(April, 2010)
OpenCV 2.1 is basically a stabilized OpenCV 2.0, yet there are a few new features. >>> General modifications - SVN repository has been migrated from SourceForge to https://code.ros.org/svn/opencv. The bug tracker has been moved to https://code.ros.org/trac/opencv/. And we also have OpenCV twitter! http://twitter.com/opencvlibrary - The whole OpenCV is now using exceptions instead of the old libc-style mechanism. That is, instead of checking error code with cvGetErrStatus() (which currently always returns 0) you can now just call OpenCV functions inside C++ try-catch statements, cv::Exception is now derived from std::exception. - OpenCV does not support autotools-based build scripts, CMake (www.cmake.org) is the only way to build OpenCV on any OS. See http://opencv.willowgarage.com/wiki/InstallGuide. - All the parallel loops in OpenCV have been converted from OpenMP to Intel TBB (http://www.threadingbuildingblocks.org/). Thus parallel version of OpenCV can now be built using MSVC 2008 Express Edition or using earlier than 4.2 versions of GCC. - SWIG-based Python wrappers are still included, but they are not built by default and it's generally preferable to use the new wrappers. The python samples have been rewritten by James Bowman to use the new-style Python wrappers, which have been also created by James. - OpenCV can now be built and run in 64-bit mode on MacOSX 10.6 and Windows (see HighGUI and known problems below). On Windows both MSVC 2008 and mingw64 are known to work. - In theory OpenCV is now able to determine the host CPU on-fly and make use of SSE/SSE2/... instructions, if they are available. That is, it should be more safe to use WITH_SSE* flags in CMake. However, if you want maximum portability, it's recommended to turn on just WITH_SSE and WITH_SSE2 and leave other SSE* turned off, as we found that using WITH_SSE3, WITH_SSSE3 and WITH_SSE4_1 can yield the code incompatible with Intel's pre-Penryn or AMD chips. - Experimental "static" OpenCV configuration in CMake was contributed by Jose Luis Blanco. Pass "BUILD_SHARED_LIBS=OFF" to CMake to build OpenCV statically. >>> New functionality, features: - cxcore, cv, cvaux: * Grabcut (http://en.wikipedia.org/wiki/GrabCut) image segmentation algorithm has been implemented. See opencv/samples/c/grabcut.cpp * new improved version of one-way descriptor is added. See opencv/samples/c/one_way_sample.cpp * modified version of H. Hirschmuller semi-global stereo matching algorithm that we call SGBM (semi-global block matching) has been created. It is much faster than Kolmogorov's graph cuts-based algorithm and yet it's usually better than the block matching StereoBM algorithm. See opencv/samples/c/stereo_matching.cpp. * existing StereoBM stereo correspondence algorithm by K. Konolige was noticeably improved: added the optional left-right consistency check and speckle filtering, improved performance (by ~20%). * User can now control the image areas visible after the stereo rectification (see the extended stereoRectify/cvStereoRectify), and also limit the region where the disparity is computed (see CvStereoBMState::roi1, roi2; getValidDisparityROI). * Mixture-of-Gaussian based background subtraction algorithm has been rewritten for better performance and better accuracy. Alternative C++ interface BackgroundSubtractor has been provided, along with the possibility to use the trained background model to segment the foreground without updating the model. See opencv/samples/c/bgfg_segm.cpp. - highgui: * MacOSX: OpenCV now includes Cocoa and QTKit backends, in addition to Carbon and Quicktime. Therefore you can build OpenCV as 64-bit library. Thanks to Andre Cohen and Nicolas Butko, which components Note however that the backend are now in the alpha state, they can crash or leak memory, so for anything more serious than quick experiments you may prefer to use Carbon and Quicktime. To do that, pass USE_CARBON=ON and USE_QUICKTIME=ON to CMake and build OpenCV in 32-bit mode (i.e. select i386 architecture in Xcode). * Windows. OpenCV can now be built in 64-bit mode with MSVC 2008 and also mingw64. * Fullscreen has been added (thanks to Yannick Verdie). Call cvSetWindowProperty(window_name, CV_WINDOW_FULLSCREEN, 1) to make the particular window to fill the whole screen. This feature is not supported in the Cocoa bindings yet. * gstreamer backend has been improved a lot (thanks to Stefano Fabri) >>> New tests: - A few dozens of new tests have been written and many existing tests have been extended to verify OpenCV correctness thoroughly. As a result, we brought the test coverage from rather mediocre numbers to pretty impressive ones (especially for cxcore and cv)! Module OpenCV 2.0 coverage OpenCV 2.1 (functions/conditions) (functions/conditions) cxcore 65/54 91/73 cv 52/46 80/68 ml 66/47 73/52 highgui 17/3 54/27 cvaux 0/0 5/12 - Many new regression tests have been written in Python that check both OpenCV and the new-style bindings. - The test data moved to the separate repository: https://code.ros.org/svn/opencv/trunk/opencv_extra/testdata. And it is not included into the package, thus some tests from the cvtest and mltest will report about the missing data. You can download the directory to your hard drive and run cvtest like: ./cvtest -d/testdata/cv ./mltest -d /testdata/ml - The test engine has been improved: added flags -tn, -seed, -r the detailed information about failed tests is displayed right in the console. >>> Bug fixes: - about 200 bugs have been fixed. For the list of closed and still open bugs, please look at https://code.ros.org/trac/opencv/report and http://sourceforge.net/tracker/?group_id=22870&atid=376677. >>> Known problems/limitations. - there are some sporadic test failures on different platforms. Most probably they are caused by some very special test cases (that are usually generated randomly on each test run) and the test cases are not properly handled by the functions or by the tests. Some of the tests have been reproduced and reported here: https://code.ros.org/trac/opencv/ticket/29 https://code.ros.org/trac/opencv/ticket/113 https://code.ros.org/trac/opencv/ticket/114 - the new Python bindings do not include interface for the new C++ functionality and MLL. this is going to be addressed in some special intermediate OpenCV release - documentation is also incomplete at the moment and there are occasional formatting, grammar and semantical errors. We continue to improve it on a regular basis. Please, check the up-to-date online documentation at: http://opencv.willowgarage.com/documentation/c/index.html (C) http://opencv.willowgarage.com/documentation/cpp/index.html (C++) http://opencv.willowgarage.com/documentation/python/index.html (Python) - please also check the list of open bugs at https://code.ros.org/trac/opencv/report and http://sourceforge.net/tracker/?group_id=22870&atid=376677.
(September, 2009)
>>> New functionality, features: <<< - General: * The brand-new C++ interface for most of OpenCV functionality (cxcore, cv, highgui) has been introduced. Generally it means that you will need to do less coding to achieve the same results; it brings automatic memory management and many other advantages. See the C++ Reference section in opencv/doc/opencv.pdf and opencv/include/opencv/*.hpp. The previous interface is retained and still supported. * The source directory structure has been reogranized; now all the external headers are placed in the single directory on all platforms. * The primary build system is CMake, http://www.cmake.org (2.6.x is the preferable version). + In Windows package the project files for Visual Studio, makefiles for MSVC, Borland C++ or MinGW are note supplied anymore; please, generate them using CMake. + In MacOSX the users can generate project files for Xcode. + In Linux and any other platform the users can generate project files for cross-platform IDEs, such as Eclipse or Code Blocks, or makefiles for building OpenCV from a command line. * OpenCV repository has been converted to Subversion, hosted at SourceForge: http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary where the very latest snapshot is at http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary/trunk, and the more or less stable version can be found at http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary/tags/latest_tested_snapshot - CXCORE, CV, CVAUX: * CXCORE now uses Lapack (CLapack <IP_ADDRESS> in OpenCV 2.0) in its various linear algebra functions (such as solve, invert, SVD, determinant, eigen etc.) and the corresponding old-style functions (cvSolve, cvInvert etc.) * Lots of new feature and object detectors and descriptors have been added (there is no documentation on them yet), see cv.hpp and cvaux.hpp: + FAST - the fast corner detector, submitted by Edward Rosten + MSER - maximally stable extremal regions, submitted by Liu Liu + LDetector - fast circle-based feature detector by V. Lepetit (a.k.a. YAPE) + Fern-based point classifier and the planar object detector - based on the works by M. Ozuysal and V. Lepetit + One-way descriptor - a powerful PCA-based feature descriptor, (S. Hinterstoisser, O. Kutter, N. Navab, P. Fua, and V. Lepetit, "Real-Time Learning of Accurate Patch Rectification"). Contributed by Victor Eruhimov + Spin Images 3D feature descriptor - based on the A. Johnson PhD thesis; implemented by Anatoly Baksheev + Self-similarity features - contributed by Rainer Leinhart + HOG people and object detector - the reimplementation of Navneet Dalal framework (http://pascal.inrialpes.fr/soft/olt/). Currently, only the detection part is ported, but it is fully compatible with the original training code. See cvaux.hpp and opencv/samples/c/peopledetect.cpp. + Extended variant of the Haar feature-based object detector - implemented by Maria Dimashova. It now supports Haar features and LBPs (local binary patterns); other features can be more or less easily added + Adaptive skin detector and the fuzzy meanshift tracker - contributed by Farhad Dadgostar, see cvaux.hpp and opencv/samples/c/adaptiveskindetector.cpp * The new traincascade application complementing the new-style HAAR+LBP object detector has been added. See opencv/apps/traincascade. * The powerful library for approximate nearest neighbor search FLANN by Marius Muja is now shipped with OpenCV, and the OpenCV-style interface to the library is included into cxcore. See cxcore.hpp and opencv/samples/c/find_obj.cpp * The bundle adjustment engine has been contributed by PhaseSpace; see cvaux.hpp * Added dense optical flow estimation function (based on the paper "Two-Frame Motion Estimation Based on Polynomial Expansion" by G. Farnerback). See cv::calcOpticalFlowFarneback and the C++ documentation * Image warping operations (resize, remap, warpAffine, warpPerspective) now all support bicubic and Lanczos interpolation. * Most of the new linear and non-linear filtering operations (filter2D, sepFilter2D, erode, dilate ...) support arbitrary border modes and can use the valid image pixels outside of the ROI (i.e. the ROIs are not "isolated" anymore), see the C++ documentation. * The data can now be saved to and loaded from GZIP-compressed XML/YML files, e.g.: cvSave("a.xml.gz", my_huge_matrix); - MLL: * Added the Extremely Random Trees that train super-fast, comparing to Boosting or Random Trees (by Maria Dimashova). * The decision tree engine and based on it classes (Decision Tree itself, Boost, Random Trees) have been reworked and now: + they consume much less memory (up to 200% savings) + the training can be run in multiple threads (when OpenCV is built with OpenMP support) + the boosting classification on numerical variables is especially fast because of the specialized low-overhead branch. * mltest has been added. While far from being complete, it contains correctness tests for some of the MLL classes. - HighGUI: * [Linux] The support for stereo cameras (currently Videre only) has been added. There is now uniform interface for capturing video from two-, three- ... n-head cameras. * Images can now be compressed to or decompressed from buffers in the memory, see the C++ HighGUI reference manual - Documentation: * The reference manual has been converted from HTML to LaTeX (by James Bowman and Caroline Pantofaru), so there is now: + opencv.pdf for reading offline + and the online up-to-date documentation (as the result of LaTeX->Sphinx->HTML conversion) available at http://opencv.willowgarage.com/documentation/index.html - Samples, misc.: * Better eye detector has been contributed by Shiqi Yu, see opencv/data/haarcascades/*[lefteye|righteye]*.xml * sample LBP cascade for the frontal face detection has been created by Maria Dimashova, see opencv/data/lbpcascades/lbpcascade_frontalface.xml * Several high-quality body parts and facial feature detectors have been contributed by Modesto Castrillon-Santana, see opencv/data/haarcascades/haarcascade_mcs*.xml >>> Optimization: * Many of the basic functions and the image processing operations (like arithmetic operations, geometric image transformations, filtering etc.) have got SSE2 optimization, so they are several times faster. - The model of IPP support has been changed. Now IPP is supposed to be detected by CMake at the configuration stage and linked against OpenCV. (In the beta it is not implemented yet though). * PNG encoder performance improved by factor of 4 by tuning the parameters >>> Bug fixes: <<< TBD (see http://sourceforge.net/tracker/?group_id=22870&atid=376677 of the list of the closed and still opened bugs). Many thanks to everybody who submitted bug reports and/or provided the patches! >>> Known issues: * configure+autotools based build is currently broken. Please, use CMake. * OpenCV bug tracker at SF still lists about 150 open bugs. Some of them may be actually fixed already, and most of the remaining bugs are going to be fixed by OpenCV 2.0 gold. * IPP is not supported. As the new OpenCV includes a lot of SSE2 code, it may be not such a serious problem, though. The support (at least for most important functions that do not have SSE2 optimization) will be returned in 2.0 gold. * The documentation has been updated and improved a lot, but it still needs quite a bit of work: - some of the new functionality in cvaux is not described yet. - the bibliography part is broken - there are quite a few known bugs and typos there - many of the hyperlinks are not working. * The existing tests partly cover the new functionality (via the old backward-compatibility OpenCV 1.x API), but the coverage is not sufficient of course. * The new-style Python interface is not included yet Many of the problems will be addressed in 2.0 gold. If you have found some specific problem, please, put the record to the bug tracker: http://sourceforge.net/tracker/?group_id=22870 Better if the bug reports will include a small code sample in C++/python + all the necessary data files needed to reproduce the problem.
(September, 2009)
>>> New functionality, features: - General: * Installation package on Windows has been fixed, MinGW is used for precompiled binaries (see the release notes on the SourceForge site) * autotools-based build has been repaired - MLL: * The new-style class aliases (e.g. cv::SVM ~ CvSVM) and the train/predict methods, taking cv::Mat in addition to CvMat, have been added. So now MLL can be used more seamlesly with the rest of the restyled OpenCV. >>> Bug fixes: - A _lot_ of bugs present in 2.0 beta have been fixed, see the OpenCV bug tracker http://sourceforge.net/tracker/?group_id=22870&atid=376677 Thanks to everybody who submitted bug reports and/or patches!
(September, 2009)
>>> New functionality, features: <<< - General: * The brand-new C++ interface for most of OpenCV functionality (cxcore, cv, highgui) has been introduced. Generally it means that you will need to do less coding to achieve the same results; it brings automatic memory management and many other advantages. See the C++ Reference section in opencv/doc/opencv.pdf and opencv/include/opencv/*.hpp. The previous interface is retained and still supported. * The source directory structure has been reogranized; now all the external headers are placed in the single directory on all platforms. * The primary build system is CMake, http://www.cmake.org (2.6.x is the preferable version). + In Windows package the project files for Visual Studio, makefiles for MSVC, Borland C++ or MinGW are note supplied anymore; please, generate them using CMake. + In MacOSX the users can generate project files for Xcode. + In Linux and any other platform the users can generate project files for cross-platform IDEs, such as Eclipse or Code Blocks, or makefiles for building OpenCV from a command line. * OpenCV repository has been converted to Subversion, hosted at SourceForge: http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary where the very latest snapshot is at http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary/trunk, and the more or less stable version can be found at http://opencvlibrary.svn.sourceforge.net/svnroot/opencvlibrary/tags/latest_tested_snapshot - CXCORE, CV, CVAUX: * CXCORE now uses Lapack (CLapack <IP_ADDRESS> in OpenCV 2.0) in its various linear algebra functions (such as solve, invert, SVD, determinant, eigen etc.) and the corresponding old-style functions (cvSolve, cvInvert etc.) * Lots of new feature and object detectors and descriptors have been added (there is no documentation on them yet), see cv.hpp and cvaux.hpp: + FAST - the fast corner detector, submitted by Edward Rosten + MSER - maximally stable extremal regions, submitted by Liu Liu + LDetector - fast circle-based feature detector by V. Lepetit (a.k.a. YAPE) + Fern-based point classifier and the planar object detector - based on the works by M. Ozuysal and V. Lepetit + One-way descriptor - a powerful PCA-based feature descriptor, (S. Hinterstoisser, O. Kutter, N. Navab, P. Fua, and V. Lepetit, "Real-Time Learning of Accurate Patch Rectification"). Contributed by Victor Eruhimov + Spin Images 3D feature descriptor - based on the A. Johnson PhD thesis; implemented by Anatoly Baksheev + Self-similarity features - contributed by Rainer Leinhart + HOG people and object detector - the reimplementation of Navneet Dalal framework (http://pascal.inrialpes.fr/soft/olt/). Currently, only the detection part is ported, but it is fully compatible with the original training code. See cvaux.hpp and opencv/samples/c/peopledetect.cpp. + Extended variant of the Haar feature-based object detector - implemented by Maria Dimashova. It now supports Haar features and LBPs (local binary patterns); other features can be more or less easily added + Adaptive skin detector and the fuzzy meanshift tracker - contributed by Farhad Dadgostar, see cvaux.hpp and opencv/samples/c/adaptiveskindetector.cpp * The new traincascade application complementing the new-style HAAR+LBP object detector has been added. See opencv/apps/traincascade. * The powerful library for approximate nearest neighbor search FLANN by Marius Muja is now shipped with OpenCV, and the OpenCV-style interface to the library is included into cxcore. See cxcore.hpp and opencv/samples/c/find_obj.cpp * The bundle adjustment engine has been contributed by PhaseSpace; see cvaux.hpp * Added dense optical flow estimation function (based on the paper "Two-Frame Motion Estimation Based on Polynomial Expansion" by G. Farnerback). See cv::calcOpticalFlowFarneback and the C++ documentation * Image warping operations (resize, remap, warpAffine, warpPerspective) now all support bicubic and Lanczos interpolation. * Most of the new linear and non-linear filtering operations (filter2D, sepFilter2D, erode, dilate ...) support arbitrary border modes and can use the valid image pixels outside of the ROI (i.e. the ROIs are not "isolated" anymore), see the C++ documentation. * The data can now be saved to and loaded from GZIP-compressed XML/YML files, e.g.: cvSave("a.xml.gz", my_huge_matrix); - MLL: * Added the Extremely Random Trees that train super-fast, comparing to Boosting or Random Trees (by Maria Dimashova). * The decision tree engine and based on it classes (Decision Tree itself, Boost, Random Trees) have been reworked and now: + they consume much less memory (up to 200% savings) + the training can be run in multiple threads (when OpenCV is built with OpenMP support) + the boosting classification on numerical variables is especially fast because of the specialized low-overhead branch. * mltest has been added. While far from being complete, it contains correctness tests for some of the MLL classes. - HighGUI: * [Linux] The support for stereo cameras (currently Videre only) has been added. There is now uniform interface for capturing video from two-, three- ... n-head cameras. * Images can now be compressed to or decompressed from buffers in the memory, see the C++ HighGUI reference manual - Documentation: * The reference manual has been converted from HTML to LaTeX (by James Bowman and Caroline Pantofaru), so there is now: + opencv.pdf for reading offline + and the online up-to-date documentation (as the result of LaTeX->Sphinx->HTML conversion) available at http://opencv.willowgarage.com/documentation/index.html - Samples, misc.: * Better eye detector has been contributed by Shiqi Yu, see opencv/data/haarcascades/*[lefteye|righteye]*.xml * sample LBP cascade for the frontal face detection has been created by Maria Dimashova, see opencv/data/lbpcascades/lbpcascade_frontalface.xml * Several high-quality body parts and facial feature detectors have been contributed by Modesto Castrillon-Santana, see opencv/data/haarcascades/haarcascade_mcs*.xml >>> Optimization: * Many of the basic functions and the image processing operations (like arithmetic operations, geometric image transformations, filtering etc.) have got SSE2 optimization, so they are several times faster. - The model of IPP support has been changed. Now IPP is supposed to be detected by CMake at the configuration stage and linked against OpenCV. (In the beta it is not implemented yet though). * PNG encoder performance improved by factor of 4 by tuning the parameters >>> Bug fixes: <<< TBD (see http://sourceforge.net/tracker/?group_id=22870&atid=376677 of the list of the closed and still opened bugs). Many thanks to everybody who submitted bug reports and/or provided the patches! >>> Known issues: * configure+autotools based build is currently broken. Please, use CMake. * OpenCV bug tracker at SF still lists about 150 open bugs. Some of them may be actually fixed already, and most of the remaining bugs are going to be fixed by OpenCV 2.0 gold. * IPP is not supported. As the new OpenCV includes a lot of SSE2 code, it may be not such a serious problem, though. The support (at least for most important functions that do not have SSE2 optimization) will be returned in 2.0 gold. * The documentation has been updated and improved a lot, but it still needs quite a bit of work: - some of the new functionality in cvaux is not described yet. - the bibliography part is broken - there are quite a few known bugs and typos there - many of the hyperlinks are not working. * The existing tests partly cover the new functionality (via the old backward-compatibility OpenCV 1.x API), but the coverage is not sufficient of course. * The new-style Python interface is not included yet Many of the problems will be addressed in 2.0 gold. If you have found some specific problem, please, put the record to the bug tracker: http://sourceforge.net/tracker/?group_id=22870 Better if the bug reports will include a small code sample in C++/python + all the necessary data files needed to reproduce the problem.
(October, 2008)
>>> New functionality/features: <<< - General: * Octave bindings have been added. See interfaces/swig/octave (for now, Linux only) * [Windows] OpenCV is now built with VS2005 with SSE2 and OpenMP support included (if you want to rebuild OpenCV using Express or Standard Edition of VS, use _make\opencv.vs2005.no_openmp.sln). * [Windows] Python bindings have been updated to use Python 2.6 * [Windows] cvcam has been removed (as videoInput is now supported by highgui) - CXCORE, CV, CVAUX: * Speeded-up Robust Features (SURF), contributed by Liu Liu. see samples/c/find_obj.cpp and the documentation opencvref_cv.htm * Many improvements in camera calibration: - Added stereo camera calibration: cvStereoCalibrate, cvStereoRectify etc. - Single camera calibration now uses Levenberg-Marquardt method and supports extra flags to switch on/off optimization of individual camera parameters - The optional 3rd radial distortion parameter (k3*r^6) is now supported in every calibration-related function * 2 stereo correspondence algorithms: - very fast block matching method by Kurt Konolige (processes the Tsukuba stereo pair in <10ms on Core2Duo laptop) - slow but more accurate graph-cut based algorithm by Kolmogorov and Zabin * Better homography estimation algorithms (RANSAC and LMEDs) * new C++ template image classes contributed by Daniel Filip (Google inc.). see opencv/cxcore/include/cvwimage.h * Fast approximate nearest neighbor search (by Xavier Delacour) * Codebook method for background/foreground segmentation (by Gary Bradski) * Sort function (contributed by Shiqi Yu) * [OpenCV+IPP] Face Detection (cvHaarDetectObjects) now runs much faster (up to 2x faster) when using IPP 5.3 or higher. * Much faster (~4x faster) fixed-point variant of cvRemap has been added - MLL: * Python bindings for MLL have been added. There are no samples yet. - HighGUI: * [Windows, 32bit] Added support for videoInput library. Hence, cvcam is [almost] not needed anymore * [Windows, 32bit] FFMPEG can now be used for video decoding/encoding via ffopencv*.dll * [Linux] Added unicap support * Improved internal video capturing and video encoding APIs - Documentation: * OpenCV book has been published (sold separately :) see docs/index.htm) - New samples (opencv/samples): * Many Octave samples * find_obj.cpp (SURF), bgfg_codebook.cpp (Codebook BG/FG segmentation), stereo_calib.cpp (Stereo calibration and stereo correspondence) >>> Bug fixes: <<< Many thanks to everybody who submitted bug reports and/or provided the patches! * added dma_unlisten to icvCloseCAM_DC1394 (thanks to Victor Benso) * LMEDs algorithm for cvFindFundamentalMat estimation has been fixed * Broken debug build of highgui in VS2005/2008 (SF #2056185, SF #1709435) * cvFindChessboardCorners memory leak and incorrect size checks (SF #1972896, SF #1910323) * disabling GTK causes v4l runtime error (SF #2088102) * cvsetmousecallback bug (SF #2053529) * libhighgui needed deprecated "img_convert" replacement (SF #2011753) * Segfault in createsamples caused by uninitialized variable (SF #1977989) * Data Alignment Issue in bgfg_gaussmix (SF #1961755) * libpng need to be updated (SF #1952793) * cvCreateVideoWriter_Win32 - identifier not found (SF #1944254) * Bug in cvmorph.cpp (SF #1908844) * dilate (cvDilate) works bogus with default kernel (SF #1887130) * CvEM non-default constructor declared but not defined (SF #1830346) * cvFloodFill (in ver 1.0) Hangs (SF #1790565) * double delete in CvImage (SF #1733437) * cvFilter2D anchor default value is not working properly (SF #1713779) * cvCvtColor - Bug? in converting HSV2RGB (SF #1676344) * Invalid selection of the MKL-dll version in cvUseOptimized() (SF #1633017) * ... >>> Known issues: * Borland compiler is not supported (but might work) in this update. * 64-bit Windows is not supported (but might work) in this update. * SF bug tracker still contains over 50 records of open bugs. Many of them will be addressed in the next update.
(October, 2006)
>>> New functionality/features: <<< - General: * Windows installation package now includes precompiled Python module * Borland C++ (v5.6+) makefiles re-added (see _make\make_all_bc.mak) - CV: * Inpainting was added, see samples/c/inpaint.cpp (thanks to Alexander Kibkalo and Alexey Kalinichenko) - MLL: * Boosted tree classifiers added, see MLL reference manual - HighGUI: * Jpeg2000 and EXR support in highgui using JasPer and OpenEXR (thanks to Nils Hasler) OpenEXR is not built-in to highgui on Windows by default. See otherlibs/_graphics/readme.txt. * >8-bit image input/output for PNG, Jpeg2000 and OpenEXR (thanks to Nils Hasler) * Updated CMUcamera wrapper. * Several V4L2 improvements and fixes - New samples (opencv/samples): * Camera calibration sample: calibrate.cpp * Inpainting sample: inpaint.cpp * Letter recognition using the existing database with random trees/boosted trees/neural nets: leter_recog.cpp * A few new Python samples. - Tests: * Most old cv tests have been rewritten/converted to use cxts instead of trs. TRS is not used by the tests anymore. >>> Bug fixes: <<< Many thanks to everybody who submitted bug reports and/or provided the patches! * Incorrect normalization in cvFindFundamentalMat (SF #1550855) * Occasional cvGetQuadrangleSubPix crashes (SF #1549168) * Occasional cvCalcOpticalFlowPyrLK crashes * Internal GCC 3.x error in cvFloor/cvCeil (SF #1546657) * Several Python-related bugs (SF #1570109, SF #1572800, SF #1543593) * Bugs in contour processing/rendering (SF #1550889, * x86-64 related bugs (SF #1526133, SF #1527997) * OpenCV dispatcher tried to load old versions of IPP (pre 4.x) that caused many failures (see SF #1555093, for example) * Inaccurate results in some cases in cvFitEllipse, cvFitLine, cvHoughCircles. * Severe bug in Bayesian classifier, broken regression tree in MLL * Overflow in blurring filter * cvSaveImage() modified saved images leading to potential problems in threaded apps. * Numeric values in XML/YAML were emitted/parsed incorrectly on some non-US locales in Linux * VS2005 Express/Standard Editions could not build OpenCV (due to missing OpenMP support) * ... >>> Known issues: * Certain tests may fail on IA64 (Itanium), e.g. gaussian filter, fundamental matrix estimation, chessboard detector. ...


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Our team is passionate about urban development and the social implications of gentrification across the globe. Each of our team members is pursuing a master's degree in data science at UC Berkeley (MIDS), where we came together to build gentrifAI as our final capstone project. We hope this tool becomes a resource for those looking to make positive, well-informed change in city planning.
Hyera Moon’s passion in Data Science is to inspire young woman to embrace STEM awareness. A qualified actuary, Hyera has reinvented herself by applying outside-the-box thinking to the most pressing problems in society. Hyera can often be found in many of New York’s hidden chocolatiers and pastry shops.
Sho Ohata is an aspiring Data Scientist working for Con Edison - the utility company serving New York City. Pivoting from his early career spent in Engineering and construction Sho is interested in applying data science to deluge of information being generated from the ever-growing IoT devices. Sho can usually be found drinking gallons of caffeinated drinks - mainly coffee and tea.
Geoff Stirling is an aspiring Data Scientist who loves using data to help others solve interesting problems in complex fields. He currently works at Google, where he's passionate about making data science skills accessible to all. Geoff can often be found in local bookshops chasing after his toddler son, while profusely apologizing to the shop owner.


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About Geopastebin
Geopastebin aims to be a useful way to paste geographic information much like programmers and designers paste code snippets that they want to talk about or ask questions about. Geopastebin currently supports the following Tex-based geographic formats:
- Well Known Text (WKT)
- Extended Well Known Text (EWKT)
- GeoJSON
Support is in the works for KML. Other formats that would be nice to support include GPX, NMEA, and GML.
Colophon
Geopastebin is merely a thin layer of glue on top of lots of excellent open source projects:
- Django the web application framework written in Python
- GeoDjango a fantastic GIS development framework
- PostgreSQL the database
- PostGIS spatially enabling PostgreSQL
- Geometry Engine, Open Source (GEOS) used by both PostgreSQL and GeoDjango
- PROJ.4 for cartographic projections
- OpenLayers and django-olwidget for map display
Geopastebin is released as open source software under the new-style BSD license.


--- title: Text mining of Wimbledon tweets using rtweet and tidytext author: Jacquie Tran date: '2018-07-20' slug: text-mining-of-wimbledon-tweets-using-rtweet-and-tidytext categories: - Off-field analyses tags: - text mining - tennis - sports analytics - r stats - tidytext - rtweet draft: yes ---
This year, I started in a new role as Senior Insights Researcher at High Performance Sport New Zealand. For me, one of the big drawcards of this role was the opportunity to learn and grow my skills and competencies as a performance sport professional.
Our team regularly deals with qualitative data, so as an applied sport scientist with a strongly quantitative training, it has been a steep learning curve but also enjoyable to open my mind up to different ways of thinking and knowing.
Online discussions about sports analytics seem heavily focused on numbers and what we can do with quantitative data. I remain just as interested in these discussions as I was before starting my current job, but I also see opportunities for more of us in the sports analytics community to think about what else we can learn by capturing and analysing qualitative data. In that spirit, this post is a brief glimpse at what is possible when applying text mining methods.
I’ve been thinking about writing this post for a couple of months now, and every so often I trawl the internet looking for text corpuses that are relevant to sport - so far, my efforts have turned up fairly light results. (If anyone knowledgeable in this domain can point me to relevant open data sets, then please get in touch!)
So…it’s rtweet
to the rescue!
rtweet
is a slick package by Mike Kearney (@kearneymw) for downloading tweets and associated metadata. The package website is a great place to start if you want to give it a crack: https://rtweet.info/
When I started this blog post, Wimbledon 2018 was in its final days with the men’s singles playing quarter finals and the women’s singles playing semi finals. I used this script to download tweets that:
All I need to do here is load the libraries I need for this analysis and read the data sets into R from the CSV files stored in this Github repo.
# Load libraries
library(readr)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(tidytext)
# Read data into R
fed <- read_delim(
"https://raw.githubusercontent.com/jacquietran/2018_wimbledon_tweets/master/fed.csv",
delim = ",", col_names = TRUE, col_types = NULL)
serena <- read_delim(
"https://raw.githubusercontent.com/jacquietran/2018_wimbledon_tweets/master/serena.csv",
delim = ",", col_names = TRUE, col_types = NULL)
If you visually scan through the data set, you’ll see it has several variables. For the purposes of this post, I am most interested in the following:
text
: The text content of a tweet.favorite_count
: The number of times a tweet has been ‘favourited’ (or in modern Twitter parlance, ‘liked’…ugh) by other user accountsretweet_count
: The number of times a tweet has been ‘retweeted’ (shared) by other user accountsfollowers_count
: The number of user accounts that follow the account who posted a tweetNot familiar with Twitter? Here’s a quick primer that will help you get a lay of the land: Mom, This is How Twitter Works
We have our data and we know what variables we’re going to focus on. How do we get from raw tweet data to text mining?
Enter: the tidytext
package.
tidytext
package, point to book and tutorial(s)# Remove URLs using regex
fed$text <- gsub("http[[:alnum:][:punct:]]*", "", fed$text)
serena$text <- gsub("http[[:alnum:][:punct:]]*", "", serena$text)
# Ref: http://www.rdatamining.com/books/rdm/faq/removeurlsfromtext
# Remove emojis
fed$text <- gsub("[^\x01-\x7F]", "", fed$text)
serena$text <- gsub("[^\x01-\x7F]", "", serena$text)
# Ref: https://stackoverflow.com/questions/44893354/remove-emoticons-in-r-using-tm-package
# Unnest tokens using tidytext
fed_tidy <- fed %>%
select(user_id, status_id, screen_name,
favorite_count, retweet_count, followers_count, text) %>%
unnest_tokens(word, text) %>%
anti_join(stop_words)
## Joining, by = "word"
serena_tidy <- serena %>%
select(user_id, status_id, screen_name,
favorite_count, retweet_count, followers_count, text) %>%
unnest_tokens(word, text) %>%
anti_join(stop_words)
## Joining, by = "word"
# Count most frequently occurring words
fed_tidy %>% count(word, sort = TRUE) %>% filter(!word %in% c("federer", "wimbledon"))
## # A tibble: 14,791 x 2
## word n
## <chr> <int>
## 1 anderson 9746
## 2 roger 6596
## 3 kevin 4781
## 4 match 4126
## 5 nadal 2893
## 6 england 2670
## 7 set 2503
## 8 2 2322
## 9 sets 2191
## 10 lost 2084
## # ... with 14,781 more rows


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I was at my GP's for ingrown toenail, when after conversing on that topic, I informed him I had difficulty sleeping and did not want over the counter sleeping remedies such as 'Nytol' which are apparently addictive. So he prescribed me melatonin. It took a while for the pharmacy to stock it but after a week they had it in. I took it home and at about 9pm one night I took one 3mg capsule.
The effects were quite noticable. There was a severe tiredness, an urge to close the eyes. But there was more, my body still had the energy to go places and move, but I could'nt move. I was sleepy and I tried to get up and found even moving was quite a challenge. So I lay down on my bed and drifted off. I had a few capsules left the other day so me and my friend tried something different. We emptied the contents of two capsules (6mg) into a joint (We refer to it as a joint because it was tobacco and melatonin, not cannabis) and smoked it. The joint was very sweet and the effects of the melatonin arrived quick and powerful, things were slow and there was again a very severe urge to sleep.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


I am a Software Engineer with a background in Website/E-Commerce Management. Together they have allowed me to expand my skills to not only software development but also include project management, budgeting, marketing and content management. What I found during my career was a natural curiosity towards the full cycle of the web development process. This curiosity led me to a decision to refocus my career. After taking some time off to travel, it was time to pursue that passion.
This led me to General Assembly's Software Engineering Bootcamp. Here not only did I learn some new technologies but I was able to use them by developing some full-stack applications.
By putting these new skills together with my existing skills I look forward to joining a team and build some exciting web applications.
HTML, CSS, SASS, Bootstrap, Handlebars, JavaScript, AJAX, JSON, jQuery, Express, React, Ruby on Rails, SQL, NoSql, MongoDB, GIT, Github, Google Analytics, Photoshop, BaseCamp, various CMS
States Visited App – Keep track of the states you have visited along with some detailed information about each.
Technologies: Ruby on Rails, html/css, Bootstrap, JavaScript, jQuery
Bucket List App – Create bucket list of items you want to complete.
Technologies: Express, MongoDB, html/css, Bootstrap, jQuery
Image Upload App – This was a team project. Working together we created an app that will allows users to upload images to AWS for storage.
Technologies: Express, html/css, MongoDB, JavaScript


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Every command (<simple cmd> and <compound cmd>) is a scope. Since commands can be nested, scopes can be nested.
Each <script> is also a scope and encloses all other scopes within the script.
There is a single special built-in scope that encloses all script scopes. Build-in names are defined in the built-in scope.


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WEEK 28 SUNDAY
Entrance Antiphon
If you, O Lord, should mark iniquities, Lord, who could stand?
But with you is found forgiveness, O God of Israel.
Collect
May your grace, O Lord, we pray, at all times go before us and follow after, and make us always determined to carry out good works. Through our Lord. . .
Theme of the Sunday: We Are Invited to a Banquet, Not to a Funeral.
The banquet theme joins together the first reading and the gospel. The banquet is the symbol of the happiness and joy present in the kingdom of God. The first reading tells us of a promise; the gospel tells us of its actualisation. If the banquet has already begun (with the coming of the Messiah), why do we still have so much hatred, so many wars, deaths all over the world? Yes, the feast has begun, but the Kingdom is still awaiting its full attainment. The second reading is also connected with this theme. We are given the example of the community at Philippi where there is authentic love and where a completely new life has really begun; the help and the gifts sent to Paul are proof of this.
FIRST READING Isaiah 25:6-10
“The Lord will prepare a feast and will wipe away tears from all faces.”
 And he will destroy on this
mountain the covering that is cast over all peoples, the veil that is spread
over all nations. He will swallow up death for ever, and the Lord GOD will wipe
away tears from all faces, and the reproach of his people he will take away
from all the earth; for the LORD has spoken. It will be said on that day,
"Behold, this is our God; we have waited for him, that he might save us.
This is the LORD; we have waited for him; let us be glad and rejoice in his
salvation." For the hand of the LORD will rest on this mountain.
The word of the Lord
RESPONSORIAL PSALM Psalm 23:1-3a.3b-4.5.6 (R. 6cd)
R. In the Lord’s own house shall I dwell for length of days unending.
The LORD is my shepherd; there is nothing I
shall want. Fresh and green are the pastures where he gives me repose. Near
restful waters he leads me; he revives my soul.
R.
In the Lord’s own house shall I dwell for length of days unending.
He guides me along the right path, for the sake
of his name. Though I should walk in the valley of the shadow of death, no evil
would I fear, for you are with me.
R.
In the Lord’s own house shall I dwell for length of days unending.
You have prepared a table before me in the
sight of my foes. My head you have anointed with oil; my cup is overflowing.
R.
In the Lord’s own house shall I dwell for length of days unending.
Surely goodness and mercy shall follow me all
the days of my life. In the LORD's own house shall I dwell for length of days unending.
R.
In the Lord’s own house shall I dwell for length of days unending.
SECOND READING Philipians
4:12-14.19-20
“I can do all things in him who strengthens me.”
A reading from the Letter of Saint Paul to the Philippians
Brethren: I know how to be
abased, and I know how to abound; in any and all circumstances I have learned
the secret of facing plenty and hunger, abundance and want. I can do all things
in him who strengthens me. Yet it was kind of you to share my trouble. And my
God will supply every need of yours according to his riches in glory in Christ
Jesus. To our God and Father be glory for ever and ever. Amen.
The word of the Lord
ALLELUIA Ephesians 1:17-18
R. Alleluia. May the Father of our Lord Jesus Christ
enlighten the eyes of our hearts that we might know what is
the hope to which he has called us. R. Alleluia.
GOSPEL Matthew 22:1-10
“Invite to the marriage feast as many as you find.”
A reading from the holy Gospel according to Matthew
At that time: Again Jesus spoke to the chief
priests and elders of the people, in parables, saying, "The kingdom of
heaven may be compared to a king who gave a marriage feast for his son, and
sent his servants to call those who were invited to the marriage feast; but
they would not come. Again he sent other servants, saying, 'Tell those who are
invited, Behold, I have made ready my dinner, my oxen and my fat calves are
killed, and everything is ready; come to the marriage feast.' But they made
light of it and went off, one to his farm, another to his business, while the
rest seized his servants, treated them shamefully, and killed them. The king
was angry, and he sent his troops and destroyed those murderers and burned
their city. Then he said to his servants, 'The wedding is ready, but those
invited were not worthy. Go therefore to the thoroughfares, and invite to the
marriage feast as many as you find.' And those servants went out into the
streets and gathered all whom they found, both bad and good; so the wedding
hall was filled with guests. "But when the king came in to look at the
guests, he saw there a man who had no wedding garment; and he said to him,
'Friend, how did you get in here without a wedding garment?' And he was
speechless. Then the king said to the attendants, 'Bind him hand and foot, and
cast him into the outer darkness; there men will weep and gnash their teeth.'
For many are called, but few are chosen."
The Gospel of the Lord
Theme of the Sunday: Go, Sell All That You Have.
In our life we are required to make many choices. Many things attract us, and we cannot have them all. To choose some things means that we have to renounce others. The readings of today are on this theme of “choice.” The first passage mentions the choice of Solomon. He preferred wisdom to the goods of this world. The gospel tells the story of the rich man; Jesus asks him to make a very committed and important choice: either follow him, giving up all his riches, or keep his goods and lose him. The second reading tells us that the word of God is like a double-edged sword that penetrates deeply and uncovers all that is hidden in the human being. This is the word that forces one to take radical decisions.
FIRST READING Wisdom
7:7-11
“I accounted wealth as nothing in comparison with wisdom.”
A reading from the Book of Wisdom
I prayed, and understanding was given me; I
called upon God, and the spirit of wisdom came to me. I preferred her to
sceptres and thrones, and I accounted wealth as nothing in comparison with her.
Neither did I liken to her any priceless gem, because all gold is but a little
sand in her sight, and silver will be accounted as clay before her. I loved her
more than health and beauty, and I chose to have her rather than light, because
her radiance never ceases. All good things came to me along with her, and in her
hands uncounted wealth.
The word of the Lord
RESPONSORIAL PSALM
Psalm 90:12-13.14-15.16-17 (R. cf. 14)
R. Fill us with your merciful love, O Lord, and we shall exult.
Teach us to number our days,
that we may gain wisdom of heart. Turn back, O LORD! How long? Show pity
to your servants.
R.
Fill us with your merciful love, O Lord, and we shall exult.
At dawn, fill us with your merciful love; we
shall exult and rejoice all our days. Give us joy for the days of our
affliction, for the years when we looked upon evil.
R.
Fill us with your merciful love, O Lord, and we shall exult.
 Let the favour of the Lord our God be
upon us; give success to the work of our hands. O give success to the work of
our hands.
R.
Fill us with your merciful love, O Lord, and we shall exult.
SECOND READING Hebrews 4:12-13
“The word of God discerns the thoughts and intentions of the heart.”
A reading from the Letter to the Hebrews
The word of God is living and
active, sharper than any two-edged sword, piercing to the division of soul and
spirit, of joints and marrow, and discerning the thoughts and intentions of the
heart. And before him no creature is hidden, but all are open and laid bare to
the eyes of him with whom we have to do.
The word of the Lord
ALLELUIA Matthew
5:3
R. Alleluia. Blessed are the poor in spirit, for theirs is
the kingdom of heaven. R. Alleluia.
GOSPEL Mark 10:17-30
“Go, sell what you have, and come, follow me.”
A reading from the holy Gospel according to Mark
At that time: As Jesus was setting out on his
journey, a man ran up and knelt before him, and asked him, "Good Teacher,
what must I do to inherit eternal life?"  No one is good but God alone.
And he said to him, "Teacher, all these I have observed from my
youth." And Jesus looking upon him loved him, and said to him, "You
lack one thing; go, sell what you have, and give to the poor, and you will have
treasure in heaven; and come, follow me." At that saying his countenance
fell, and he went away sorrowful; for he had great possessions. And Jesus
looked around and said to his disciples, "How hard it will be for those
who trust in riches to enter the
The Gospel of the Lord
Theme of the Sunday: The One Who Heals Lepers Is Amongst Us.
Why are we proud when we do something good? Why do we feel superior to others? We forget that we are lepers who have been healed by the word of Jesus. The gospel tells us that the first to understand this truth were those Jews considered heretics. The first reading shows us Naaman, a leper and foreigner. He is healed both in body and in spirit by his encounter with the man sent by God. The second reading gives us the example of Paul, who was aware that he had been a ‘leper’. Christ saved him and enabled him to bear everything for the sake of the gospel.
FIRST READING 2 Kings 5:14-17
Naaman returned to the man of God and acknowledged the Lord.
A reading from the second Book of Kings
In those days: Naaman
the Syrian went down and dipped himself seven times in the Jordan, according to
the word of Elisha the man of God; and his flesh was restored like the flesh of
a little child, and he was clean. Then he returned to the man of God, he and
all his company, and he came and stood before him; and he said, "Behold, I
know that there is no God in all the earth but in
The word of the Lord
RESPONSORIAL PSALM Psalm 98:1.2-3ab.3cd-4 (R. cf. 2)
R. The Lord has shown his deliverance to the nations.
O sing a new song to the LORD, for he has
worked wonders. His right hand and his holy arm have brought salvation.
R.
The Lord has shown his deliverance to the nations.
The LORD has made known his salvation, has
shown his deliverance to the nations. He has remembered his merciful love and
his truth for the house of
R.
The Lord has shown his deliverance to the nations.
All the ends of the earth have seen the
salvation of our God. Shout to the LORD, all the earth; break forth into joyous
song, and sing out your praise.
R.
The Lord has shown his deliverance to the nations.
SECOND READING 2 Timothy 2:8-13
“If we endure, we shall also reign with Christ.”
A reading from the second Letter of Saint Paul to Timothy
Beloved: Remember Jesus Christ, risen from the
dead, descended from David, as preached in my gospel, the gospel for which I am
suffering and wearing fetters like a criminal. But the word of God is not
fettered. Therefore I endure everything for the sake of the elect, that they
also may obtain salvation in Christ Jesus with its eternal glory. The saying is
sure: If we have died with him, we shall also live with him; if we endure, we
shall also reign with him; if we deny him, he also will deny us; if we are
faithless, he remains faithful-- for he cannot deny himself.
The word of the Lord
ALLELUIA 1
Thessalonians 5:18
R. Alleluia. Give thanks in all circumstances; for this is
the will of God in Christ Jesus for you. R. Alleluia.
GOSPEL Luke 17:11-19
“Was no one found to return and give praise to God except this foreigner?”
A reading from the holy Gospel according to Luke
On the way to Jerusalem Jesus was passing along
between
The Gospel of the Lord
Prayer over the Offerings
Accept, O Lord, the prayers of your faithful with the sacrificial offerings, that, through these acts of devotedness, we may pass over to the glory of heaven. Through Christ our Lord.
Communion Antiphon
The rich suffer want and go hungry, but those who seek the Lord lack no blessing.
Or:
When the Lord appears, we shall be like him, for we shall see him as he is.
Prayer after Communion
We entreat your majesty most humbly, O Lord, that, as you feed us with the nourishment which comes from the most holy Body and Blood of your Son, so you may make us sharers of his divine nature. Who lives and reigns for ever and ever.


Click on the plot and use the scroll-wheel on the mouse, or a two-fingered scroll gesture to magnify the plot. Click and drag to move the plot around the screen.
Try hovering your mouse over a datapoint to find out more information - further information on IEDB epitopes can be found in the table below.


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@* main Template File *@ @(pageTitle:String,loginStatus:String,userName:String ="no user")(contents:Html)
@title(pageTitle) @styleSheet("home") @scripts("home") @navbar(loginStatus,userName) @contents @footer{Knoldus is a team of Passionate Technologists,focused on staying at the edge of the curve. We love to build Scalable,Performant, Concurrent systems with Functional Programming to meet the needs of the business. Our big data solutions have won accolades in domains like Social media analytics, Finance, Healthcare, Gaming, Shipping and Media. Our proactive thinking, led by the mission of Authority enables us to deliver Business Innovation & Acceleration to help you succeed.
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ACRU Effort to Purge Voters
The ACRU has targetted some counties, threatening to sue, and filed lawsuits in other counties.
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:: com :: sun :: star :: frame ::
|
| unpublished |
interface XUntitledNumbers |
|
|
|
- Usage Restrictions
- not published
- Description
- knows all currently used and all free numbers for using with untitled
but counted objects.
|
| Methods' Summary |
| leaseNumber |
calli has to lease a number befor he can use it within in its own title.
Such number must be freed after using e.g. while the object was closed or
get's another title (e.g. by saving a document to a real location on disc).
|
| releaseNumber |
has to be used to mark those number as "free for using".
If the reqistered component does not use such leased number any longer
it has to be released so it can be used for new components.
Note: calling this method with an unknown (but normaly valid number)
has to be ignored. No exceptions - no errors.
|
| releaseNumberForComponent |
does the same then releaseNumber () but it searches the corresponding
number for the specified component and deregister it.
|
| getUntitledPrefix |
returns the localized string value to be used for untitles objects in
combination with the leased number.
Note: Such string already contains leading spaces/tabs etcpp. !
The only thing which an outside code has todo then ... adding a leased number
to the string.
|
| Methods' Details |
leaseNumber
- Description
- calli has to lease a number befor he can use it within in its own title.
Such number must be freed after using e.g. while the object was closed or
get's another title (e.g. by saving a document to a real location on disc).
- Parameter xComponent
- the component which has to be registered for the leased number.
- Returns
- the new number for these object or 0 if no further numbers are available.
- Throws
- [IllegalArgumentException]
if an invalid object reference was provided to this method.
|
|
releaseNumber
- Description
- has to be used to mark those number as "free for using".
If the reqistered component does not use such leased number any longer
it has to be released so it can be used for new components.
Note: calling this method with an unknown (but normaly valid number)
has to be ignored. No exceptions - no errors.
- Parameter nNumber
- specify number for release.
- Throws
- [IllegalArgumentException]
if the given number is the special value 0.
|
|
releaseNumberForComponent
- Description
- does the same then releaseNumber () but it searches the corresponding
number for the specified component and deregister it.
- Parameter xComponent
- the component for deregistration.
- Throws
- [IllegalArgumentException]
if an invalid object reference was provided to this method.
|
|
getUntitledPrefix
| string |
| getUntitledPrefix(); |
- Description
- returns the localized string value to be used for untitles objects in
combination with the leased number.
Note: Such string already contains leading spaces/tabs etcpp. !
The only thing which an outside code has todo then ... adding a leased number
to the string.
- Returns
- the localized string for untitled components.
|
|
Top of Page
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


src/toggle.it.service.ts
constructor()
|
|
Defined in src/toggle.it.service.ts:7
|
| Private getFromLocalStorage |
getFromLocalStorage()
|
|
Defined in src/toggle.it.service.ts:12
|
|
Returns:
Feature[]
|
| Private saveInLocalStorage |
saveInLocalStorage(features: Feature[])
|
|
Defined in src/toggle.it.service.ts:16
|
|
Returns:
void
|
| Public setFeatureList |
setFeatureList(features: Feature[])
|
|
Defined in src/toggle.it.service.ts:21
|
|
Returns:
void
|
| Public ciao |
ciao(features: Feature[])
|
|
Defined in src/toggle.it.service.ts:30
|
|
Returns:
void
|
| Public getAll |
getAll()
|
|
Defined in src/toggle.it.service.ts:38
|
|
Returns:
Feature[]
|
| Public getFeature |
getFeature(key: string)
|
|
Defined in src/toggle.it.service.ts:46
|
|
Returns:
any
|
| Public toggleFeature |
toggleFeature(key: string, enabled: boolean)
|
|
Defined in src/toggle.it.service.ts:59
|
|
Returns:
any
|
| Public addFeature |
addFeature(feature: Feature)
|
|
Defined in src/toggle.it.service.ts:75
|
|
Returns:
any
|
| Public deleteFeature |
deleteFeature(feature: Feature)
|
|
Defined in src/toggle.it.service.ts:90
|
|
Returns:
any
|
import { Injectable, } from '@angular/core';
import { Feature } from './model/feature';
import { Props } from './const/props';
@Injectable()
export class ToggleItService {
constructor() { }
private getFromLocalStorage(): Feature[] {
return JSON.parse(localStorage.getItem(Props.STORAGE_KEY));
}
private saveInLocalStorage(features: Feature[]) {
localStorage.setItem(Props.STORAGE_KEY, JSON.stringify(features));
}
public setFeatureList(features: Feature[]) {
try {
this.saveInLocalStorage(features);
} catch (error) {
console.warn(error);
}
}
public ciao(features: Feature[]) {
try {
this.saveInLocalStorage(features);
} catch (error) {
console.warn(error);
}
}
public getAll(): Feature[] {
try {
return this.getFromLocalStorage();
} catch (error) {
console.warn(error);
}
}
public getFeature(key: string): any {
try {
for (let feature of this.getFromLocalStorage()) {
if (feature.key === key) {
return feature;
}
}
return new Error('No features found with name:' + key);
} catch (error) {
console.warn(error);
}
}
public toggleFeature(key: string, enabled: boolean): any {
try {
let features = this.getFromLocalStorage();
for (let feature of features) {
if (feature.key === key) {
feature.enabled = enabled;
this.saveInLocalStorage(features);
return;
}
}
return new Error('No features found with name:' + key);
} catch (error) {
console.warn(error);
}
}
public addFeature(feature: Feature): any {
try {
let features = this.getFromLocalStorage();
for (let f of features) {
if (f.key === feature.key) {
return new Error('Duplicated key: feature names must be unique');
}
}
features.push(feature);
this.saveInLocalStorage(features);
} catch (error) {
console.warn(error);
}
}
public deleteFeature(feature: Feature): any {
try {
let features = this.getFromLocalStorage();
for (let f of features) {
if (f.key === feature.key) {
let index: number = features.indexOf(f, 0);
if ( index > -1 ) {
features.splice(index, 1);
this.saveInLocalStorage(features);
return;
}
}
}
return new Error('No deletion performed as no features found with name:' + feature.key);
} catch (error) {
console.warn(error);
}
}
}


[
linked list
]
Leetcode 0024. Swap Nodes in Pairs
Problem statement
https://leetcode.com/problems/swap-nodes-in-pairs/
Solution
As with a lot of other linked lists, it is good idea to add dummy node before list to avoid cases. Imagine, we have list 1, 2, 3, 4, 5, 6
, let us add 0
node in the beginning, so we have 0 -> 1 -> 2 -> 3 -> 4 -> 5 -> 6
now.
Now, let us look at the main step of algorithm (for simplicity I will call nodes by its values)
pre = 0
, whe check ifpre.next
andpre.next.next
exists, they are, so definea = 1
andb = 2
.- Now, we need to rewrite links:
0 -> 2
,2 -> 1
and1 -> 3
. Note, that we do it all in one step. - Finally, we say, that
pre = 1
. Also, our list now looks like0 -> 2 -> 1 -> 3 -> 4 -> 5 -> 6
and as I saidpre = 1
now, so we swapped first two elements and now we on element number 2, which is exaclty what we have previously for smaller list. - On next step we have
0 -> 2 -> 1 -> 4 -> 3 -> 5 -> 6
and finally0 -> 2 -> 1 -> 4 -> 3 -> 6 -> 5
, this is exaclty what we need to return.
Complexity
Time complexity is O(n)
: we iterate over our list once, space complexity is O(1)
: we did not add any new space and reused already existing nodes.
class Solution:
def swapPairs(self, head):
dummy = ListNode(-1)
dummy.next = head
pre = dummy
while pre.next and pre.next.next:
a = pre.next
b = a.next
pre.next, b.next, a.next = b, a, b.next
pre = a
return dummy.next


PART XIX. SCHOOL HEALTH SERVICES PROGRAM--REPEALED
Cross References
For present provisions, see §§302A-851 to 855.
§§321-241 to 242 REPEALED. L 2007, c 105, §5.


All functions |
|
|---|---|
crul library adapter |
|
hash with counter, to store requests, and count each time it is used |
|
http lib adapter registry |
|
httr library adapter |
|
RequestPattern class |
|
Request registry |
|
General purpose request signature builder |
|
Response class |
|
Stub registry |
|
StubbedRequest class |
|
Build a crul request |
|
Build a crul response |
|
Build a httr request |
|
Build a httr response |
|
Enable or disable webmockr |
|
Turn on httr mocking |
|
Remove a request stub |
|
List requests in the request registry |
|
List stubs in the stub registry |
|
Clear the stub registry |
|
Stub an http request |
|
Set raise error condition |
|
Expectation for what's returned from a stubbed request |
|
Set timeout as an expected return on a match |
|
Defunct functions in webmockr |
|
Stubbing and setting expectations on HTTP requests |
|
|
|
webmockr configuration |
Set additional parts of a stubbed request |


- HTML
- URL
- HTTP
- Applications
People use browsers and search engines to make requests through the internet. These requests exist in a form of HTTP which is protocol the browser uses to make these requests. HTTP requests are accepted by the servers which are computers that hosts data and sends files back in reply to requests.
HTML or Hypertext Markup Language is the most common type of contents you can find on the web together with pictures, music, links and other documents. HTML is a coding language that creates websites. It consists of links, tags or markups and the language code itself.
Mark ups or tags are functions that give order to the your computer.
HTML is made up of elements. Each element consist of an
- opening tag,
- contents,
- closing tag.
< opening tag > data < / closing tag >
example:
This word is bold.
The tags gave order to my computer to show the word bold.
< b > contents < /b > - b stands for bold and make the word bold.
< em > contents < /em> - em stands for emphasized.
< i > contents < /i > - i stands for italic and make the contents slanted.
You can also include links in HTML contents and the way to do it is to include a:
- tag with an attribute and the particular value,
- a word, part of your text or your "link"
- and a closing tag.
< tag ATTR = "value" > contents < closing tag >
< a href = "URL" > your chosen word < /a >
< a > stands for anchor,this is the opening tag,
href is the name of the attribure,
< /a > is the closing tag
example:
This website is your best friend.
Other feature of HTML that you can include pictures in your webpage.
We use the image tag and the text which will carry the title of the image.
< img src = "URL" alt = "text" >
example:
is an amazing science subject.
Some tags does not have contents, these tags are called void tags. Image is one of these void tags.
Tags are also distinguished by their property of being a part of an inline or block element. Inline tags can
be placed into the text-line without breaking that while block elements creat an invisible block around the text breaking the structure.
These block elements can also be altered by other coding languages as CSS or JS.
Inline tags
< a > anchor,
< b > bold,
< br > break,
< em > emphasized,
< i > italic,
< img > image,
< span > Span makes it possible to alter the word's size, colour by other coding language.
Block tags
< p > paragraph,
< div > Similar to span but a block tag,
< form >
1. web page - documents written in HTML
2. How coding works
3. Computers are limited
4. Programmers cannot remember everything
5. Basic HTML vocabulary


Welcome {{currentUser.name}}
Locate an object using Google GeoCode Service
These are the caches that have not been found
- Name: {{cache.name}}
- Description: {{cache.description}}
- Location: {{cache.address}}
Address: {{location.formatted_address}}
Latitude: {{coordinates.lat}}
Longitude: {{coordinates.lng}}


AP Top Sports News at 1:54 a.m. EST
Gurley, Brown help Rams ground out 17-7 win over Bears
Edelman's TD pass leads Patriots over Eagles 17-10
Ravens harass Watson, beat Texans 41-7 for 6th straight win
Kyle Busch leads Gibbs trio to win 2nd NASCAR championship
Alabama star Tua Tagovailoa set for hip surgery in Houston
AP Top 25: Georgia edges past Alabama to No. 4; OU up to 8
Vikings overcome 20-0 deficit at half to beat Broncos 27-23
Brees throws for 228 yards, 3 TDs as Saints beat Bucs 34-17
49ers rally past Cardinals 36-26 on 4 TD passes by Garoppolo
AP source: NFL to hear Garrett's appeal early this week
Copyright 2019 The Associated Press. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.


Define a add group
Which can get angle between this to T (use rad as unit) Commonly, we use classOf[this] as T for symmetry
Which can get angle between this to T (use rad as unit) Commonly, we use classOf[this] as T for symmetry
Type of the object to compare
Distance between type T and this
Distance between type T and this
type of the object to compare
Distance between type T and this
Distance between type T and this
type of the object to compare
Object which can convert to GeoJSON, for more details, see: http://geojson.org/
For Chinese only 注意转换后坐标的逆转换在一些国家和地区是违法的 我愿意对自己的代码承担风险 但是该逆转方法也不能保证全局都能做到无误差，也不保证所有的逆向方法都有效 因为部分加密方法存在一定的信息损失，这些损失不一定能恢复 在生效区域全局都是单射单变量复函数的加密方法在本函数面前都是渣渣 如果坐标形式和经纬度差距太大可以采用线性回归变为近似线性以后再利用本方法
For Chinese only 注意转换后坐标的逆转换在一些国家和地区是违法的 我愿意对自己的代码承担风险 但是该逆转方法也不能保证全局都能做到无误差，也不保证所有的逆向方法都有效 因为部分加密方法存在一定的信息损失，这些损失不一定能恢复 在生效区域全局都是单射单变量复函数的加密方法在本函数面前都是渣渣 如果坐标形式和经纬度差距太大可以采用线性回归变为近似线性以后再利用本方法
1.0
2.3
element type
Which class can get an indexed hash the index code should be unique to avoid duplication in Set or other data structures
Which class can get an indexed hash the index code should be unique to avoid duplication in Set or other data structures
should have a great randomly hashCode, recommend use Long, Int, avoid using String or Double
to pack a value with some type you can make a collection with type _<:IValue[T] and getValue as T foreach
to pack a value with some type you can make a collection with type _<:IValue[T] and getValue as T foreach
value type
This vector is not same in Scala's scala.collection.immutable.Vector
it means a point in N-dimensional Euclid space
Which can get inner product to another object by given type T
Which can get inner product to another object by given type T
Type of the object to compare
Object which can get jaccard similarity and distance
Object which can get jaccard similarity and distance
Type to compare with
Commonly used in IVector3 V1×V2->V3 The common define is
Commonly used in IVector3 V1×V2->V3 The common define is
See Outer Product for more details
type to get TO
result type
Define a monoid which has product operation
Define a monoid which has product operation
Type of self extends this
Common utils of generating GeoJSON object
Define a add group
element type


This example shows how to use the gmf.themeselector directive from a c2c geoportal theme service.
gmf.themeselector