Read Matlab File Into LMDB/LevelDB

I found current Caffe lacking this functionality to read Matlab .mat file (of arbitrary channels, not restricted to RGB) into LMDB/LevelDB, and was motivated to write an extension for this:

convert_mat.cpp

To use it, put it under Caffe_directory/tools, and include proper Matlab headers and libraries in Caffe Makefile. I also included an example of the CMakeLists.txt:

CMakeLists.txt 

This works for Mac. Under linux, the matlab path would probably be

-I/opt/matlab/extern/include
-L/opt/matlab/bin/glnxa64

Hope this small piece of code would be helpful.

Reading .mat file in C++

The CMakeLists.txt:

cmake_minimum_required(VERSION 3.1)
project(mat2lmdb_cpp)

include_directories(/Applications/MATLAB_R2015a.app/extern/include)
link_directories(/Applications/MATLAB_R2015a.app/bin/maci64)

set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11 -lmx -lmat")
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/bin")

set(SOURCE_FILES    convert_mat.cpp)

add_executable(mat2lmdb_cpp ${SOURCE_FILES})

Before you run, add the following:

export MATLAB="/Applications/MATLAB_R2015a.app"

export DYLD_LIBRARY_PATH=$MATLAB/bin/maci64/:DYLD_LIBRARY_PATH

A Quick Look at How to Mount SFTP Drive on Mac

1. Install macfuse.
2. Install sshfs
3. Mount using:

sshfs -o defer_permissions -o ServerAliveInterval=10 harryyang@***.***.edu:/ /Users/temp/sshfs2

Unmount

umount -f /Users/temp/sshfs

Git switch branch

1. initialize from remote

git clone

2. update:

git pull

3. new branch:

git branch iss53

git checkout iss53

4. pull remote changes:

git reset --hard HEAD
git pull

CMakeLists Example

cmake_minimum_required(VERSION 3.1)
project(WebRun)

set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/bin")

include_directories(revlib/include include)
set(SOURCE_FILES main.cpp)
add_executable(WebRun ${SOURCE_FILES})
TARGET_LINK_LIBRARIES(WebRun libboost_system.a libboost_filesystem.a libsqlite3.a)

Another example:

cmake_minimum_required(VERSION 3.1)
project(Occlusion)
find_package(PCL 1.3 REQUIRED COMPONENTS common io octree surface)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/bin")

set(SOURCE_FILES    main.cpp)

add_executable(Occlusion ${SOURCE_FILES})
target_link_libraries(Occlusion ${PCL_LIBRARIES})

[Linux] Go to other partition

sudo mount /dev/sda2 /media

CLion Build Output Directory

Preferences: Build, Execution; CMake; Bin

Mac Essentials

Homebrew

XtraFinder

HyperDock

Atom not found symbol index for...

Turn off the strip optimization (-s).

The credit should go to some Chinese tech websites. Although I dislike searching in Chinese, but I found sometimes when you get stuck in some technical issues and become helpless with discussions on stackoverflow etc, they could be your last resort. =)

MatlabMPI

MPI_func('eval_bmaps_mpi',[40],{'localhost'},randomDirName('/share/project/shapes/harry'),mymaps,imnames,category,mymaps,SBDopts.path);

put config to get SBDopts.path

A Line Never Processed

It took me two hours to find out a bug in my code. At this time, two hours could mean a real saboteur. It is not something classic, but still it's worth marking down.

So I wanted to read 1000 lines from a huge file at a time, and I did the following:

while (true)

{

count := 0;

while (infile>> xyz && count <1000)

{

        do something with xyz;

        count ++;

}

do something;

if (count < 1000)

      break;

}

}

The code runs smooth, however it takes a long time for me to find out some lines are missing from the output.

Eventually I found out it all occurs at 

while (infile>> xyz && count <1000)

which means if count == 1000 it will still read another line to xyz but stops at the condition count<1000, and that line will never be processed.

Looks silly, but it does caused me a lot of panic. 

A New Caffe Branch Supporting High-dimensional LMDB Data

Added support of high-dimensional LMDB data. Training at your own risk.

https://github.com/leehomyc/caffe_lmdb

Ubuntu Launcher Stays Behind

Open your terminal by pressing Ctrl + Alt + T and type this following to solve this problem:

unity&disown

Emacs Parenthesis Highlight and Indent Region

Parenthesis Highlight:

M-x show-paren-mode RET

Indent Region:

C-M-\ 

Caffe Compile Problem

#error -- unsupported GNU version! gcc 4.9 and up are not supported!

comment this line out:

CUSTOM_CXX := /gcc-4.9.2/bin/g++

You may need to remove "/gcc-4.9.2/lib64" from LIBRARY_DIRS too.

Change this back when it's time to compile "matcaffe".

You need to run source  ~/.bashrc everytime you update it

Matlab visualization

hold on;
plot(y,x,'o',color,marker,'markersize',msz);
clf;

drawBoundary([],regions,color,width);

[x,y]=find(ucm>.1);plot(y,x,'r.','markersize',1)

h=iimagesc(b);
set(h,'AlphaData',0.5);

clf;

id=125;

name=ds.imnames{id};

mat=load(fullfile(ds.spdirs.slic,[name,'_slic_k600_m15.mat']));

im=mat.im;

p=load(['/share/data/vision-greg/harry/aeroplane/',name,'_pos.mat']);

pos_res=p.pos_res;

pos_res=pos_res';

t=cell2mat(pos_res);

t1=t(:,1);

t2=t(:,2);

imshow(im);

hold on;

plot(t2+17,t1+17,'o','Color','magenta','Marker','x','MarkerSize',8);

ucm=ds.loadUCM(id);

ucm=ucm>0.1;

hold on;

h=imagesc(ucm);

set(h,'AlphaData',0.4);

clf;

im2=rgb2gray(im);

samples=GetSamplePointsUCM(im2,ucm);

t3=samples(:,1);

t4=samples(:,2);

imshow(im);

hold on;

plot(t4,t3,'o','Color','magenta','Marker','x','MarkerSize',8);

clf;

gt=ds.loadGT(id);

gt=gt.groundTruth{1}.Segmentation;

gt(gt==255)=0;

gt=gt>1;

imshow(im);

hold on;

h2=imagesc(gt);

set(h2,'AlphaData',0.4);

SSHFS

sudo sshfs -o allow_other harryyang@sXXX.XXX:/share/ /mnt/share

fuse unmount: sudo umount

show using process fuser -mu /mnt/

caffe make runtest problem

 error while loading shared libraries: libcudart.so.7.0: cannot open shared object file: No such file or directory

Solution:

sudo ldconfig /usr/local/cuda-7.0/lib64

clustering in matlab

clusterdata(A','criterion','distance','cutoff',9.9)

matlab terminal

matlab -nojvm -nodisplay -nosplash