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Changelog:
2.4.9
April, 2014
Several improvements in OpenCL optimizations (ocl::sum, ocl::countNonZero, ocl::minMax, bitwise operationss, Haar face detector, etc)
Multiple fixes in Naitve Camera (NativeCameraView, cv::VideoCapture);
Improved CUDA support for all CUDA-enabled SoCs.
New VTK-based 3D visualization module viz stabilized and back-ported to 2.4 branch.
The module provides a very convenient way to display and position clouds, meshes, cameras and trajectories, and simple widgets (cube, line, circle, etc.).
Full demo video can be found at Itseez Youtube channel
Numerous bugfixes in code and docs from community
156 pull requests have been merged since 2.4.8
55 reported bugs have been closed since 2.4.8
2.4.8
December, 2013
User provided OpenCL context can be used by OpenCV ( ocl::initializeContext )
A separate OpenCL command queue is created for every CPU thread (allows concurrent kernels execution)
Some new OpenCL optimizations and bug-fixes
NVidia CUDA support on CUDA capable SoCs;
Android 4.4 support, including native camera;
Java wrappers for GPU-detection functions from core module were added;
New sample with CUDA on Android was added;
OpenCV Manager and apps hanging were fixed on Samsung devices with Android 4.3 (#3368, #3372, #3403, #3414, #3436).
Static linkage support for native C++ libraries;
139 pull requests have been merged since version:2.4.7!
32 reported bugs have been closed since version:2.4.7
2.4.7
November, 2013
Now 'ocl' module can be built without installing OpenCL SDK (Khronos headers in OpenCV tree);
Dynamic dependency on OpenCL runtime (allows run-time branching between OCL and non-OCL implementation);
Changing default OpenCL device via OPENCV_OPENCL_DEVICE environment variable (without app re-build);
Refactoring/extending/bug-fixing of existing OpenCL optimizations, updated documentation;
New OpenCL optimizations of SVM, MOG/MOG2, KalmanFilter and more;
New optimization for histograms, TV-L1 optical flow and resize;
Updated multi gpu sample for stereo matching;
Fixed BGR<->YUV color conversion and bitwize operations;
Fixed several build issues;
Android NDK-r9 (x86, x86_64) support;
Android 4.3 support: hardware detector (Bugs #3124, #3265, #3270) and native camera (Bug #3185);
MediaRecorder hint enabled for all Android devices with API level 14 and above;
Fixed JavaCameraView slowdown (Bugs #3033, #3238);
Fixed MS Certification test issues for all algorithmical modules and highgui, except OpenEXR and Media Foundation code for camera;
Implemented XAML-based sample for video processing using OpenCV;
Fixed issue in Media Foundation back-end for VideoCapture (#3189);
382 pull requests have been merged since 2.4.6!
54 reported bugs have been fixed since 2.4.6 (issue tracker query).
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Fix PR pkg/48777
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From Tobias Nygren in PR 48544.
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Changes in 2.4.6.1:
* Hotfix for camera pipeline for Linux (V4L).
Changes in 2.4.6:
* Windows RT: added video file i/o and sample application using camera,
enabled parallelization with TBB or MS Concurrency
* CUDA 5.5: added support for desktop and ARM
* Added Qt 5 support
* Binary compatiblility with both OpenCL 1.1/1.2 platforms. Now the binaries
compiled with any of AMD/Intel/Nvidia's SDK can run on all other platforms.
* New functions ported, CLAHE, GoodFeaturesToTrack, TVL1 optical flow and more
* Performance optimizations, HOG and more.
* More kernel binary cache options though setBinaryDiskCache interface.
* OpenCL binaries are now included into the superpack for Windows (for VS2010
and VS2012 only)
* Switched all the remaining parallel loops from TBB-only
'tbb::parallel_for()' to universal 'cv::parallel_for_()' with many possible
backends (MS Concurrency, Apple's GDC, OpenMP, Intel TBB etc.)
* iOS build scripts (together with Android ones) moved to 'opencv/platforms'
directory
* Fixed bug with incorrect saved video from camera through CvVideoCamera
* Added 'rotateVideo' flag to the CvVideoCamera class to control camera
preview rotation on device rotation
* Added functions to convert between UIImage and cv::Mat (just include
opencv2/highgui/ios.h)
* Numerous bug-fixes across all the library
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2.4.5
April, 2013
Experimental WinRT support (build for WindowsRT guide)
the new video super-resolution module has been added that
implements the following papers:
- S. Farsiu, D. Robinson, M. Elad, P. Milanfar. Fast and robust
Super-Resolution. Proc 2003 IEEE Int Conf on Image Process,
pp. 291â294, 2003.
- D. Mitzel, T. Pock, T. Schoenemann, D. Cremers. Video super
resolution using duality based TV-L1 optical flow. DAGM, 2009.
CLAHE (adaptive histogram equalization) algorithm has been
implemented, both CPU and GPU-accelerated versions (in imgproc
and gpu modules, respectively)
there are further improvements and extensions in ocl module:
- 2 stereo correspondence algorithms: stereobm (block matching)
and stereobp (belief propagation) have been added
- many bugs fixed, including some crashes on Intel HD4000
The tutorial on displaying cv::Mat inside Visual Studio 2012
debugger has been contributed by Wolf Kienzle from Microsoft
Research. See
http://opencv.org/image-debugger-plug-in-for-visual-studio.html
78 pull requests have been merged. Big thanks to everybody who
contributed!
At least 25 bugs have been fixed since 2.4.4 (see
http://code.opencv.org/projects/opencv/issues select closed
issues with target version set to "2.4.5").
2.4.4
March, 2013
This is the biggest news in 2.4.4 - we've got full-featured
OpenCV Java bindings on a desktop, not only Android! In fact
you can use any JVM language, including functional Java or
handy Groovy. Big thanks to Eric Christiansen for the contribution!
Check the tutorial for details and code samples.
Android application framework, samples, tutorials, OpenCV
Manager are updated, see Android Release Notes for details.
Numerous improvements in gpu module and the following new
functionality & optimizations:
Optimizations for the NVIDIA Kepler architecture
NVIDIA CARMA platform support
HoughLinesP for line segments detection
Lab/Luv <-> RGB conversions
Let us be more verbose here. The openCL-based hardware acceleration
(ocl) module is now mature, and, with numerous bug fixes, it
is largely bug-free. Correct operation has been verified on
all tested platforms, including discrete GPUs (tested on NVIDIA
and AMD boards), as well as integrated GPUs (AMD APUs as well
as Intel Ivy Bridge iGPUs). On the host side, there has been
exhaustive testing on 32/64 bit, Windows/Linux systems, making
the ocl module a very serious and robust cross-platform GPU
hardware acceleration solution. While we currently do not test
on other devices that implement OpenCL (e.g. FPGA, ARM or other
processors), it is expected that the ocl module will work well
on such devices as well (provided the minimum requirements
explained in the user guide are met).
Here are specific highlights of the 2.4.4 release:
The ocl::Mat can now use âspecialâ memory (e.g. pinned
memory, host-local or device-local).
The ocl module can detect if the underlying hardware supports
âintegrated memory,â and if so use âdevice-localâ memory
by default for all operations.
New arithmetic operations for ocl::Mat, providing significant
ease of use for simple numerical manipulations.
Interop with OpenCL enables very easy integration of OpenCV
in existing OpenCL applications, and vice versa.
New algorithms include Hough circles, more color conversions
(including YUV, YCrCb), and Hu Moments.
Numerous bug fixes, and optimizations, including in:
blendLinear, square samples, erode/dilate, Canny, convolution
fixes with AMD FFT library, mean shift filtering, Stereo
BM.
Platform specific bug fixes: PyrLK, bruteForceMatcher,
faceDetect now works also on Intel Ivy Bridge chips (as
well as on AMD APUs/GPUs and NVIDIA GPUs); erode/dilate
also works on NVIDIA GPUs (as well as AMD APUs/GPUs and
Intel iGPUs).
Many people contributed their code in the form of pull requests.
Here are some of the most interesting contributions, that were
included into 2.4 branch:
>100 reported problems have been resolved since 2.4.3
Oscar Deniz submitted smile detector and sample.
Alexander Smorkalov created a tutorial on cross-compilation
of OpenCV for Linux on ARM platforms.
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NetBSD 6, requested by tron.
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Recursively bump package revisions again after the "freetype2" and
"fontconfig" handling was fixed.
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to address issues with NetBSD-6(and earlier)'s fontconfig not being
new enough for pango.
While doing that, also bump freetype2 dependency to current pkgsrc
version.
Suggested by tron in PR 47882
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Changelog:
* Add universal parallell mechianism support
* Add sample codes
* Add some new algorithms
* Many improvements in GPU support
* Many bugfixes
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Suggested by SAITOH Masanobu <msaitoh@execsw.org> in PR 47051.
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requested by Thomas Klausner.
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(additionaly, reset PKGREVISION of qt4-* sub packages from base qt4 update)
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- New keypoint descriptor FREAK contributed by EPFL group
- Improved face recognizer class and tutorial added by Philipp Wagner
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installation on Mac OS X
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not tested. New ffmpeg support not enabled in package.
2.4.1
June, 2012
The changes since 2.4.0
The GPU module now supports CUDA 4.1 and CUDA 4.2 and can be
compiled with CUDA 5.0 preview.
Added API for storing OpenCV data structures to text string
and reading them back:
cv::calcOpticalFlowPyrLK now supports precomputed pyramids as
input.
Function signatures in documentation are made consistent with
source code.
Restored python wrappers for SURF and MSER.
45 more bugs in our bug tracker have been fixed
2.4.0
May, 2012
The major changes since 2.4 beta
OpenCV now provides pretty complete build information via
(surprise) cv::getBuildInformation().
reading/writing video via ffmpeg finally works and it's now
available on MacOSX too.
note 1: we now demand reasonably fresh versions of ffmpeg/libav
with libswscale included.
note 2: if possible, do not read or write more than 1 video
simultaneously (even within a single thread) with ffmpeg 0.7.x
or earlier versions, since they seem to use some global structures
that are destroyed by simultaneously executed codecs. Either
build and install a newer ffmpeg (0.10.x is recommended), or
serialize your video i/o, or use parallel processes instead of
threads.
MOG2 background subtraction by Zoran Zivkovic was optimized
using TBB.
The reference manual has been updated to match OpenCV 2.4.0
better (though, not perfectly).
>20 more bugs in our bug tracker have been closed
(http://code.opencv.org/projects/opencv/roadmap).
Asus Xtion is now properly supported for HighGUI. For now, you
have to manually specify this device by using
VideoCapture(CV_CAP_OPENNI_ASUS) instead of
VideoCapture(CV_CAP_OPENNI).
2.4 beta
April, 2012
As usual, we created 2.4 branch in our repository
(http://code.opencv.org/svn/opencv/branches/2.4), where we will
further stabilize the code. You can check this branch periodically,
before as well as after 2.4 release.
Common changes
At the age of 12, OpenCV got its own home! http://code.opencv.org
is now the primary site for OpenCV development and http://opencv.org
(to be launched soon) will be the official OpenCV user site.
Some of the old functionality from the modules imgproc, video,
calib3d, features2d, objdetect has been moved to legacy.
CMake scripts have been substantially modified. Now it's very
easy to add new modules - just put the directory with include,
src, doc and test sub-directories to the modules directory,
create a very simple CMakeLists.txt and your module will be
built as a part of OpenCV. Also, it's possible to exclude
certain modules from build (the CMake variables
"BUILD_opencv_<modulename>" control that).
New functionality
The new very base cv::Algorithm class has been introduced. It's
planned to be the base of all the "non-trivial" OpenCV
functionality. All Algorithm-based classes have the following
features:
"virtual constructor", i.e. an algorithm instance can be created by name;
there is a list of available algorithms;
one can retrieve and set algorithm parameters by name;
one can save algorithm parameters to XML/YAML file and then load them.
A new ffmpeg wrapper has been created that features multi-threaded
decoding, more robust video positioning etc. It's used with
ffmpeg starting with 0.7.x versions.
features2d API has been cleaned up. There are no more numerous
classes with duplicated functionality. The base classes
FeatureDetector and DescriptorExtractor are now derivatives of
cv::Algorithm. There is also the base Feature2D, using which
you can detect keypoints and compute the descriptors in a single
call. This is also more efficient.
SIFT and SURF have been moved to a separate module named nonfree
to indicate possible legal issues of using those algorithms in
user applications. Also, SIFT performance has been substantially
improved (by factor of 3-4x).
The current state-of-art textureless detection algorithm,
Line-Mod by S. Hinterstoisser, has been contributed by Patrick
Mihelich. See objdetect/objdetect.hpp, class Detector.
3 face recognition algorithms have been contributed by Philipp
Wagner. Please, check opencv/contrib/contrib.hpp, FaceRecognizer
class, and opencv/samples/cpp/facerec_demo.cpp.
2 algorithms for solving PnP problem have been added. Please,
check flags parameter in solvePnP and solvePnPRansac functions.
Enhanced LogPolar implementation (that uses Blind-Spot model)
has been contributed by Fabio Solari and Manuela Chessa, see
opencv/contrib/contrib.hpp, LogPolar_* classes and
opencv/samples/cpp/logpolar_bsm.cpp sample.
A stub module photo has been created to support a quickly
growing "computational photography" area. Currently, it only
contains inpainting algorithm, moved from imgproc, but it's
planned to add much more functionality.
Another module videostab (beta version) has been added that
solves a specific yet very important task of video stabiliion.
The module is under active development. Please, check
opencv/samples/cpp/videostab.cpp sample.
findContours can now find contours on a 32-bit integer image
of labels (not only on a black-and-white 8-bit image). This is
a step towards more convenhich results in better edge maps
Python bindings can now be used within python threads, so one
can write multi-threaded computer vision applications in Python.
OpenCV on GPU
Different Optical Flow algorithms have been added:
Brox (contrtions;
Improved performance.
pyrUp/pyrDown implementations.
Matrix multiplication on GPU (wrapper for the CUBLAS library).
This is optional, user need to compile OpenCV with CUBLAS
support.
OpenGL back-end has been implemented for highgui module, that
allows to display GpuMat directly without downloading them to
CPU.
Performance
A few OpenCV functions, like color conversion, morphology, data
type conversions, brute-force feature mer have been optimized
using TBB and/or SSE intrinisics.
Along with regression tests, now many OpenCV functions have
got performance tests. Now for most modules one can build
opencv_perf_<modulename> executables that run various functions
from the particular module and produce a XML file. Note that
if you want to run those tests, as well as the normal regression
tests, you will need to get (a rather big)
http://code.opencv.org/svn/opencv/trunk/opencv_extra directory
and set environment variable OPENCV_TEST_DATA_PATH to
"<your_copy_of_opencv_extra>/testdata".
Bug fixes
In this version we fixed literally hundreds of bugs. Please,
check http://code.opencv.org/projects/opencv/versions/1 for a
list of fixed bugs.
Known issues
When OpenCV is built statically, dynamically created classes
(via Algorithm::create) can fail because linker excludes the
"unused" object files. To avoid this problem, create classes
explicitly, e.g
1 Ptr<DescriptorExtractor> d = new BriefDescriptorExtractor;
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Add a python option (off by default).
2.3.1
(August, 2011)
New Functionality and Features
* Retina module has been contributed by Alexandre Benoit (in opencv_contrib
module).
* Planar subdivisions construction (Delaunay triangulation and Voronoi
tesselation) have been ported to C++. See the new delaunay2.cpp sample.
* Several new Python samples have been added.
* FLANN in OpenCV has been upgraded to v1.6. Also, added Python bindings
for FLANN.
* We now support the latest FFMPEG (0.8.x) that features multi-threaded
decoding. Reading videos in OpenCV has never been that fast.
* Over 100 issues have been resolved since 2.3 release.
2.3
(July, 2011)
Modifications and Improvements since 2.3rc
* A few more bugs reported in the OpenCV bug tracker have been fixed.
* Documentation has been improved a lot!
2.3rc
(June, 2011)
New Functionality, Features
* Many functions and methods now take InputArray/OutputArray instead of
"cv::Mat" references. It retains compatibility with the existing code and
yet brings more natural support for STL vectors and potentially other
"foreign" data structures to OpenCV.
core:
* LAPACK is not used by OpenCV anymore.
* Arithmetic operations now support mixed-type operands and arbitrary number
of channels.
features2d:
* Completely new patent-free BRIEF and ORB feature descriptors have been
added.
* Very fast LSH matcher for BRIEF and ORB descriptors will be added in 2.3.1.
calib3d:
* calibration.cpp sample. With the new pattern calibration accuracy is
usually much higher.
stitching:
* opencv_stitching is a beta version of new application that makes a panorama
out of a set of photos taken from the same point.
python:
* Now there are 2 extension modules: cv and cv2. cv2 includes wrappers for
OpenCV 2.x functionality. opencv/samples/python2 contain a few samples
demonstrating cv2 in use.
* Over 250 issues have been resolved.
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a) tiff update to 4.0 (shlib major change)
b) glib2 update 2.30.2 (adds libffi dependency to buildlink3.mk)
Enjoy.
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