$ cd cmake-3.7.1
$ ./bootstrap --prefix=/usr
$ make
$ sudo make install
sudo apt-get update
sudo apt-get install openssh-server
sudo ufw allow 22
sudo apt-get install openssh-clientssh username@host
Then, we can simply the usage to connect to hostHost workstationHostName 10.70.70.44User darrenlPort 22
ssh workstation
Copy the public key to remote host using ssh-copy-id, thus, we didn't need to type password every timessh-copy-id -i ~/.ssh/id_rsa.pub remote-host
In your build.gradle file, adding the below snipet of code can generate the java doc of your module
configurations { javadocDeps } dependencies { compile fileTree(dir: 'libs', include: ['*.jar']) compile "com.android.support:support-annotations:${rootProject.ext.androidSupportSdkVersion}" javadocDeps "com.android.support:support-annotations:${rootProject.ext.androidSupportSdkVersion}"} task generateJavadocs(type: Javadoc) { source = android.sourceSets.main.java.srcDirs classpath += project.files(android.getBootClasspath() .join(File.pathSeparator)) classpath += configurations.javadocDeps failOnError false destinationDir = file("../javaDoc/") exclude { it.file.path.contains('aidl') } }
$ git clone https://github.com/google/flatbuffers
$ cd flatbuffers
Start to build$ cmake -G "Unix Makefiles"$ cmake -G "Visual Studio 10"$ cmake -G "Xcode"
$ make
After making it, there is one of executable files, called flatc. Now, we can use flatc to genereate different source files for different language using flatbuffers's interface definition language(IDL).$ vi resultcode.fbs
namespace tzutalin.common;Use the below command to generate its c++ header, python, and Java file.enum ResultCode { SUCCESS = 0, TIME_OUT, UNKNOWN_ERROR }
$ ./flatc --cpp --python --java -b resultcode.fbs
ResultCode.py// automatically generated by the FlatBuffers compiler, do not modify#ifndef FLATBUFFERS_GENERATED_RESULTCODE_TZUTALIN_COMMON_H_#define FLATBUFFERS_GENERATED_RESULTCODE_TZUTALIN_COMMON_H_#include "flatbuffers/flatbuffers.h"namespace tzutalin {namespace common {enum ResultCode {ResultCode_SUCCESS = 0,ResultCode_TIME_OUT = 1,ResultCode_UNKNOWN_ERROR = 2,ResultCode_MIN = ResultCode_SUCCESS,ResultCode_MAX = ResultCode_UNKNOWN_ERROR};inline const char **EnumNamesResultCode() {static const char *names[] = { "SUCCESS", "TIME_OUT", "UNKNOWN_ERROR", nullptr };return names;}inline const char *EnumNameResultCode(ResultCode e) { return EnumNamesResultCode()[static_cast<int>(e)]; }} // namespace common} // namespace tzutalin#endif // FLATBUFFERS_GENERATED_RESULTCODE_TZUTALIN_COMMON_H_
# automatically generated by the FlatBuffers compiler, do not modify# namespace: commonclass ResultCode(object):SUCCESS = 0TIME_OUT = 1UNKNOWN_ERROR = 2
// automatically generated by the FlatBuffers compiler, do not modifypackage tzutalin.common;public final class ResultCode {private ResultCode() { }public static final byte SUCCESS = 0;public static final byte TIME_OUT = 1;public static final byte UNKNOWN_ERROR = 2;public static final String[] names = { "SUCCESS", "TIME_OUT", "UNKNOWN_ERROR", };public static String name(int e) { return names[e]; }}
1. $ sudo apt install compizconfig-settings-manager2. $ ccsm3. Enable Ubuntu Unity Plugin. It will ask some questions because enabling it conflicts with another one.
#include <rapidjson/document.h> #include <rapidjson/prettywriter.h> #include <rapidjson/stringbuffer.h> #include <stdio.h> #include <sys/stat.h> using namespace rapidjson; std::stringstream ss_date; time_t t = time(0); struct tm * now = localtime(&t); ss_date << (now->tm_year + 1900) << '-' << (now->tm_mon + 1) << '-' << now->tm_mday; StringBuffer s; PrettyWriter<StringBuffer> writer(s); writer.StartObject(); writer.Key("version"); writer.String("1.0"); writer.Key("data"); writer.String(ss_date.str().c_str()); writer.Key("file"); writer.StartArray(); // m_vWriteFilePath is a vector<std::string> which contains 0.mp3 1.mp3 ... for (const auto& path : m_vWriteFilePath) { writer.String(path.c_str()); } writer.EndArray(); writer.EndObject(); std::ofstream of(m_indexFilePath); of << s.GetString(); if (!of.good()) throw std::runtime_error("Can't write the JSON string to the file!");Result:
{ "version": "1.0", "data": "2016-7-20", "file": [ "0.mp3", "1.mp3", "2.mp3", "3.mp3", "4.mp3" ] }
using namespace rapidjson; std::stringstream ss; std::ifstream file(m_indexFilePath); if (file) { ss << file.rdbuf(); file.close(); } else { throw std::runtime_error("!! Unable to open json file"); } Document doc; if (doc.Parse<0>(ss.str().c_str()).HasParseError()) throw std::invalid_argument("json parse error"); // Start parsing json string std::string version = doc["version"].GetString(); std::string date = doc["data"].GetString(); const Value& array = doc["file"]; for (rapidjson::SizeType i = 0; i < array.Size(); i++) { m_vReadFilePath.push_back(array[i].GetString()); }
To initialize with a different maximum value, first stop the Gradle daemon by calling ‘gradlew —-stop’.dexOptions is specifying a maximum number of 2 concurrent dx processes, but the Gradle daemon was initialized with 4.
android { ... dexOptions { jumboMode = true // Eabled it to allow a larger number of strings in the dex files maxProcessCount 1 // The maximum number of concurrent processes that can be used to dex. Defaults to 4. threadCount 1 // Number of threads to use when running dx. Defaults to 4. dexInProcess false //To disable dexing-in-process, add the following code to your module-level build.gradle file: preDexLibraries true // Whether to pre-dex libraries. This can improve incremental builds, but clean builds may be slower. } }
Conversion to Dalvik format failed: Unable to execute dex: method ID not in [0, 0xffff]: 65536
adb disable-verity/enable-verit can only be executed if your ROM is userdebug, and you cannot remount system partition if your image is user build.$ adb root $ adb disable-verity $ adb reboot $ adb wait-for-device $ adb remount
/system/vendor/lib/libOpenCL.so
or /system/lib/libOpenCL.so (older devices)/system/vendor/lib/egl/libGLES_mali.so
or /system/lib/egl/libGLES_mali.so/system/vendor/lib/libPVROCL.so$ wget http://mingliu.myweb.hinet.net/MingLiu/MingLiU.zip ; uznip MingLiU.zip ;$ sudo mkdir -p /usr/share/fonts/myfonts; sudo cp MingLiU.ttc /usr/share/fonts/myfont/新細明體.ttc$ fc-cache -v /usr/share/fonts/myfonts$ fc-listOne Millisecond Face Alignment with an Ensemble of Regression Trees by Vahid Kazemi and Josephine SullivanThe implementation of facial landmark extraction is fast enough, and it has 68 landmarks. Therefore, I spent a while to implement this feature to Android platform.
$ sudo apt-get install apache2
$ git clone https://github.com/tzutalin/tzutalin.github.io.git
$ cd tzutalin.github.io; sudo cp -rf . /var/www/html/
private $class$() { } private static class $class$LazyHolder { private static final $class$ INSTANCE = new $class$(); } public static $class$ getInstance() { return $class$LazyHolder.INSTANCE; }
$ lsusb–v
$ sudo apt-get install ros-fuerte-openni-kinect
if it is 0601 not 0600(old verison)
$ sudo apt-get install --reinstall libopenni-sensor-primesense0
$ sudo gedit /etc/openni/GlobalDefaults.ini
Set `UsbInterface=2`
$ sudo reboot$ roscore
$ roslaunch openni_launch openni.launch$ rosrun image_view image_view image:=/camera/rgb/image_color
$ rosrun image_view image_view image:=/camera/depth/image
$ git clone https://github.com/jefftee/dvo_slam.git$ rosmake dvo_core dvo_ros dvo_slam dvo_benchmark$ git clone -b fuerte https://github.com/tum-vision/dvo_slam.git$ git clone -b fuerte git@bitbucket.org:TzuTaLin/dvo_slam.git
$ export ROS_PACKAGE_PATH=$ROS_PACKAGE_PATH:~/dvo_slam
$ sudo apt-get install ros-fuerte-libg2o liblapack-dev libblas-dev freeglut3-dev libqglviewer-qt4-dev libsuitesparse-dev libx11-dev
$ rosmake dvo_core dvo_ros dvo_slam dvo_benchmark
$ roscd your_package_name && make clean
$ roslaunch dvo_slam qucikstart.lauch$ associate.py rgb.txt depth.txt > assoc.txt$ roslaunch dvo_benchmark benchmark.launch keep_alive
or
$ roslaunch dvo_benchmark benchmark.launch$ rosrun rqt rq