 'chi2' + descrs = vl_homkermap(descrs,1,'kchi2') ; + otherwise + assert(false) ; +end +descrs = bsxfun(@times, descrs, 1./sqrt(sum(descrs.^2))) ; + +% train and test +train = find(imdb.images.set <= 2) ; +test = find(imdb.images.set == 3) ; +lambda = 1 / (opts.C*numel(train)) ; +par = {'Solver', 'sdca', 'Verbose', ... + 'BiasMultiplier', 1, ... + 'Epsilon', 0.001, ... + 'MaxNumIterations', 100 * numel(train)} ; + +scores = cell(1, numel(classRange)) ; +ap = zeros(1, numel(classRange)) ; +ap11 = zeros(1, numel(classRange)) ; +w = cell(1, numel(classRange)) ; +b = cell(1, numel(classRange)) ; +for c = 1:numel(classRange) + if isfield(imdb.images, 'class') + y = 2 * (imdb.images.class == classRange(c)) - 1 ; + else + y = - ones(1, numel(imdb.images.id)) ; + [~,loc] = ismember(imdb.classes.imageIds{classRange(c)}, imdb.images.id) ; + y(loc) = 1 - imdb.classes.difficult{classRange(c)} ; + end + if all(y <= 0), continue ; end + + [w{c},b{c}] = vl_svmtrain(descrs(:,train), y(train), lambda, par{:}) ; + scores{c} = w{c}' * descrs + b{c} ; + + [~,~,info] = vl_pr(y(test), scores{c}(test)) ; + ap(c) = info.ap ; + ap11(c) = info.ap_interp_11 ; + fprintf('class %s AP %.2f; AP 11 %.2f\n', imdb.meta.classes{classRange(c)}, ... + ap(c) * 100, ap11(c)*100) ; +end +scores = cat(1,scores{:}) ; + +diary off ; +diary on ; + +% confusion matrix (can be computed only if each image has only one label) +if isfield(imdb.images, 'class') + [~,preds] = max(scores, [], 1) ; + confusion = zeros(numClasses) ; + for c = 1:numClasses + sel = find(imdb.images.class == classRange(c) & imdb.images.set == 3) ; + tmp = accumarray(preds(sel)', 1, [numClasses 1]) ; + tmp = tmp / max(sum(tmp),1e-10) ; + confusion(c,:) = tmp(:)' ; + end +else + confusion = NaN ; +end + +% save results +save(opts.modelPath, 'w', 'b') ; +save(fullfile(opts.resultDir,'result.mat'), ... + 'scores', 'ap', 'ap11', 'confusion', 'classRange', 'opts') ; + +% figures +meanAccuracy = sprintf('mean accuracy: %f\n', mean(diag(confusion))); +mAP = sprintf('mAP: %.2f %%; mAP 11: %.2f', mean(ap) * 100, mean(ap11) * 100) ; + +figure(1) ; clf ; +imagesc(confusion) ; axis square ; +title([opts.prefix ' - ' meanAccuracy]) ; +vl_printsize(1) ; +print('-dpdf', fullfile(opts.resultDir, 'result-confusion.pdf')) ; +print('-djpeg', fullfile(opts.resultDir, 'result-confusion.jpg')) ; + +figure(2) ; clf ; bar(ap * 100) ; +title([opts.prefix ' - ' mAP]) ; +ylabel('AP %%') ; xlabel('class') ; +grid on ; +vl_printsize(1) ; +ylim([0 100]) ; +print('-dpdf', fullfile(opts.resultDir,'result-ap.pdf')) ; + +disp(meanAccuracy) ; +disp(mAP) ; +diary off ; + +end diff --git a/vlfeat-0.9.21/apps/sift_mosaic.m b/vlfeat-0.9.21/apps/sift_mosaic.m new file mode 100644 index 0000000..9e0fdee --- /dev/null +++ b/vlfeat-0.9.21/apps/sift_mosaic.m @@ -0,0 +1,149 @@ +function mosaic = sift_mosaic(im1, im2) +% SIFT_MOSAIC Demonstrates matching two images using SIFT and RANSAC +% +% SIFT_MOSAIC demonstrates matching two images based on SIFT +% features and RANSAC and computing their mosaic. +% +% SIFT_MOSAIC by itself runs the algorithm on two standard test +% images. Use SIFT_MOSAIC(IM1,IM2) to compute the mosaic of two +% custom images IM1 and IM2. + +% AUTORIGHTS + +if nargin == 0 + im1 = imread(fullfile(vl_root, 'data', 'river1.jpg')) ; + im2 = imread(fullfile(vl_root, 'data', 'river2.jpg')) ; +end + +% make single +im1 = im2single(im1) ; +im2 = im2single(im2) ; + +% make grayscale +if size(im1,3) > 1, im1g = rgb2gray(im1) ; else im1g = im1 ; end +if size(im2,3) > 1, im2g = rgb2gray(im2) ; else im2g = im2 ; end + +% -------------------------------------------------------------------- +% SIFT matches +% -------------------------------------------------------------------- + +[f1,d1] = vl_sift(im1g) ; +[f2,d2] = vl_sift(im2g) ; + +[matches, scores] = vl_ubcmatch(d1,d2) ; + +numMatches = size(matches,2) ; + +X1 = f1(1:2,matches(1,:)) ; X1(3,:) = 1 ; +X2 = f2(1:2,matches(2,:)) ; X2(3,:) = 1 ; + +% -------------------------------------------------------------------- +% RANSAC with homography model +% -------------------------------------------------------------------- + +clear H score ok ; +for t = 1:100 + % estimate homograpyh + subset = vl_colsubset(1:numMatches, 4) ; + A = [] ; + for i = subset + A = cat(1, A, kron(X1(:,i)', vl_hat(X2(:,i)))) ; + end + [U,S,V] = svd(A) ; + H{t} = reshape(V(:,9),3,3) ; + + % score homography + X2_ = H{t} * X1 ; + du = X2_(1,:)./X2_(3,:) - X2(1,:)./X2(3,:) ; + dv = X2_(2,:)./X2_(3,:) - X2(2,:)./X2(3,:) ; + ok{t} = (du.*du + dv.*dv) < 6*6 ; + score(t) = sum(ok{t}) ; +end + +[score, best] = max(score) ; +H = H{best} ; +ok = ok{best} ; + +% -------------------------------------------------------------------- +% Optional refinement +% -------------------------------------------------------------------- + +function err = residual(H) + u = H(1) * X1(1,ok) + H(4) * X1(2,ok) + H(7) ; + v = H(2) * X1(1,ok) + H(5) * X1(2,ok) + H(8) ; + d = H(3) * X1(1,ok) + H(6) * X1(2,ok) + 1 ; + du = X2(1,ok) - u ./ d ; + dv = X2(2,ok) - v ./ d ; + err = sum(du.*du + dv.*dv) ; +end + +if exist('fminsearch') == 2 + H = H / H(3,3) ; + opts = optimset('Display', 'none', 'TolFun', 1e-8, 'TolX', 1e-8) ; + H(1:8) = fminsearch(@residual, H(1:8)', opts) ; +else + warning('Refinement disabled as fminsearch was not found.') ; +end + +% -------------------------------------------------------------------- +% Show matches +% -------------------------------------------------------------------- + +dh1 = max(size(im2,1)-size(im1,1),0) ; +dh2 = max(size(im1,1)-size(im2,1),0) ; + +figure(1) ; clf ; +subplot(2,1,1) ; +imagesc([padarray(im1,dh1,'post') padarray(im2,dh2,'post')]) ; +o = size(im1,2) ; +line([f1(1,matches(1,:));f2(1,matches(2,:))+o], ... + [f1(2,matches(1,:));f2(2,matches(2,:))]) ; +title(sprintf('%d tentative matches', numMatches)) ; +axis image off ; + +subplot(2,1,2) ; +imagesc([padarray(im1,dh1,'post') padarray(im2,dh2,'post')]) ; +o = size(im1,2) ; +line([f1(1,matches(1,ok));f2(1,matches(2,ok))+o], ... + [f1(2,matches(1,ok));f2(2,matches(2,ok))]) ; +title(sprintf('%d (%.2f%%) inliner matches out of %d', ... + sum(ok), ... + 100*sum(ok)/numMatches, ... + numMatches)) ; +axis image off ; + +drawnow ; + +% -------------------------------------------------------------------- +% Mosaic +% -------------------------------------------------------------------- + +box2 = [1 size(im2,2) size(im2,2) 1 ; + 1 1 size(im2,1) size(im2,1) ; + 1 1 1 1 ] ; +box2_ = inv(H) * box2 ; +box2_(1,:) = box2_(1,:) ./ box2_(3,:) ; +box2_(2,:) = box2_(2,:) ./ box2_(3,:) ; +ur = min([1 box2_(1,:)]):max([size(im1,2) box2_(1,:)]) ; +vr = min([1 box2_(2,:)]):max([size(im1,1) box2_(2,:)]) ; + +[u,v] = meshgrid(ur,vr) ; +im1_ = vl_imwbackward(im2double(im1),u,v) ; + +z_ = H(3,1) * u + H(3,2) * v + H(3,3) ; +u_ = (H(1,1) * u + H(1,2) * v + H(1,3)) ./ z_ ; +v_ = (H(2,1) * u + H(2,2) * v + H(2,3)) ./ z_ ; +im2_ = vl_imwbackward(im2double(im2),u_,v_) ; + +mass = ~isnan(im1_) + ~isnan(im2_) ; +im1_(isnan(im1_)) = 0 ; +im2_(isnan(im2_)) = 0 ; +mosaic = (im1_ + im2_) ./ mass ; + +figure(2) ; clf ; +imagesc(mosaic) ; axis image off ; +title('Mosaic') ; + +if nargout == 0, clear mosaic ; end + +end diff --git a/vlfeat-0.9.21/data/box.pgm b/vlfeat-0.9.21/data/box.pgm new file mode 100644 index 0000000..55d9cc6 Binary files /dev/null and b/vlfeat-0.9.21/data/box.pgm differ diff --git a/vlfeat-0.9.21/data/box.sift b/vlfeat-0.9.21/data/box.sift new file mode 100644 index 0000000..ade0566 --- /dev/null +++ b/vlfeat-0.9.21/data/box.sift @@ -0,0 +1,5105 @@ +638 128 +133.92 135.88 14.38 -2.732 + 3 12 23 38 10 15 78 20 39 67 42 8 12 8 39 35 118 43 17 0 + 0 1 12 109 9 2 6 0 0 21 46 22 14 18 51 19 5 9 41 52 + 65 30 3 21 55 49 26 30 118 118 25 12 8 3 2 60 53 56 72 20 + 7 10 16 7 88 23 13 15 12 11 11 71 45 7 4 49 82 38 38 91 + 118 15 2 16 33 3 5 118 98 38 6 19 36 1 0 15 64 22 1 2 + 6 11 18 61 31 3 0 6 15 23 118 118 13 0 0 35 38 18 40 96 + 24 1 0 13 17 3 24 98 +132.36 99.75 11.45 -2.910 + 94 32 7 2 13 7 5 23 121 94 13 5 0 0 4 59 13 30 71 32 + 0 6 32 11 25 32 13 0 0 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2 41 +52.78 96.38 1.07 1.071 + 41 0 0 15 110 0 0 4 128 0 0 1 5 0 0 26 49 0 0 36 + 128 0 0 6 89 0 0 8 26 0 0 11 54 2 0 23 83 10 20 7 + 128 19 0 4 14 0 4 20 61 2 0 50 128 0 0 4 124 0 0 5 + 18 0 0 19 10 5 31 4 10 50 128 11 113 18 19 9 21 4 67 74 + 50 3 3 44 128 0 0 12 127 0 0 1 9 0 0 31 0 17 97 3 + 3 17 33 1 2 28 128 21 10 5 13 14 32 4 51 55 34 0 5 66 + 55 0 0 0 1 0 0 67 +52.78 96.38 1.07 -2.201 + 0 0 0 68 55 0 0 0 23 0 5 77 36 2 58 55 11 8 13 13 + 2 7 129 23 2 9 43 3 0 1 112 5 6 0 0 18 129 1 0 0 + 129 8 0 8 50 4 9 29 26 1 57 74 97 24 33 7 12 23 129 18 + 12 3 26 4 6 0 0 2 129 5 0 0 129 1 0 0 57 8 0 11 + 39 0 3 7 129 56 0 2 66 7 16 4 80 14 0 5 4 0 0 0 + 108 5 0 0 129 0 0 1 41 3 0 7 32 0 0 0 129 14 0 1 + 58 3 0 0 90 7 0 0 +51.25 67.69 0.95 2.650 + 4 3 19 2 0 0 91 124 20 16 20 3 23 2 20 124 38 2 0 7 + 107 3 0 6 68 5 0 2 22 0 0 2 10 29 124 37 0 2 24 29 + 116 124 98 12 21 0 2 10 59 11 2 9 112 1 0 8 77 0 0 2 + 31 0 0 10 14 8 47 7 0 33 124 30 124 27 7 2 21 5 61 124 + 75 3 0 10 97 2 0 14 69 1 0 2 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40 24 13 + 60 43 14 131 118 24 3 7 138 112 7 21 16 5 1 23 20 5 0 5 + 74 29 1 3 14 6 5 22 24 18 33 15 47 3 0 34 120 101 14 28 + 138 37 0 1 7 24 12 95 28 7 0 0 32 78 13 11 15 19 21 40 + 10 1 2 5 12 6 2 34 38 25 17 23 93 138 25 19 28 12 3 5 + 21 133 44 20 23 22 5 1 +38.49 238.58 1.01 -0.402 + 0 1 20 70 26 23 49 15 3 1 2 70 118 65 18 52 11 10 3 0 + 7 7 33 122 4 1 1 2 0 0 32 122 3 2 32 122 11 0 0 0 + 105 16 4 73 20 1 2 117 46 12 18 0 0 0 2 122 6 4 32 37 + 0 0 0 23 8 9 12 89 44 0 0 0 122 115 17 18 6 0 0 7 + 34 48 122 16 0 0 0 4 0 3 101 122 1 0 1 2 2 9 7 33 + 26 16 0 0 33 96 42 17 7 10 2 1 12 40 122 32 0 0 0 7 + 12 4 52 53 2 0 7 52 +38.00 211.91 1.07 -2.007 + 145 42 0 0 0 0 0 5 145 51 0 0 0 0 0 32 72 37 5 4 + 1 0 0 10 13 17 18 18 5 7 2 0 145 29 0 0 0 0 0 9 + 145 45 0 0 0 4 3 35 77 21 4 1 6 39 9 20 46 10 3 7 + 11 40 11 10 127 14 0 0 0 0 6 125 145 40 0 0 0 2 8 104 + 110 5 0 1 16 56 16 21 43 9 8 54 27 14 8 9 106 15 0 0 + 0 1 4 91 145 6 0 0 0 0 2 74 63 8 6 11 7 7 21 16 + 6 0 3 33 65 23 10 9 +37.86 210.76 1.15 -2.057 + 143 54 0 0 0 0 0 4 143 49 0 0 0 0 0 26 48 40 8 7 + 3 4 1 6 13 14 18 23 7 15 5 2 143 43 0 0 0 0 0 10 + 143 69 0 0 0 9 5 26 84 21 3 0 5 52 13 17 45 9 4 22 + 20 42 15 11 128 12 0 0 0 0 7 139 143 32 0 0 0 2 7 113 + 91 6 0 3 17 40 24 18 38 11 8 73 57 17 8 11 121 31 0 1 + 1 2 4 53 143 20 0 0 0 0 0 42 55 16 14 26 7 4 14 8 + 22 2 2 26 50 26 9 18 +37.64 224.59 0.94 0.797 + 0 0 0 4 82 97 0 0 29 0 0 0 75 53 1 19 101 0 0 0 + 0 10 82 124 4 0 0 0 0 84 132 16 0 0 0 10 132 28 0 0 + 74 0 0 0 132 55 1 8 132 25 0 0 3 3 10 43 41 23 0 0 + 0 50 49 12 0 0 0 6 117 67 0 0 40 1 0 2 106 71 4 11 + 132 78 1 0 3 6 2 14 27 107 12 0 0 2 0 0 0 0 12 68 + 50 15 0 0 12 4 6 40 68 14 3 9 107 38 1 2 3 1 2 22 + 23 57 13 0 0 0 0 4 +33.14 256.33 0.99 -2.966 + 14 16 9 11 5 4 0 1 0 0 3 56 51 4 1 2 58 0 0 24 + 67 4 4 95 127 3 0 0 0 0 0 127 21 18 5 7 9 1 1 4 + 12 2 1 69 87 1 0 2 127 19 1 20 17 0 0 127 127 24 3 0 + 0 0 0 116 17 6 4 27 14 0 2 8 14 9 1 75 105 0 0 0 + 127 127 3 7 12 0 0 14 109 127 17 2 0 0 0 12 6 8 5 60 + 17 0 1 1 1 1 1 71 27 0 0 0 127 41 0 2 4 0 0 9 + 127 37 24 7 0 0 0 15 +29.06 150.90 0.97 1.709 + 3 2 3 44 84 2 0 0 135 18 7 18 15 0 0 18 131 25 2 0 + 0 0 1 39 18 22 3 4 8 3 18 35 15 5 4 58 138 5 0 0 + 138 33 6 17 27 0 0 25 138 25 1 0 0 0 0 81 32 11 5 16 + 32 3 5 22 22 0 0 33 138 24 0 1 138 27 0 3 33 5 0 12 + 124 92 6 0 0 0 0 22 12 44 20 15 35 3 3 15 12 2 1 26 + 123 26 0 1 138 37 2 7 23 6 0 9 130 38 0 0 0 0 0 34 + 34 4 0 7 56 12 12 46 +26.89 302.59 0.94 -2.143 + 1 4 61 74 1 0 0 1 13 32 81 72 39 2 0 1 75 28 4 59 + 48 3 11 50 24 16 9 9 35 66 42 33 9 4 29 91 35 46 29 12 + 111 29 25 19 40 57 8 36 59 95 15 6 48 111 23 7 16 70 84 53 + 26 10 32 23 5 2 1 8 111 48 46 14 111 79 40 17 73 22 2 21 + 57 28 39 14 13 62 67 54 6 4 12 3 0 8 111 66 0 1 0 5 + 111 54 20 2 15 26 13 6 44 32 85 111 30 6 7 2 0 0 20 111 + 4 0 1 3 0 0 8 11 +26.43 219.70 0.89 1.503 + 0 0 1 16 10 1 0 0 28 4 4 16 8 0 0 11 80 6 0 0 + 2 18 35 116 52 4 0 1 25 70 30 14 0 0 0 18 15 0 0 0 + 112 1 0 8 13 0 0 23 145 9 0 0 26 31 16 140 58 6 0 0 + 145 96 13 20 0 0 0 3 22 20 3 0 117 7 0 2 7 0 0 17 + 145 142 5 8 30 4 0 12 55 34 9 25 145 25 0 3 0 0 0 0 + 29 132 5 0 60 1 0 0 2 16 3 36 93 92 14 5 1 2 5 25 + 25 40 25 47 79 1 0 0 +25.59 201.26 1.05 -1.998 + 6 6 0 2 23 15 0 3 62 24 5 0 0 0 0 11 135 15 0 0 + 0 0 0 45 105 32 4 0 0 1 0 26 5 0 0 0 75 93 4 9 + 51 18 2 5 3 1 2 18 135 77 0 0 0 0 0 13 135 55 1 0 + 0 4 0 9 2 0 0 0 135 135 0 2 34 3 0 1 10 12 6 57 + 135 22 0 0 0 0 2 109 114 38 0 0 0 0 0 21 1 0 0 0 + 135 135 0 0 79 13 0 0 51 55 0 20 80 62 11 8 3 0 0 24 + 43 94 8 1 0 0 0 1 +24.01 232.36 1.06 -1.656 + 8 0 0 0 133 17 0 0 104 9 0 0 43 31 17 22 28 11 0 0 + 25 111 12 4 101 22 0 0 3 7 1 13 9 0 0 0 133 25 0 0 + 133 11 0 0 69 12 1 16 37 3 0 5 111 59 3 9 133 23 0 1 + 31 13 0 1 6 0 0 0 133 24 0 0 133 18 1 1 91 8 0 3 + 49 6 2 21 133 7 0 2 84 58 1 9 47 2 0 0 1 0 0 2 + 133 14 0 0 81 48 16 2 83 7 0 0 15 25 48 28 67 7 0 0 + 21 37 3 10 44 8 0 0 +23.76 229.04 0.92 -1.492 + 8 0 0 30 139 0 0 1 139 0 0 5 48 0 0 49 36 0 0 19 + 103 16 2 21 72 0 0 8 64 10 0 5 22 0 0 40 139 0 0 3 + 139 8 1 9 49 0 0 44 35 2 1 64 139 0 0 8 94 24 0 31 + 53 0 0 4 23 3 0 42 139 0 0 1 133 85 42 11 27 0 0 6 + 8 25 55 59 122 2 0 0 54 42 2 13 66 4 0 0 9 0 0 24 + 139 0 0 6 21 20 17 1 13 15 11 20 0 19 35 39 21 9 1 0 + 22 21 5 32 19 0 0 0 +22.84 160.20 0.91 -1.630 + 40 4 0 0 156 11 0 0 156 23 0 1 18 1 0 2 9 2 0 3 + 29 18 8 1 0 0 0 0 86 41 4 0 44 3 0 0 156 17 0 0 + 156 14 0 0 20 4 7 16 21 1 0 1 14 39 36 8 0 0 0 1 + 107 48 3 0 40 2 0 0 156 19 0 0 156 23 0 0 24 2 1 6 + 42 8 1 13 36 16 6 5 0 0 0 27 112 19 0 0 24 2 0 0 + 156 8 0 0 156 24 0 0 24 1 0 6 41 8 2 14 44 10 1 6 + 0 0 0 8 56 34 0 0 +23.06 155.71 1.11 -1.548 + 10 0 0 10 152 0 0 0 152 2 0 3 64 2 2 18 32 1 0 7 + 25 27 13 7 0 0 0 9 119 22 0 0 17 0 0 20 152 0 0 0 + 152 8 0 6 69 1 0 23 41 4 1 24 68 12 1 9 0 0 0 17 + 108 35 0 0 20 0 0 12 152 0 0 0 152 25 2 7 61 0 0 9 + 32 10 5 34 30 15 5 2 0 0 0 7 84 36 1 0 19 0 0 7 + 152 1 0 1 152 2 0 1 43 0 0 18 29 2 0 3 11 18 12 7 + 0 0 0 9 64 29 2 0 +7.49 318.86 1.13 -1.670 + 0 0 0 0 0 0 0 0 0 0 0 0 0 0 17 8 0 0 0 0 + 0 0 60 7 0 0 0 0 0 0 67 12 9 2 0 1 2 1 0 4 + 111 4 0 0 1 1 100 166 17 0 0 0 0 1 173 102 0 0 0 0 + 0 1 173 55 19 3 0 1 4 3 1 1 173 74 0 0 0 1 10 44 + 126 24 0 0 6 8 74 30 0 0 4 11 8 6 50 5 6 0 0 0 + 3 3 0 0 173 42 0 0 1 0 0 0 171 23 0 0 3 2 3 2 + 1 0 3 16 52 8 2 3 +7.49 318.86 1.13 -2.998 + 9 0 0 0 0 0 0 1 168 0 0 0 0 0 0 62 159 0 0 0 + 2 2 2 44 3 5 0 2 28 37 23 2 26 0 0 0 0 0 0 5 + 168 41 7 0 0 0 0 86 130 32 57 0 0 0 7 40 3 8 37 0 + 0 6 13 4 14 3 0 0 0 0 1 1 121 164 91 0 0 0 1 7 + 20 118 168 0 0 0 1 2 0 86 168 0 0 0 0 0 0 0 0 0 + 0 0 1 0 0 6 13 1 1 2 3 0 0 9 50 0 0 1 6 2 + 0 19 60 0 0 0 4 1 diff --git a/vlfeat-0.9.21/data/river1.jpg b/vlfeat-0.9.21/data/river1.jpg new file mode 100644 index 0000000..e32f2f3 Binary files /dev/null and b/vlfeat-0.9.21/data/river1.jpg differ diff --git a/vlfeat-0.9.21/data/river2.jpg b/vlfeat-0.9.21/data/river2.jpg new file mode 100644 index 0000000..f289c22 Binary files /dev/null and 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VLFeat is a cross-platform open source collection of vision +algorithms with a special focus on visual features (for instance SIFT +and MSER) and clustering (k-means, hierarchical k-means, agglomerative +information bottleneck). It bundles a MATLAB toolbox, a clean and +portable C library and a number of command line utilities. Thus it is +possible to use the same algorithm both from MATLAB, the command line, +and your own programs.

+ +

Many parties make the development of VLFeat possible:

+ + +

Sponsors

+ + +

In 2012 the development of VLFeat is +supported by the PASCAL Harvest programme. Several people have been +working in Oxford to add new functionalities to the library. Moreover, +leading researchers in computer vision were consulted as +advisors of the project. Some of +these advancements have been presented at a +tutorial at +the European Conference in Computer Vision (ECCV) 2012. See +the PASCAL Harvest Roadmap for further +details.

+ + +Yandex +credits + + +

Team

+ + +

VLFeat is developed by a team of computer vision +researchers, including master and PhD students, postgraduates, and +senior researchers, as listed below. VLFeat was created by Andrea +Vedaldi and Brian Fulkerson in 2007, based on previously published +software by the same authors.

+ +

+ Andrea Vedaldi picture + + Andrea Vedaldi joined + the faculty at the University of Oxford in 2012. Since 2008 he was + junior research fellow in the Oxford Visual Geometry Group. He + received the Ph.D. and Master's degrees in Computer Science from the + University of California - Los Angeles, in 2008 and 2005, and the + Bachelor's degree in Information Engineering from the University of + Padova, Italy, in 2003. He is the recipient of the UCLA outstanding + Master's and Ph.D. awards. +

+ +

+ Brian Fulkerson picture + + Brian + Fulkerson received his B.S. in Computer Engineering from the + University of California - San Diego in 2004, and his M.S. and Ph.D. + in Computer Science from the University of California - Los Angeles + Vision Lab in 2006 and 2010. +

+ +

+ Karel Lenc picture + + Karel Lenc received his B.S. degree in Cybernetics and + Measurements from the Czech Technical University in 2010. He is + currently pursuing M.S. degree in Computer Vision and Computer + Engineering at the CTU, Center for Machine Perception. He visited the + Department of Engineering Mathematics, University of Bristol in 2011 + and the Oxford Visual Geometry Group in 2012.

+ +

+ Daniele Perrone picture + + Daniele + Perrone received his B.S. degree in Computer Engineering from + Università della Calabria in 2007, and his M.S. degree in + Artificial Intelligence from "Sapienza" Università di Roma in + 2009. He started his Ph.D. in June 2010 at Heriot-Watt University, + Edinburgh, UK. From June 2012 he joined the Computer Vision Group at + the Universität Bern, Switzerland. +

+ +

+ Michal Perdoch picture + + Michal Perdoch + received his Bachelor's degree in Software Engineering from the + Slovak University of Technology in Bratislava in 2001, Master's + degree in Computer Science and Ph.D. degree in Artificial + Intelligence and Biocybernetics from the Czech Technical University + in Prague, in 2004 and 2011. He is currently a postdoctoral + researcher at the CTU Center for Machine Perception. +

+ +

+ Milan Sulc picture + + Milan Sulc + received his Bachelor's degree in Cybernetics and Robotics from the + Czech Technical University in 2012. + He is currently pursuing Master degrees in Computer Vision + and Artificial Intelligence at the CTU + and Entrepreneurship and Commercial Engineering in Industry at CTU. + He is a student intern at the CTU Center for Machine Perception. +

+ +

+ Hana Sarbortova picture + + Hana Sarbortova +received her Bachelor of Engineering degree in Digital Signal and Image Processing from the +University of Central Lancashire in 2012. She is currently studying Computer Vision and Digital Image +at the Czech Technical University in Prague. She is a student intern at the CTU Center for Machine Perception. +

+ + +

Advisors

+ + +

The development of VLFeat is supported by a number of computer +vision groups and researchers:

+ +
    +
  • Prof. Andrew +Zisserman, Oxford VGG +Lab.
    • +
  • Prof. Jiri Matas, Czech Technical University in Prague.
    • +
  • Prof. Tinne Tuytelaars, KU Leuven.
    • +
  • Dr. Cordelia Schmid, LEAR, Grenoble.
    • +
  • Dr. Krystian Mikolajczyk, Surrey.
    • +
  • Prof. Stefano Soatto, UCLA Vision +Lab.
    • +
+ + +

Users and community

+ + +

The authors would like to thank the many colleagues that have +contributed to VLFeat by testing and providing helpful suggestions and +comments.

+ + diff --git a/vlfeat-0.9.21/docsrc/api.html b/vlfeat-0.9.21/docsrc/api.html new file mode 100644 index 0000000..b3f98ec --- /dev/null +++ b/vlfeat-0.9.21/docsrc/api.html @@ -0,0 +1 @@ + diff --git a/vlfeat-0.9.21/docsrc/apps.html b/vlfeat-0.9.21/docsrc/apps.html new file mode 100644 index 0000000..5eb7c44 --- /dev/null +++ b/vlfeat-0.9.21/docsrc/apps.html @@ -0,0 +1,114 @@ + + + + + +#content table.checker { + border-collapse: collapse ; + margin-left: auto ; + margin-right: auto ; +} +#content table.checker td { + background-color: #f6f6f6 ; + border: 1px solid #DDD ; + padding: 0.5em ; +} + + +

This page lists a number of example VLFeat applications. The code +can be found in the VLROOT/apps/ subdirectory in the +VLFeat package.

+ +

Basic recognition

+ + + + + +Caltech-101 Collage + +

This sample application uses VLFeat to train an test an image +classifier on the Caltech-101 data. The classifier achieves 65% +average accuracy by using a single feature and 15 training images per +class. It uses:

+
    +
  • PHOW features (dense multi-scale SIFT descriptors)
    • +
  • Elkan k-means for fast visual word dictionary +construction
    • +
  • Spatial histograms as image descriptors
    • +
  • A homogeneous kernel map to transform a Chi2 support vector +machine (SVM) into a linear one
    • +
  • SVM classifiers
    • +
+ +

The program is fully contained in +a single MATLAB M-file, +and can also be simply adapted to use your own data (change +conf.calDir).

+ +

Advanced encodings for recognition

+ + + + + +

This example application extends the Caltech-101 demo above in many +ways: it supports multiple encoding methods, including BoVW, VLAD, and +Fisher Vectors, tweaked image features, and multiple benchmark +datasets. The code is located int apps/recognition. Start +from the main +file.

+ +

The following tables report results on a few standard benchmark +datasets (PASCAL VOC 2007 classification challenge, Caltech 101 30 +training images, MIT Scene 67, and Flickr Material Dataset) for a +number of different encodings:

+ + + + + + + + +
methodVOC07Caltech 101Scene 67FMD
FV59.12% mAP73.02% Acc58.25% Acc59.60% Acc
FV + aug.60.25% mAP75.61% Acc57.57% Acc60.80% Acc
FV + s.p.62.23% mAP77.63% Acc61.83% Acc60.80% Acc
VLAD + aug.54.66% mAP78.68% Acc53.29% Acc49.40% Acc
BOVW + aug.49.87% mAP75.98% Acc50.22% Acc46.00% Acc
+ +

The baseline feature is SIFT (vl_dsift) computed at +seven scales with a factor $\sqrt{2}$ between successive scales, bins +8 pixel wide, and computed with a step of 4 pixels. All experiments +but the Caltech-101 ones start by doubling the resolution of the input +image. The details of the encodings are as follows:

+ +
    +
  • Bag-of-visual-words uses 4096 vector quantized visual words +histogram square rooting, followed by $L^2$ normalization (Hellinger's +kernel).
    • +
  • VLAD uses 256 vector quantized visual +words, signed square-rooting, component wise $L^2$ normalization, and +global $L^2$ normalization (see vl_vlad).
    • +
  • Fisher vectors uses a 256 visual words +GMM and the improved formulation (signed square-rooting followed by +$L^2$ normalization, see vl_fisher).
    • +
  • Learning uses a linear SVM +(see vl_svmtrain). The parameter $C$ is set to 10 for all +dataset except PASCAL VOC, for which it is set to 1.
    • +
  • Experiments labelled with “aug.” encode spatial +information by appending the feature coordinates to the descriptor; +the ones labelled with “s.p.” use a spatial pyramid with +1x1 and 3x1 subdivisions.
    • +
+ +

SIFT mosaic

+ + + + + +SIFT mosaic + +

This sample application uses VLFeat to extract SIFT features form a +pair of images and match them. It then filters the matches based on +RANSAC and produces a mosaic. Read +the code.

+ + diff --git a/vlfeat-0.9.21/docsrc/compiling.html b/vlfeat-0.9.21/docsrc/compiling.html new file mode 100644 index 0000000..aac6c12 --- /dev/null +++ b/vlfeat-0.9.21/docsrc/compiling.html @@ -0,0 +1,143 @@ + + + +

These instructions explain how to compile VLFeat from sources. +While this is necessary in order to develop or modify VLFeat, using +the pre-compiled binaries will work in +most other cases.

+ +

VLFeat is largely self-contained and hence easy to compile. While +certain features such as multi-core computation and vector instruction +support may require specific compilers, most compilers and +environments should be capable of producing fully functional version +of the library. Compiling MATLAB or Octave support requires the +corresponding applications to be installed too.

+ + + + + +%tableofcontents; + + +

General instructions

+ + +

Compiling for UNIX-like platforms (e.g. GNU/Linux, Mac OS X) +assumes that the standard GNU toolchain is available. In particular, +while compilers other than GCC can be used, the compilation scripts +require GNU/make.

+ +

To compile the library, it is usually sufficient to change to +VLFeat root directory, denoted VLFEATROOT in the +following, and type make:

+ + +$ cd VLFEATROOT +$ make + + +

The make script attempts to automatically detect the host +architecture and configure itself accordingly. If the architecture is +not detected correctly, it can be specified manually. For instance

+ + +$ make ARCH=glnx86 + + +

compiles for GNU/Linux 32-bit. make help can be used +to obtain a list of other useful options. You can also use make +info to obtain a list of the configuration parameters used by +the Makefile, which might allow you do debug any potential issue.

+ + +

Compiling MATLAB support

+ + +

In order for MATLAB support to be compiled, the +MATLAB mex script must be in the current path. If it is +not, its location must be passed to make as +follows. First, determine MATLAB's root directory by running a MATLAB +session and issuing the matlabroot +command. Let MATLABROOT denote the returned path +(e.g. /Applications/MATLAB_R2009b.app/). The mex +script is usually located in MALTABROOT/bin/mex. Then run +the compilation with the command

+ + +$ make MEX=MATLABROOT/bin/mex + + +

VLFeat must be compiled for the architecture used by MATLAB (run +MATLAB's computer command to obtain this information). On +Mac OS X it is often necessary to turn on 64-bit support explicitly by +setting ARCH=maci64 as both the 32 and 64 bit versions +are plausible targets on 64-bit machines.

+ + +

Compiling Octave support

+ + +

Octave support is still experimental. Similarly to MATLAB, Octave +requires compiling MEX files. This can be turned on by passing to make +the path to the mkoctfile command:

+ + +$ make MKOCTFILE=/path/to/mkoctfile + + + +

Mac OS X troubleshooting

+ + +

Since macOS CLang compiler does not support OpenMP, this is + disabled by default on this platform. To use it, + install Brew llvm:

+ +$ brew install llvm + +

Then, use the Brew CLang compiler to compile VLFeat, as follows::

+ +$ make CC=BREWROOT/opt/llvm/bin/clang DISABLE_OPENMP=no + +

Here BREWROOT is the path to Brew installation.

+ + + + + + +

For Windows, the library bundles an NMake makefile +(Makefile.mak). In order to use it, you must edit +Makefile.mak to adjust the values of a number of configuration +variables to match your setup. Once you have done that, start the +Visual Studio Command Prompt and type

+ + +$ nmake /f Makefile.mak # for the Windows 64 target +$ nmake /f Makefile.mak ARCH=win32 # for the Windows 32 target + + +

For Windows platform, it is also possible to compile just the +MATLAB MEX files from within MATLAB (using the vl_compile +command). This is meant to help less experienced users that may need +to recompile the mex file due to binary incompatibilities with older +MATLAB versions.

+ +

Windows troubleshooting

+ +
+
syntax error: '=' unexpected:
+

Use nmake /f Makefile.mak. + Without /f, nmake will default to the wrong + makefile.

+
'long' followed by 'long' is illegal:
+

This error is usually caused by + attempting to compile outside of the Visual Studio Command Prompt.

+
+ + + diff --git a/vlfeat-0.9.21/docsrc/doc.html b/vlfeat-0.9.21/docsrc/doc.html new file mode 100644 index 0000000..c399ac9 --- /dev/null +++ b/vlfeat-0.9.21/docsrc/doc.html @@ -0,0 +1,35 @@ + + + +

The VLFeat reference documentation has three parts:

+ + + + + + + +
+

MATLAB functions

+

The reference documentation of VLFeat MATLAB commands (this + is an on-line version of the documentation built in the + command themsevles).

+ 		+

C API + reference

This documentation + includes descriptions of all the algorithms and hence + it is useful even if you do not plan to use the C library + directly.

+ 		+

Man pages

+

The documentation of the command line + utilities bundled with VLFeat (this is an on-line version + of the Unix man found in the src/ + subdirectory.

+
+ +

In addition to the documentation, there are also +tutorials which introduce many of the +algorithms contained in the library.

+ + diff --git a/vlfeat-0.9.21/docsrc/download.html b/vlfeat-0.9.21/docsrc/download.html new file mode 100644 index 0000000..3038ea3 --- /dev/null +++ b/vlfeat-0.9.21/docsrc/download.html @@ -0,0 +1,66 @@ + + + +

The latest version of VLFeat is %env:VERSION;. To use +VLFeat, simply download and unpack the latest binary package and add +the appropriate paths to your environment (see below for details).

+ + + + + + +
+

Downloads

+ +		 +

Install

+ +
+ +
&nsbp;
+ +

Repository access

+ +

VLFeat is under active development. You +can browse our +Git repository or download it by

+ +git clone git://github.com/vlfeat/vlfeat.git + +

(This will require Git to be +installed). The top of the master branch corresponds to the most +recent version of VLFeat, but it could be unstable.

+ +

We welcome contributions to both the documentation and the source +code of VLFeat. You can create patches against our Git repository and +send them to us for inclusion in the next version. There are two ways +to contribute. For minor changes, simply clone our public repository, +as explained above. Once you have made and committed your changes +locally, you can submit them to the project via e-mail using a command +like git format-patch: +

+ +git format-patch origin + +

For major additions, we prefer to handle collaboration through +github. Follow +their tutorial +to fork our project +and submit your modifications using a pull request.

+ + diff --git a/vlfeat-0.9.21/docsrc/doxygen.conf b/vlfeat-0.9.21/docsrc/doxygen.conf new file mode 100644 index 0000000..fec99d3 --- /dev/null +++ b/vlfeat-0.9.21/docsrc/doxygen.conf @@ -0,0 +1,2297 @@ +# Doxyfile 1.8.5 + +# This file describes the settings to be used by the documentation system +# doxygen (www.doxygen.org) for a project. +# +# All text after a double hash (##) is considered a comment and is placed in +# front of the TAG it is preceding. +# +# All text after a single hash (#) is considered a comment and will be ignored. +# The format is: +# TAG = value [value, ...] +# For lists, items can also be appended using: +# TAG += value [value, ...] +# Values that contain spaces should be placed between quotes (\" \"). + +#--------------------------------------------------------------------------- +# Project related configuration options +#--------------------------------------------------------------------------- + +# This tag specifies the encoding used for all characters in the config file +# that follow. The default is UTF-8 which is also the encoding used for all text +# before the first occurrence of this tag. Doxygen uses libiconv (or the iconv +# built into libc) for the transcoding. See http://www.gnu.org/software/libiconv +# for the list of possible encodings. +# The default value is: UTF-8. + +DOXYFILE_ENCODING = UTF-8 + +# The PROJECT_NAME tag is a single word (or a sequence of words surrounded by +# double-quotes, unless you are using Doxywizard) that should identify the +# project for which the documentation is generated. This name is used in the +# title of most generated pages and in a few other places. +# The default value is: My Project. + +PROJECT_NAME = VLFeat + +# The PROJECT_NUMBER tag can be used to enter a project or revision number. This +# could be handy for archiving the generated documentation or if some version +# control system is used. + +PROJECT_NUMBER = + +# Using the PROJECT_BRIEF tag one can provide an optional one line description +# for a project that appears at the top of each page and should give viewer a +# quick idea about the purpose of the project. Keep the description short. + +PROJECT_BRIEF = + +# With the PROJECT_LOGO tag one can specify an logo or icon that is included in +# the documentation. The maximum height of the logo should not exceed 55 pixels +# and the maximum width should not exceed 200 pixels. Doxygen will copy the logo +# to the output directory. + +PROJECT_LOGO = + +# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute) path +# into which the generated documentation will be written. If a relative path is +# entered, it will be relative to the location where doxygen was started. If +# left blank the current directory will be used. + +OUTPUT_DIRECTORY = doc/ + +# If the CREATE_SUBDIRS tag is set to YES, then doxygen will create 4096 sub- +# directories (in 2 levels) under the output directory of each output format and +# will distribute the generated files over these directories. Enabling this +# option can be useful when feeding doxygen a huge amount of source files, where +# putting all generated files in the same directory would otherwise causes +# performance problems for the file system. +# The default value is: NO. + +CREATE_SUBDIRS = NO + +# The OUTPUT_LANGUAGE tag is used to specify the language in which all +# documentation generated by doxygen is written. Doxygen will use this +# information to generate all constant output in the proper language. +# Possible values are: Afrikaans, Arabic, Brazilian, Catalan, Chinese, Chinese- +# Traditional, Croatian, Czech, Danish, Dutch, English, Esperanto, Farsi, +# Finnish, French, German, Greek, Hungarian, Italian, Japanese, Japanese-en, +# Korean, Korean-en, Latvian, Norwegian, Macedonian, Persian, Polish, +# Portuguese, Romanian, Russian, Serbian, Slovak, Slovene, Spanish, Swedish, +# Turkish, Ukrainian and Vietnamese. +# The default value is: English. + +OUTPUT_LANGUAGE = English + +# If the BRIEF_MEMBER_DESC tag is set to YES doxygen will include brief member +# descriptions after the members that are listed in the file and class +# documentation (similar to Javadoc). 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If set to YES the +# scope will be hidden. +# The default value is: NO. + +HIDE_SCOPE_NAMES = NO + +# If the SHOW_INCLUDE_FILES tag is set to YES then doxygen will put a list of +# the files that are included by a file in the documentation of that file. +# The default value is: YES. + +SHOW_INCLUDE_FILES = YES + +# If the FORCE_LOCAL_INCLUDES tag is set to YES then doxygen will list include +# files with double quotes in the documentation rather than with sharp brackets. +# The default value is: NO. + +FORCE_LOCAL_INCLUDES = NO + +# If the INLINE_INFO tag is set to YES then a tag [inline] is inserted in the +# documentation for inline members. +# The default value is: YES. + +INLINE_INFO = YES + +# If the SORT_MEMBER_DOCS tag is set to YES then doxygen will sort the +# (detailed) documentation of file and class members alphabetically by member +# name. If set to NO the members will appear in declaration order. +# The default value is: YES. + +SORT_MEMBER_DOCS = YES + +# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the brief +# descriptions of file, namespace and class members alphabetically by member +# name. If set to NO the members will appear in declaration order. +# The default value is: NO. + +SORT_BRIEF_DOCS = NO + +# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen will sort the +# (brief and detailed) documentation of class members so that constructors and +# destructors are listed first. If set to NO the constructors will appear in the +# respective orders defined by SORT_BRIEF_DOCS and SORT_MEMBER_DOCS. +# Note: If SORT_BRIEF_DOCS is set to NO this option is ignored for sorting brief +# member documentation. +# Note: If SORT_MEMBER_DOCS is set to NO this option is ignored for sorting +# detailed member documentation. +# The default value is: NO. + +SORT_MEMBERS_CTORS_1ST = NO + +# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the hierarchy +# of group names into alphabetical order. If set to NO the group names will +# appear in their defined order. +# The default value is: NO. + +SORT_GROUP_NAMES = NO + +# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be sorted by +# fully-qualified names, including namespaces. If set to NO, the class list will +# be sorted only by class name, not including the namespace part. +# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES. +# Note: This option applies only to the class list, not to the alphabetical +# list. +# The default value is: NO. + +SORT_BY_SCOPE_NAME = NO + +# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to do proper +# type resolution of all parameters of a function it will reject a match between +# the prototype and the implementation of a member function even if there is +# only one candidate or it is obvious which candidate to choose by doing a +# simple string match. By disabling STRICT_PROTO_MATCHING doxygen will still +# accept a match between prototype and implementation in such cases. +# The default value is: NO. + +STRICT_PROTO_MATCHING = NO + +# The GENERATE_TODOLIST tag can be used to enable ( YES) or disable ( NO) the +# todo list. This list is created by putting \todo commands in the +# documentation. +# The default value is: YES. + +GENERATE_TODOLIST = YES + +# The GENERATE_TESTLIST tag can be used to enable ( YES) or disable ( NO) the +# test list. This list is created by putting \test commands in the +# documentation. +# The default value is: YES. + +GENERATE_TESTLIST = YES + +# The GENERATE_BUGLIST tag can be used to enable ( YES) or disable ( NO) the bug +# list. This list is created by putting \bug commands in the documentation. +# The default value is: YES. + +GENERATE_BUGLIST = YES + +# The GENERATE_DEPRECATEDLIST tag can be used to enable ( YES) or disable ( NO) +# the deprecated list. This list is created by putting \deprecated commands in +# the documentation. +# The default value is: YES. + +GENERATE_DEPRECATEDLIST= YES + +# The ENABLED_SECTIONS tag can be used to enable conditional documentation +# sections, marked by \if ... \endif and \cond +# ... \endcond blocks. + +ENABLED_SECTIONS = + +# The MAX_INITIALIZER_LINES tag determines the maximum number of lines that the +# initial value of a variable or macro / define can have for it to appear in the +# documentation. If the initializer consists of more lines than specified here +# it will be hidden. Use a value of 0 to hide initializers completely. The +# appearance of the value of individual variables and macros / defines can be +# controlled using \showinitializer or \hideinitializer command in the +# documentation regardless of this setting. +# Minimum value: 0, maximum value: 10000, default value: 30. + +MAX_INITIALIZER_LINES = 30 + +# Set the SHOW_USED_FILES tag to NO to disable the list of files generated at +# the bottom of the documentation of classes and structs. If set to YES the list +# will mention the files that were used to generate the documentation. +# The default value is: YES. + +SHOW_USED_FILES = YES + +# Set the SHOW_FILES tag to NO to disable the generation of the Files page. This +# will remove the Files entry from the Quick Index and from the Folder Tree View +# (if specified). +# The default value is: YES. + +SHOW_FILES = YES + +# Set the SHOW_NAMESPACES tag to NO to disable the generation of the Namespaces +# page. This will remove the Namespaces entry from the Quick Index and from the +# Folder Tree View (if specified). +# The default value is: YES. + +SHOW_NAMESPACES = YES + +# The FILE_VERSION_FILTER tag can be used to specify a program or script that +# doxygen should invoke to get the current version for each file (typically from +# the version control system). Doxygen will invoke the program by executing (via +# popen()) the command command input-file, where command is the value of the +# FILE_VERSION_FILTER tag, and input-file is the name of an input file provided +# by doxygen. Whatever the program writes to standard output is used as the file +# version. For an example see the documentation. + +FILE_VERSION_FILTER = + +# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed +# by doxygen. The layout file controls the global structure of the generated +# output files in an output format independent way. To create the layout file +# that represents doxygen's defaults, run doxygen with the -l option. You can +# optionally specify a file name after the option, if omitted DoxygenLayout.xml +# will be used as the name of the layout file. +# +# Note that if you run doxygen from a directory containing a file called +# DoxygenLayout.xml, doxygen will parse it automatically even if the LAYOUT_FILE +# tag is left empty. + +LAYOUT_FILE = + +# The CITE_BIB_FILES tag can be used to specify one or more bib files containing +# the reference definitions. This must be a list of .bib files. The .bib +# extension is automatically appended if omitted. This requires the bibtex tool +# to be installed. See also http://en.wikipedia.org/wiki/BibTeX for more info. +# For LaTeX the style of the bibliography can be controlled using +# LATEX_BIB_STYLE. To use this feature you need bibtex and perl available in the +# search path. Do not use file names with spaces, bibtex cannot handle them. See +# also \cite for info how to create references. + +CITE_BIB_FILES = vlfeat.bib + +#--------------------------------------------------------------------------- +# Configuration options related to warning and progress messages +#--------------------------------------------------------------------------- + +# The QUIET tag can be used to turn on/off the messages that are generated to +# standard output by doxygen. If QUIET is set to YES this implies that the +# messages are off. +# The default value is: NO. + +QUIET = NO + +# The WARNINGS tag can be used to turn on/off the warning messages that are +# generated to standard error ( stderr) by doxygen. If WARNINGS is set to YES +# this implies that the warnings are on. +# +# Tip: Turn warnings on while writing the documentation. +# The default value is: YES. + +WARNINGS = YES + +# If the WARN_IF_UNDOCUMENTED tag is set to YES, then doxygen will generate +# warnings for undocumented members. If EXTRACT_ALL is set to YES then this flag +# will automatically be disabled. +# The default value is: YES. + +WARN_IF_UNDOCUMENTED = YES + +# If the WARN_IF_DOC_ERROR tag is set to YES, doxygen will generate warnings for +# potential errors in the documentation, such as not documenting some parameters +# in a documented function, or documenting parameters that don't exist or using +# markup commands wrongly. +# The default value is: YES. + +WARN_IF_DOC_ERROR = YES + +# This WARN_NO_PARAMDOC option can be enabled to get warnings for functions that +# are documented, but have no documentation for their parameters or return +# value. If set to NO doxygen will only warn about wrong or incomplete parameter +# documentation, but not about the absence of documentation. +# The default value is: NO. + +WARN_NO_PARAMDOC = NO + +# The WARN_FORMAT tag determines the format of the warning messages that doxygen +# can produce. The string should contain the $file, $line, and $text tags, which +# will be replaced by the file and line number from which the warning originated +# and the warning text. Optionally the format may contain $version, which will +# be replaced by the version of the file (if it could be obtained via +# FILE_VERSION_FILTER) +# The default value is: $file:$line: $text. + +WARN_FORMAT = "$file:$line: $text" + +# The WARN_LOGFILE tag can be used to specify a file to which warning and error +# messages should be written. If left blank the output is written to standard +# error (stderr). + +WARN_LOGFILE = + +#--------------------------------------------------------------------------- +# Configuration options related to the input files +#--------------------------------------------------------------------------- + +# The INPUT tag is used to specify the files and/or directories that contain +# documented source files. You may enter file names like myfile.cpp or +# directories like /usr/src/myproject. Separate the files or directories with +# spaces. +# Note: If this tag is empty the current directory is searched. + +INPUT = vl \ + toolbox/mexutils.h \ + src/generic-driver.h + +# This tag can be used to specify the character encoding of the source files +# that doxygen parses. Internally doxygen uses the UTF-8 encoding. Doxygen uses +# libiconv (or the iconv built into libc) for the transcoding. See the libiconv +# documentation (see: http://www.gnu.org/software/libiconv) for the list of +# possible encodings. +# The default value is: UTF-8. + +INPUT_ENCODING = UTF-8 + +# If the value of the INPUT tag contains directories, you can use the +# FILE_PATTERNS tag to specify one or more wildcard patterns (like *.cpp and +# *.h) to filter out the source-files in the directories. If left blank the +# following patterns are tested:*.c, *.cc, *.cxx, *.cpp, *.c++, *.java, *.ii, +# *.ixx, *.ipp, *.i++, *.inl, *.idl, *.ddl, *.odl, *.h, *.hh, *.hxx, *.hpp, +# *.h++, *.cs, *.d, *.php, *.php4, *.php5, *.phtml, *.inc, *.m, *.markdown, +# *.md, *.mm, *.dox, *.py, *.f90, *.f, *.for, *.tcl, *.vhd, *.vhdl, *.ucf, +# *.qsf, *.as and *.js. + +FILE_PATTERNS = *.h \ + *.c \ + *.tc + +# The RECURSIVE tag can be used to specify whether or not subdirectories should +# be searched for input files as well. +# The default value is: NO. + +RECURSIVE = NO + +# The EXCLUDE tag can be used to specify files and/or directories that should be +# excluded from the INPUT source files. This way you can easily exclude a +# subdirectory from a directory tree whose root is specified with the INPUT tag. +# +# Note that relative paths are relative to the directory from which doxygen is +# run. + +EXCLUDE = + +# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or +# directories that are symbolic links (a Unix file system feature) are excluded +# from the input. +# The default value is: NO. + +EXCLUDE_SYMLINKS = NO + +# If the value of the INPUT tag contains directories, you can use the +# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude +# certain files from those directories. +# +# Note that the wildcards are matched against the file with absolute path, so to +# exclude all test directories for example use the pattern */test/* + +EXCLUDE_PATTERNS = test_* + +# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names +# (namespaces, classes, functions, etc.) that should be excluded from the +# output. The symbol name can be a fully qualified name, a word, or if the +# wildcard * is used, a substring. Examples: ANamespace, AClass, +# AClass::ANamespace, ANamespace::*Test +# +# Note that the wildcards are matched against the file with absolute path, so to +# exclude all test directories use the pattern */test/* + +EXCLUDE_SYMBOLS = + +# The EXAMPLE_PATH tag can be used to specify one or more files or directories +# that contain example code fragments that are included (see the \include +# command). + +EXAMPLE_PATH = vl/doc + +# If the value of the EXAMPLE_PATH tag contains directories, you can use the +# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp and +# *.h) to filter out the source-files in the directories. If left blank all +# files are included. + +EXAMPLE_PATTERNS = + +# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be +# searched for input files to be used with the \include or \dontinclude commands +# irrespective of the value of the RECURSIVE tag. +# The default value is: NO. + +EXAMPLE_RECURSIVE = NO + +# The IMAGE_PATH tag can be used to specify one or more files or directories +# that contain images that are to be included in the documentation (see the +# \image command). + +IMAGE_PATH = doc/figures + +# The INPUT_FILTER tag can be used to specify a program that doxygen should +# invoke to filter for each input file. Doxygen will invoke the filter program +# by executing (via popen()) the command: +# +# +# +# where is the value of the INPUT_FILTER tag, and is the +# name of an input file. Doxygen will then use the output that the filter +# program writes to standard output. If FILTER_PATTERNS is specified, this tag +# will be ignored. +# +# Note that the filter must not add or remove lines; it is applied before the +# code is scanned, but not when the output code is generated. If lines are added +# or removed, the anchors will not be placed correctly. + +INPUT_FILTER = "\ +sed -e 's/\/\*\* -----------* *$/\/** /g' \ + -e \"s/__VLFEAT_VERSION__/$(cat VERSION)/g\" \ + -e \"s/@cite{\([a-zA-Z0-9-]*\)}/@cite \1 /g\" \ + -e 's/\([^f]\)\$/\1@f$/g' \ + -e 's/^\$/@f$/g' \ + -e 's/\\\[/@f[/g' \ + -e 's/\\\]/@f]/g' \ +" +# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern +# basis. Doxygen will compare the file name with each pattern and apply the +# filter if there is a match. The filters are a list of the form: pattern=filter +# (like *.cpp=my_cpp_filter). See INPUT_FILTER for further information on how +# filters are used. If the FILTER_PATTERNS tag is empty or if none of the +# patterns match the file name, INPUT_FILTER is applied. + +FILTER_PATTERNS = + +# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using +# INPUT_FILTER ) will also be used to filter the input files that are used for +# producing the source files to browse (i.e. when SOURCE_BROWSER is set to YES). +# The default value is: NO. + +FILTER_SOURCE_FILES = NO + +# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file +# pattern. A pattern will override the setting for FILTER_PATTERN (if any) and +# it is also possible to disable source filtering for a specific pattern using +# *.ext= (so without naming a filter). +# This tag requires that the tag FILTER_SOURCE_FILES is set to YES. + +FILTER_SOURCE_PATTERNS = + +# If the USE_MDFILE_AS_MAINPAGE tag refers to the name of a markdown file that +# is part of the input, its contents will be placed on the main page +# (index.html). This can be useful if you have a project on for instance GitHub +# and want to reuse the introduction page also for the doxygen output. + +USE_MDFILE_AS_MAINPAGE = + +#--------------------------------------------------------------------------- +# Configuration options related to source browsing +#--------------------------------------------------------------------------- + +# If the SOURCE_BROWSER tag is set to YES then a list of source files will be +# generated. Documented entities will be cross-referenced with these sources. +# +# Note: To get rid of all source code in the generated output, make sure that +# also VERBATIM_HEADERS is set to NO. +# The default value is: NO. + +SOURCE_BROWSER = NO + +# Setting the INLINE_SOURCES tag to YES will include the body of functions, +# classes and enums directly into the documentation. +# The default value is: NO. + +INLINE_SOURCES = NO + +# Setting the STRIP_CODE_COMMENTS tag to YES will instruct doxygen to hide any +# special comment blocks from generated source code fragments. Normal C, C++ and +# Fortran comments will always remain visible. +# The default value is: YES. + +STRIP_CODE_COMMENTS = YES + +# If the REFERENCED_BY_RELATION tag is set to YES then for each documented +# function all documented functions referencing it will be listed. +# The default value is: NO. + +REFERENCED_BY_RELATION = NO + +# If the REFERENCES_RELATION tag is set to YES then for each documented function +# all documented entities called/used by that function will be listed. +# The default value is: NO. + +REFERENCES_RELATION = NO + +# If the REFERENCES_LINK_SOURCE tag is set to YES and SOURCE_BROWSER tag is set +# to YES, then the hyperlinks from functions in REFERENCES_RELATION and +# REFERENCED_BY_RELATION lists will link to the source code. Otherwise they will +# link to the documentation. +# The default value is: YES. + +REFERENCES_LINK_SOURCE = NO + +# If SOURCE_TOOLTIPS is enabled (the default) then hovering a hyperlink in the +# source code will show a tooltip with additional information such as prototype, +# brief description and links to the definition and documentation. Since this +# will make the HTML file larger and loading of large files a bit slower, you +# can opt to disable this feature. +# The default value is: YES. +# This tag requires that the tag SOURCE_BROWSER is set to YES. + +SOURCE_TOOLTIPS = YES + +# If the USE_HTAGS tag is set to YES then the references to source code will +# point to the HTML generated by the htags(1) tool instead of doxygen built-in +# source browser. The htags tool is part of GNU's global source tagging system +# (see http://www.gnu.org/software/global/global.html). You will need version +# 4.8.6 or higher. +# +# To use it do the following: +# - Install the latest version of global +# - Enable SOURCE_BROWSER and USE_HTAGS in the config file +# - Make sure the INPUT points to the root of the source tree +# - Run doxygen as normal +# +# Doxygen will invoke htags (and that will in turn invoke gtags), so these +# tools must be available from the command line (i.e. in the search path). +# +# The result: instead of the source browser generated by doxygen, the links to +# source code will now point to the output of htags. +# The default value is: NO. +# This tag requires that the tag SOURCE_BROWSER is set to YES. + +USE_HTAGS = NO + +# If the VERBATIM_HEADERS tag is set the YES then doxygen will generate a +# verbatim copy of the header file for each class for which an include is +# specified. Set to NO to disable this. +# See also: Section \class. +# The default value is: YES. + +VERBATIM_HEADERS = NO + +#--------------------------------------------------------------------------- +# Configuration options related to the alphabetical class index +#--------------------------------------------------------------------------- + +# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index of all +# compounds will be generated. Enable this if the project contains a lot of +# classes, structs, unions or interfaces. +# The default value is: YES. + +ALPHABETICAL_INDEX = YES + +# The COLS_IN_ALPHA_INDEX tag can be used to specify the number of columns in +# which the alphabetical index list will be split. +# Minimum value: 1, maximum value: 20, default value: 5. +# This tag requires that the tag ALPHABETICAL_INDEX is set to YES. + +COLS_IN_ALPHA_INDEX = 5 + +# In case all classes in a project start with a common prefix, all classes will +# be put under the same header in the alphabetical index. The IGNORE_PREFIX tag +# can be used to specify a prefix (or a list of prefixes) that should be ignored +# while generating the index headers. +# This tag requires that the tag ALPHABETICAL_INDEX is set to YES. + +IGNORE_PREFIX = + +#--------------------------------------------------------------------------- +# Configuration options related to the HTML output +#--------------------------------------------------------------------------- + +# If the GENERATE_HTML tag is set to YES doxygen will generate HTML output +# The default value is: YES. + +GENERATE_HTML = YES + +# The HTML_OUTPUT tag is used to specify where the HTML docs will be put. If a +# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of +# it. +# The default directory is: html. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_OUTPUT = api + +# The HTML_FILE_EXTENSION tag can be used to specify the file extension for each +# generated HTML page (for example: .htm, .php, .asp). +# The default value is: .html. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_FILE_EXTENSION = .html + +# The HTML_HEADER tag can be used to specify a user-defined HTML header file for +# each generated HTML page. If the tag is left blank doxygen will generate a +# standard header. +# +# To get valid HTML the header file that includes any scripts and style sheets +# that doxygen needs, which is dependent on the configuration options used (e.g. +# the setting GENERATE_TREEVIEW). It is highly recommended to start with a +# default header using +# doxygen -w html new_header.html new_footer.html new_stylesheet.css +# YourConfigFile +# and then modify the file new_header.html. See also section "Doxygen usage" +# for information on how to generate the default header that doxygen normally +# uses. +# Note: The header is subject to change so you typically have to regenerate the +# default header when upgrading to a newer version of doxygen. For a description +# of the possible markers and block names see the documentation. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_HEADER = doc/build/doxygen_header.html + +# The HTML_FOOTER tag can be used to specify a user-defined HTML footer for each +# generated HTML page. If the tag is left blank doxygen will generate a standard +# footer. See HTML_HEADER for more information on how to generate a default +# footer and what special commands can be used inside the footer. See also +# section "Doxygen usage" for information on how to generate the default footer +# that doxygen normally uses. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_FOOTER = doc/build/doxygen_footer.html + +# The HTML_STYLESHEET tag can be used to specify a user-defined cascading style +# sheet that is used by each HTML page. It can be used to fine-tune the look of +# the HTML output. If left blank doxygen will generate a default style sheet. +# See also section "Doxygen usage" for information on how to generate the style +# sheet that doxygen normally uses. +# Note: It is recommended to use HTML_EXTRA_STYLESHEET instead of this tag, as +# it is more robust and this tag (HTML_STYLESHEET) will in the future become +# obsolete. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_STYLESHEET = + +# The HTML_EXTRA_STYLESHEET tag can be used to specify an additional user- +# defined cascading style sheet that is included after the standard style sheets +# created by doxygen. Using this option one can overrule certain style aspects. +# This is preferred over using HTML_STYLESHEET since it does not replace the +# standard style sheet and is therefor more robust against future updates. +# Doxygen will copy the style sheet file to the output directory. For an example +# see the documentation. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_EXTRA_STYLESHEET = + +# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or +# other source files which should be copied to the HTML output directory. Note +# that these files will be copied to the base HTML output directory. Use the +# $relpath^ marker in the HTML_HEADER and/or HTML_FOOTER files to load these +# files. In the HTML_STYLESHEET file, use the file name only. Also note that the +# files will be copied as-is; there are no commands or markers available. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_EXTRA_FILES = + +# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output. Doxygen +# will adjust the colors in the stylesheet and background images according to +# this color. Hue is specified as an angle on a colorwheel, see +# http://en.wikipedia.org/wiki/Hue for more information. For instance the value +# 0 represents red, 60 is yellow, 120 is green, 180 is cyan, 240 is blue, 300 +# purple, and 360 is red again. +# Minimum value: 0, maximum value: 359, default value: 220. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_COLORSTYLE_HUE = 220 + +# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of the colors +# in the HTML output. For a value of 0 the output will use grayscales only. A +# value of 255 will produce the most vivid colors. +# Minimum value: 0, maximum value: 255, default value: 100. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_COLORSTYLE_SAT = 100 + +# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to the +# luminance component of the colors in the HTML output. Values below 100 +# gradually make the output lighter, whereas values above 100 make the output +# darker. The value divided by 100 is the actual gamma applied, so 80 represents +# a gamma of 0.8, The value 220 represents a gamma of 2.2, and 100 does not +# change the gamma. +# Minimum value: 40, maximum value: 240, default value: 80. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_COLORSTYLE_GAMMA = 80 + +# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML +# page will contain the date and time when the page was generated. Setting this +# to NO can help when comparing the output of multiple runs. +# The default value is: YES. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_TIMESTAMP = YES + +# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML +# documentation will contain sections that can be hidden and shown after the +# page has loaded. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_DYNAMIC_SECTIONS = NO + +# With HTML_INDEX_NUM_ENTRIES one can control the preferred number of entries +# shown in the various tree structured indices initially; the user can expand +# and collapse entries dynamically later on. Doxygen will expand the tree to +# such a level that at most the specified number of entries are visible (unless +# a fully collapsed tree already exceeds this amount). So setting the number of +# entries 1 will produce a full collapsed tree by default. 0 is a special value +# representing an infinite number of entries and will result in a full expanded +# tree by default. +# Minimum value: 0, maximum value: 9999, default value: 100. +# This tag requires that the tag GENERATE_HTML is set to YES. + +HTML_INDEX_NUM_ENTRIES = 100 + +# If the GENERATE_DOCSET tag is set to YES, additional index files will be +# generated that can be used as input for Apple's Xcode 3 integrated development +# environment (see: http://developer.apple.com/tools/xcode/), introduced with +# OSX 10.5 (Leopard). To create a documentation set, doxygen will generate a +# Makefile in the HTML output directory. Running make will produce the docset in +# that directory and running make install will install the docset in +# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find it at +# startup. See http://developer.apple.com/tools/creatingdocsetswithdoxygen.html +# for more information. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_DOCSET = NO + +# This tag determines the name of the docset feed. A documentation feed provides +# an umbrella under which multiple documentation sets from a single provider +# (such as a company or product suite) can be grouped. +# The default value is: Doxygen generated docs. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_FEEDNAME = "Doxygen generated docs" + +# This tag specifies a string that should uniquely identify the documentation +# set bundle. This should be a reverse domain-name style string, e.g. +# com.mycompany.MyDocSet. Doxygen will append .docset to the name. +# The default value is: org.doxygen.Project. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_BUNDLE_ID = org.doxygen.Project + +# The DOCSET_PUBLISHER_ID tag specifies a string that should uniquely identify +# the documentation publisher. This should be a reverse domain-name style +# string, e.g. com.mycompany.MyDocSet.documentation. +# The default value is: org.doxygen.Publisher. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_PUBLISHER_ID = org.doxygen.Publisher + +# The DOCSET_PUBLISHER_NAME tag identifies the documentation publisher. +# The default value is: Publisher. +# This tag requires that the tag GENERATE_DOCSET is set to YES. + +DOCSET_PUBLISHER_NAME = Publisher + +# If the GENERATE_HTMLHELP tag is set to YES then doxygen generates three +# additional HTML index files: index.hhp, index.hhc, and index.hhk. The +# index.hhp is a project file that can be read by Microsoft's HTML Help Workshop +# (see: http://www.microsoft.com/en-us/download/details.aspx?id=21138) on +# Windows. +# +# The HTML Help Workshop contains a compiler that can convert all HTML output +# generated by doxygen into a single compiled HTML file (.chm). Compiled HTML +# files are now used as the Windows 98 help format, and will replace the old +# Windows help format (.hlp) on all Windows platforms in the future. Compressed +# HTML files also contain an index, a table of contents, and you can search for +# words in the documentation. The HTML workshop also contains a viewer for +# compressed HTML files. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_HTMLHELP = NO + +# The CHM_FILE tag can be used to specify the file name of the resulting .chm +# file. You can add a path in front of the file if the result should not be +# written to the html output directory. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +CHM_FILE = + +# The HHC_LOCATION tag can be used to specify the location (absolute path +# including file name) of the HTML help compiler ( hhc.exe). If non-empty +# doxygen will try to run the HTML help compiler on the generated index.hhp. +# The file has to be specified with full path. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +HHC_LOCATION = + +# The GENERATE_CHI flag controls if a separate .chi index file is generated ( +# YES) or that it should be included in the master .chm file ( NO). +# The default value is: NO. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +GENERATE_CHI = NO + +# The CHM_INDEX_ENCODING is used to encode HtmlHelp index ( hhk), content ( hhc) +# and project file content. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +CHM_INDEX_ENCODING = + +# The BINARY_TOC flag controls whether a binary table of contents is generated ( +# YES) or a normal table of contents ( NO) in the .chm file. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +BINARY_TOC = NO + +# The TOC_EXPAND flag can be set to YES to add extra items for group members to +# the table of contents of the HTML help documentation and to the tree view. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTMLHELP is set to YES. + +TOC_EXPAND = NO + +# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and +# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated that +# can be used as input for Qt's qhelpgenerator to generate a Qt Compressed Help +# (.qch) of the generated HTML documentation. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_QHP = NO + +# If the QHG_LOCATION tag is specified, the QCH_FILE tag can be used to specify +# the file name of the resulting .qch file. The path specified is relative to +# the HTML output folder. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QCH_FILE = + +# The QHP_NAMESPACE tag specifies the namespace to use when generating Qt Help +# Project output. For more information please see Qt Help Project / Namespace +# (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#namespace). +# The default value is: org.doxygen.Project. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_NAMESPACE = org.doxygen.Project + +# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating Qt +# Help Project output. For more information please see Qt Help Project / Virtual +# Folders (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#virtual- +# folders). +# The default value is: doc. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_VIRTUAL_FOLDER = doc + +# If the QHP_CUST_FILTER_NAME tag is set, it specifies the name of a custom +# filter to add. For more information please see Qt Help Project / Custom +# Filters (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#custom- +# filters). +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_CUST_FILTER_NAME = + +# The QHP_CUST_FILTER_ATTRS tag specifies the list of the attributes of the +# custom filter to add. For more information please see Qt Help Project / Custom +# Filters (see: http://qt-project.org/doc/qt-4.8/qthelpproject.html#custom- +# filters). +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_CUST_FILTER_ATTRS = + +# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this +# project's filter section matches. Qt Help Project / Filter Attributes (see: +# http://qt-project.org/doc/qt-4.8/qthelpproject.html#filter-attributes). +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHP_SECT_FILTER_ATTRS = + +# The QHG_LOCATION tag can be used to specify the location of Qt's +# qhelpgenerator. If non-empty doxygen will try to run qhelpgenerator on the +# generated .qhp file. +# This tag requires that the tag GENERATE_QHP is set to YES. + +QHG_LOCATION = + +# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files will be +# generated, together with the HTML files, they form an Eclipse help plugin. To +# install this plugin and make it available under the help contents menu in +# Eclipse, the contents of the directory containing the HTML and XML files needs +# to be copied into the plugins directory of eclipse. The name of the directory +# within the plugins directory should be the same as the ECLIPSE_DOC_ID value. +# After copying Eclipse needs to be restarted before the help appears. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_ECLIPSEHELP = NO + +# A unique identifier for the Eclipse help plugin. When installing the plugin +# the directory name containing the HTML and XML files should also have this +# name. Each documentation set should have its own identifier. +# The default value is: org.doxygen.Project. +# This tag requires that the tag GENERATE_ECLIPSEHELP is set to YES. + +ECLIPSE_DOC_ID = org.doxygen.Project + +# If you want full control over the layout of the generated HTML pages it might +# be necessary to disable the index and replace it with your own. The +# DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs) at top +# of each HTML page. A value of NO enables the index and the value YES disables +# it. Since the tabs in the index contain the same information as the navigation +# tree, you can set this option to YES if you also set GENERATE_TREEVIEW to YES. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +DISABLE_INDEX = NO + +# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index +# structure should be generated to display hierarchical information. If the tag +# value is set to YES, a side panel will be generated containing a tree-like +# index structure (just like the one that is generated for HTML Help). For this +# to work a browser that supports JavaScript, DHTML, CSS and frames is required +# (i.e. any modern browser). Windows users are probably better off using the +# HTML help feature. Via custom stylesheets (see HTML_EXTRA_STYLESHEET) one can +# further fine-tune the look of the index. As an example, the default style +# sheet generated by doxygen has an example that shows how to put an image at +# the root of the tree instead of the PROJECT_NAME. Since the tree basically has +# the same information as the tab index, you could consider setting +# DISABLE_INDEX to YES when enabling this option. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +GENERATE_TREEVIEW = NONE + +# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values that +# doxygen will group on one line in the generated HTML documentation. +# +# Note that a value of 0 will completely suppress the enum values from appearing +# in the overview section. +# Minimum value: 0, maximum value: 20, default value: 4. +# This tag requires that the tag GENERATE_HTML is set to YES. + +ENUM_VALUES_PER_LINE = 4 + +# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be used +# to set the initial width (in pixels) of the frame in which the tree is shown. +# Minimum value: 0, maximum value: 1500, default value: 250. +# This tag requires that the tag GENERATE_HTML is set to YES. + +TREEVIEW_WIDTH = 250 + +# When the EXT_LINKS_IN_WINDOW option is set to YES doxygen will open links to +# external symbols imported via tag files in a separate window. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +EXT_LINKS_IN_WINDOW = NO + +# Use this tag to change the font size of LaTeX formulas included as images in +# the HTML documentation. When you change the font size after a successful +# doxygen run you need to manually remove any form_*.png images from the HTML +# output directory to force them to be regenerated. +# Minimum value: 8, maximum value: 50, default value: 10. +# This tag requires that the tag GENERATE_HTML is set to YES. + +FORMULA_FONTSIZE = 13 + +# Use the FORMULA_TRANPARENT tag to determine whether or not the images +# generated for formulas are transparent PNGs. Transparent PNGs are not +# supported properly for IE 6.0, but are supported on all modern browsers. +# +# Note that when changing this option you need to delete any form_*.png files in +# the HTML output directory before the changes have effect. +# The default value is: YES. +# This tag requires that the tag GENERATE_HTML is set to YES. + +FORMULA_TRANSPARENT = YES + +# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax (see +# http://www.mathjax.org) which uses client side Javascript for the rendering +# instead of using prerendered bitmaps. Use this if you do not have LaTeX +# installed or if you want to formulas look prettier in the HTML output. When +# enabled you may also need to install MathJax separately and configure the path +# to it using the MATHJAX_RELPATH option. +# The default value is: NO. +# This tag requires that the tag GENERATE_HTML is set to YES. + +USE_MATHJAX = YES + +# When MathJax is enabled you can set the default output format to be used for +# the MathJax output. See the MathJax site (see: +# http://docs.mathjax.org/en/latest/output.html) for more details. +# Possible values are: HTML-CSS (which is slower, but has the best +# compatibility), NativeMML (i.e. MathML) and SVG. +# The default value is: HTML-CSS. +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_FORMAT = HTML-CSS + +# When MathJax is enabled you need to specify the location relative to the HTML +# output directory using the MATHJAX_RELPATH option. The destination directory +# should contain the MathJax.js script. For instance, if the mathjax directory +# is located at the same level as the HTML output directory, then +# MATHJAX_RELPATH should be ../mathjax. The default value points to the MathJax +# Content Delivery Network so you can quickly see the result without installing +# MathJax. However, it is strongly recommended to install a local copy of +# MathJax from http://www.mathjax.org before deployment. +# The default value is: http://cdn.mathjax.org/mathjax/latest. +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_RELPATH = http://www.mathjax.org/mathjax + +# The MATHJAX_EXTENSIONS tag can be used to specify one or more MathJax +# extension names that should be enabled during MathJax rendering. For example +# MATHJAX_EXTENSIONS = TeX/AMSmath TeX/AMSsymbols +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_EXTENSIONS = + +# The MATHJAX_CODEFILE tag can be used to specify a file with javascript pieces +# of code that will be used on startup of the MathJax code. See the MathJax site +# (see: http://docs.mathjax.org/en/latest/output.html) for more details. For an +# example see the documentation. +# This tag requires that the tag USE_MATHJAX is set to YES. + +MATHJAX_CODEFILE = + +# When the SEARCHENGINE tag is enabled doxygen will generate a search box for +# the HTML output. The underlying search engine uses javascript and DHTML and +# should work on any modern browser. Note that when using HTML help +# (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets (GENERATE_DOCSET) +# there is already a search function so this one should typically be disabled. +# For large projects the javascript based search engine can be slow, then +# enabling SERVER_BASED_SEARCH may provide a better solution. It is possible to +# search using the keyboard; to jump to the search box use + S +# (what the is depends on the OS and browser, but it is typically +# , /