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locks; strict; comment @# @; 1.62 date 2024.03.11.09.37.20; author jperkin; state Exp; branches; next 1.61; commitid zrvdHxPwMOTzYI1F; 1.61 date 2024.02.09.11.50.30; author adam; state Exp; branches; next 1.60; commitid UNSOGYeslFI3IKXE; 1.60 date 2024.01.16.19.23.05; author adam; state Exp; branches; next 1.59; commitid wwhWJYlVlfzLYHUE; 1.59 date 2023.12.22.15.35.44; author thor; state Exp; branches; next 1.58; commitid OBpChQ4DcfDtwtRE; 1.58 date 2023.12.22.07.35.07; author thor; state Exp; branches; next 1.57; commitid RcajIgvK2sg8QqRE; 1.57 date 2021.10.26.10.46.34; author nia; state Exp; branches; next 1.56; commitid 6mU28GyqPd3PdjeD; 1.56 date 2021.10.21.16.25.07; author jperkin; state Exp; branches; next 1.55; commitid 0OlnaJyxOrLggHdD; 1.55 date 2021.10.16.07.16.29; author adam; state Exp; branches; next 1.54; commitid mFN4TbMeo1b3o0dD; 1.54 date 2021.10.10.07.02.01; author adam; state Exp; branches; next 1.53; commitid nNDv1SwKsDS1vecD; 1.53 date 2021.10.07.14.12.36; author nia; 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fix testing @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.60 2024/01/16 19:23:05 adam Exp $ d28 1 @ 1.60 log @opencv opencv-contrib-face: updated to 3.4.20 3.4.20 Bug fixes @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.59 2023/12/22 15:35:44 thor Exp $ d11 1 a11 1 SHA1 (patch-cmake_OpenCVDetectPython.cmake) = 4f3bfe574edf083ebc7e78d347355c58461b2c6b @ 1.59 log @graphics/opencv: avoid name-clash of complex macro for gcc<4.8 This adds #undef complex explicitly, to fix the build for older gccs that don't have that in their headers for C++ code. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.58 2023/12/22 07:35:07 thor Exp $ d3 3 a5 3 BLAKE2s (opencv-3.4.17.tar.gz) = f8cbf244836026ef700534a4aa35a96f0e1521a6a5aa05ffecb90b1cdbcb75d3 SHA512 (opencv-3.4.17.tar.gz) = b17a4a04ab29f0f966681a825af782039a2cc6564956894aba639731542fdb86d316b16b96e2d45de8b5e0db7c79ce4b4c348b82ccd124d125aacb7c02026841 Size (opencv-3.4.17.tar.gz) = 87758183 bytes d13 1 d24 1 a24 1 SHA1 (patch-modules_dnn_test__precomp.hpp) = 9bf15d32394f36b92e5fc5d57fd576b3860233ae d28 1 @ 1.58 log @opencv: version 3.4.17 with proper explicit BLAS (CBLAS + LAPACKE) usage This does the small bugfix update from 3.4.16 to 3.4.17 and adds proper usage of BLAS stuff. There was linkage to BLAS before via numpy, but the internal explicit BLAS-using code was not built, as the CMake machinery did not find it. This commit drops an actually counterproductive patch and adds pkg-config calls to find the BLAS-related libraries. Note that vor opencv-contrib-face, the BLAS choice during its build doesn't really enter the result, apparently, but the build process does use it and it would not help to confuse matters there. I am not sure if the buildlink3.mk should also add blas.buildlink3.mk now. It does not feature numpy right now. Should it? Next step should be move towards 4.x at least. Upstream: December, 2021 OpenCV 3.4.17 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.5.5. Long-lived OpenCV 3.x release series is here since 2015. We are going to reduce support of 3.x branch in the future to move forward to OpenCV 5.0. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.57 2021/10/26 10:46:34 nia Exp $ d12 1 a12 1 SHA1 (patch-cmake_OpenCVFindLAPACK.cmake) = e8c474d91ba6de7c3204fcd753a33d33847b18b8 @ 1.57 log @graphics: Replace RMD160 checksums with BLAKE2s checksums All checksums have been double-checked against existing RMD160 and SHA512 hashes @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.56 2021/10/21 16:25:07 jperkin Exp $ d3 3 a5 3 BLAKE2s (opencv-3.4.16.tar.gz) = 153eb897082e2f0b98bd5bee22fdff8a7c5d3f0cb2276f90ae2232286e34ebde SHA512 (opencv-3.4.16.tar.gz) = 2fa9243625309a1c12c916737c94f0e2f9566f0828469b148cc1683dd1b8db8d1d58f90a36cfcaa72052964a718929451f04cda5361d8b546a63da69217d040a Size (opencv-3.4.16.tar.gz) = 87694121 bytes d8 1 a8 1 SHA1 (patch-CMakeLists.txt) = 029368ab14163640d1651f572810eb8eb0c043d9 d12 1 a12 2 SHA1 (patch-cmake_OpenCVFindOpenEXR.cmake) = 202d0fdc84464d563dead955d5299b42098d52a6 SHA1 (patch-cmake_checks_lapack__check.cpp) = dd25d34fff25e0d46651789cf5577391d7b48c81 a17 1 SHA1 (patch-modules_core_src_hal__internal.cpp) = 22beba5ee93fc468999479227d7ef07397848b22 @ 1.56 log @opencv: Explicitly use std::ceil. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.55 2021/10/16 07:16:29 adam Exp $ d3 1 a3 1 RMD160 (opencv-3.4.16.tar.gz) = c8c3c68a05b01d58505ca84e328996bbe17706b2 @ 1.55 log @opencv: one more guard for V4L2_PIX_FMT_Y16 @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.54 2021/10/10 07:02:01 adam Exp $ d22 1 @ 1.54 log @opencv opencv-contrib-face: updated to 3.4.16 OpenCV 3.4.16 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.5.4. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.53 2021/10/07 14:12:36 nia Exp $ d29 1 a29 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = 847c9cf47c3fb71a2e05281544a03a5ed0d224a5 @ 1.53 log @graphics: Remove SHA1 hashes for distfiles @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.52 2021/10/06 21:10:24 adam Exp $ d3 3 a5 3 RMD160 (opencv-3.4.15.tar.gz) = e7f75f9f9f6102ab7b88d04be4e00a0148eb623c SHA512 (opencv-3.4.15.tar.gz) = 775149e56f0aa94d53eb024404866380d97ce423ef1c8343ee8f12c1377e454ae182b2528e86949b5f7250e551d464bd1a5de2e2d9f0d0e1dd3dc188a1db790d Size (opencv-3.4.15.tar.gz) = 87661484 bytes a19 1 SHA1 (patch-modules_core_src_parallel.cpp) = 9974e53f3be96782025dae3c64d9f1535d9bf0fd a21 1 SHA1 (patch-modules_dnn_src_caffe_caffe__io.cpp) = 705963fb3227174c414874a8dd28a9f1219be070 @ 1.52 log @opencv opencv-contrib-face: updated to 3.4.15 OpenCV 3.4.15 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.5.3. Long-lived OpenCV 3.x release series is here since 2015. We are going to reduce support of 3.x branch in the future to move forward to OpenCV 5.0. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.51 2021/09/22 13:40:41 nia Exp $ a2 1 SHA1 (opencv-3.4.15.tar.gz) = 2baab7f24f48f2dd2f4c72d47195da00f2ad317a @ 1.51 log @opencv: Fix netbsd-8 build failure. Still does not link, due to libstdc++ @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.50 2021/07/08 21:27:39 markd Exp $ d3 4 a6 4 SHA1 (opencv-3.4.9.tar.gz) = bcd0fafc9f1a240d92af9007c9f8098da601d7a5 RMD160 (opencv-3.4.9.tar.gz) = 2ab36f669a70c876e739736e6b9daacabc5933fe SHA512 (opencv-3.4.9.tar.gz) = f445970ca39794fc5fbcaed8b506c6b332cbce911ed8487f490bca9a565c8ed3071816261a1803a8f4b43f58d66ca5eaab30be478c4b7ee973a6b6fc2b370869 Size (opencv-3.4.9.tar.gz) = 87342965 bytes d15 1 a15 1 SHA1 (patch-modules_core_include_opencv2_core_bindings__utils.hpp) = 9018a6124fb840be5213450b1bbe353078b37029 d21 1 d24 1 d32 1 a32 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = 275e72e3c146cf15845fbb7272b28e21f51d6fb4 @ 1.50 log @opencv: build with openexr3 @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.49 2020/09/09 11:50:50 nia Exp $ d14 1 d20 1 @ 1.49 log @opencv: Include arm_neon.h before NEON'ing @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.48 2020/08/24 07:08:03 tnn Exp $ d13 1 d25 1 @ 1.48 log @opencv: avoid non-standard integer types in v4l module @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.47 2020/08/08 22:40:59 joerg Exp $ d18 1 @ 1.47 log @Fix build on Illumos. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.46 2020/04/18 22:01:33 joerg Exp $ d25 1 a25 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = 8e935a6d8128aaf536a9a431dc8b8a7ea58ae43d @ 1.46 log @Fix missing includes. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.45 2020/02/13 09:23:46 adam Exp $ d23 1 @ 1.45 log @opencv: updated to 3.4.9 version:3.4.9 OpenCV 3.4.9 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.2.0. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.44 2019/12/29 10:00:08 markd Exp $ d10 1 d13 2 d16 1 d19 2 @ 1.44 log @opencv: switch to ffmpeg4. Don't pick up stray packages. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.43 2019/12/16 08:24:39 adam Exp $ d3 4 a6 4 SHA1 (opencv-3.4.8.tar.gz) = ae032936ddbfecca7fbe6cd307d942604f26d403 RMD160 (opencv-3.4.8.tar.gz) = 40652271f410d9d48904a7df428465296f71d874 SHA512 (opencv-3.4.8.tar.gz) = 6c2dfa88e9a93747397f80e6a3dd7eed126bc14efe6c0ec5b064d10bc49f24fc6fb187029f3ac6f5d9f5c16465b96ba55e5d5cacc3584dce69e10567df423ccb Size (opencv-3.4.8.tar.gz) = 87343996 bytes d10 1 a10 1 SHA1 (patch-cmake_OpenCVDetectCXXCompiler.cmake) = 221b0551d0f29d7e79afe3da8a33b1b3a4f7bf20 @ 1.43 log @opencv: updated to 3.4.8 version:3.4.8 OpenCV 3.4.8 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.1.2. version:3.4.7 OpenCV 3.4.7 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.1.1. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.42 2019/04/29 06:59:17 wiz Exp $ d9 1 a9 1 SHA1 (patch-CMakeLists.txt) = 43fac541d6445186e335cb74c95d9e1c05749edd @ 1.42 log @opencv: add new patch to distinfo @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.41 2019/04/24 19:34:44 adam Exp $ d3 4 a6 4 SHA1 (opencv-3.4.6.tar.gz) = c445fe9f0a07a95837d2f39c0637da71158129c5 RMD160 (opencv-3.4.6.tar.gz) = 9fba797c535a7c4366cbf8018ee61ccd396b6c51 SHA512 (opencv-3.4.6.tar.gz) = 86870788cbe36062b8fdb359d516714df887b0bb894d82bc65d33f7c5e8435371908cf21cee57137a60334187c74f4dabd358a20e9f13bbb36308acec51260cc Size (opencv-3.4.6.tar.gz) = 88174475 bytes d9 1 a9 1 SHA1 (patch-CMakeLists.txt) = d7b434783aca4d0999c6d888eb8e160142a3aa1b d11 1 a16 1 SHA1 (patch-modules_highgui_src_window__cocoa.mm) = 03a35cdbb32f40f7a234c406ddf0e4991873ae37 d18 1 a18 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = 20e572d04a15b08180ad7d6671ab3d124b73b748 @ 1.41 log @opencv: updated to 3.4.6 version:3.4.6 OpenCV 3.4.6 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.1.0. version:3.4.5 OpenCV 3.4.5 has been released. Bug fixes, optimizations and other enhancements are propagated into OpenCV 4.0.1. version:3.4.4 OpenCV 3.4.4 has been released. This is a mantenance release. New features are landed in OpenCV 4.0. version:3.4.3 OpenCV 3.4.3 has been released, with further extended dnn module, documentation improvements, some other new functionality and bug fixes. version:3.4.2 OpenCV 3.4.2 has been released, with further extended dnn module, documentation improvements, some other new functionality and bug fixes. OpenCV 3.4.x development is switched from "master" to "3.4" branch. "master" branch is used for development of upcoming OpenCV 4.x releases. Bugfixes / optimizations / small improvemets should go into "3.4" branch. We will merge changes from "3.4" into "master" regularly (weekly/bi-weekly). @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.40 2018/09/26 19:33:50 prlw1 Exp $ d14 1 @ 1.40 log @Fix opencv build with PYTHON_VERSION_DEFAULT=37 @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.39 2018/03/02 16:24:21 fhajny Exp $ d3 4 a6 4 SHA1 (opencv-3.4.1.zip) = 1e2a04746eaeee520e58f81002c556c435ef0dce RMD160 (opencv-3.4.1.zip) = d9f6de36b3d43e0ec5ce7dcfe752a7529f1c4daa SHA512 (opencv-3.4.1.zip) = 23610b7f909963ed3d7df233932e8ca0ef0604683affcbdec099b9b991bd4c0af275ec808c874ea29a5e8fbd5f02ad284aa0749c99748e01a73845aa25ebc3b9 Size (opencv-3.4.1.zip) = 90982898 bytes d9 1 d15 1 a15 1 SHA1 (patch-modules_python_src2_cv2.cpp) = f9280bfe8e5b7154ce1ef75bf9da8020a5c7c666 d17 1 a17 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = 985d91d9a4c63f081c3fff495cc86d8d0a1c6aa4 @ 1.39 log @graphics/opencv: Update to 3.4.1. == OpenCV 3.4.1 dnn - Added support for quantized TensorFlow networks - OpenCV is now able to use Intel DL inference engine as DNN acceleration backend - Added AVX-512 acceleration to the performance-critical kernels, such as convolution and fully-connected layers - SSD-based models trained and retrained in TensorFlow Object Detection API can be easier imported by a single invocation of python script making a text graph representation - Performance of pthreads backend of cv::parallel_for_() has been greatly improved on many core machines - OpenCL backend has been expanded to cover more layers - Several bugs in various layers have been fixed OpenCL - On-disk caching of precompiled OpenCL kernels has been fixed to comply with OpenCL standard - Certain cases with UMat deadlock when copying UMats in different threads has been fixed Android - Supported Android NDK16 - Added build.gradle into OpenCV 4 Android SDK - Added initial support of Camera2 API via JavaCamera2View interface C++ - C++11: added support of multi-dimentional cv::Mat creation via C++ initializers lists - C++17: OpenCV source code and tests comply C++17 standard Misc - opencv_contrib: added GMS matching - opencv_contrib: added CSR-DCF tracker - opencv_contrib: several improvements in OVIS module == OpenCV 3.4 - New background subtraction algorithms have been integrated. dnn - Added faster R-CNN support - Javascript bindings have been extended to cover DNN module - DNN has been further accelerated for iGPU using OpenCL OpenCL - On-disk caching of precompiled OpenCL kernels has been finally implemented - It's now possible to load and run pre-compiled OpenCL kernels via T-API - Bit-exact 8-bit and 16-bit resize has been implemented @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.38 2017/09/04 15:23:49 fhajny Exp $ d14 1 @ 1.38 log @Update graphics/opencv to 3.3.0. Sync opencv-contrib-face too. Main changes: - DNN module from opencv_contrib was promoted to the main repository, improved and accelerated it a lot. An external BLAS implementation is not needed anymore. For GPU there is experimental DNN acceleration using Halide (http://halide-lang.org). - OpenCV can now be built as C++ 11 library using the flag ENABLE_CXX11. Some cool features for C++ 11 programmers have been added. - We've also enabled quite a few AVX/AVX2 and SSE4.x optimizations in the default build of OpenCV thanks to the feature called 'dynamic dispatching'. The DNN module also has some AVX/AVX2 optimizations. - Intel Media SDK can now be utilized by our videoio module to do hardware-accelerated video encoding/decoding. MPEG1/2, as well as H.264 are supported. - Embedded into OpenCV Intel IPP subset has been upgraded from 2015.12 to 2017.2 version, resulting in ~15% speed improvement in our core & imgproc perf tests. Full release notes: https://github.com/opencv/opencv/wiki/ChangeLog @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.37 2017/03/16 21:59:13 prlw1 Exp $ d3 4 a6 4 SHA1 (opencv-3.3.0.zip) = 7ca35eceb3caa2d96b846b682dbcdf1e6fa66904 RMD160 (opencv-3.3.0.zip) = d2cbf32ff7f62c8064e0ba774baa56fa1b168206 SHA512 (opencv-3.3.0.zip) = 14430c6225926e5118daccb57c7276d9f9160c90a034b2c73a09b73ac90ba7ebd3ae78cccffb4a10b58bb0e5e16ebd03bf617030fa74cc67d9d18366bf6b4951 Size (opencv-3.3.0.zip) = 84873317 bytes a11 1 SHA1 (patch-modules_core_src_parallel__pthreads.cpp) = d8070117286b36a23a6788fc834aacc52d5919d7 d15 1 a15 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = 96aac9380d94818a52afd51f2d4b3f774debd080 @ 1.37 log @Update opencv to 3.2 Many Darwin library handling patches removed because of commit 912592de4ce Remove "INSTALL_NAME_DIR lib" target property Full changelog at https://github.com/opencv/opencv/wiki/ChangeLog Highlights: * Results from 11 GSoC 2016 projects have been submitted to the library, 9 of them have been integrated already, 2 still pending (the numbers below are the id's of the Pull Requests in opencv or opencv_contrib repository): + Ambroise Moreau (Delia Passalacqua) - sinusoidal patterns for structured light and phase unwrapping module (711) + Alexander Bokov (Maksim Shabunin) - DIS optical flow (excellent dense optical flow algorithm that is both significantly better and significantly faster than Farneback's algorithm - our baseline), and learning-based color constancy algorithms implementation (689, 708, 722, 736, 745, 747) + Tyan Vladimir (Antonella Cascitelli) - CNN based tracking algorithm (GOTURN) (718, 899) + Vladislav Samsonov (Ethan Rublee) - PCAFlow and Global Patch Collider algorithms implementation (710, 752) + Jo o Cartucho (Vincent Rabaud) - Multi-language OpenCV Tutorials in Python, C++ and Java (7041) + Jiri Horner (Bo Li) - New camera model and parallel processing for stitching pipeline (6933) + Vitaliy Lyudvichenko (Anatoly Baksheev) - Optimizations and improvements of dnn module (707, 750) + Iric Wu (Vadim Pisarevsky) - Base64 and JSON support for file storage (6697, 6949, 7088). Use names like `"myfilestorage.xml?base64"` when writing file storage to store big chunks of numerical data in base64-encoded form. + Edgar Riba (Manuele Tamburrano, Stefano Fabri) - tiny_dnn improvements and integration (720: pending) + Yida Wang (Manuele Tamburrano, Stefano Fabri) - Quantization and semantic saliency detection with tiny_dnn + Anguelos Nicolaou (Lluis Gomez) - Word-spotting CNN based algorithm (761: pending) @ text @d1 1 a1 1 $NetBSD$ d3 6 a8 5 SHA1 (opencv-3.2.0.zip) = 7a7d2eb8cf617f58d610d856e531f3d92b89bc42 RMD160 (opencv-3.2.0.zip) = 09da1443a5ef3de036b11bf0d1f384da36d459d9 SHA512 (opencv-3.2.0.zip) = c6418d2a7654fe9d50611e756778df4c6736f2de76b85773efbf490bb475dd95ec1041fe57a87163ce11a7db44430cd378c8416af3319f979ced92532bf5ebb5 Size (opencv-3.2.0.zip) = 82033498 bytes SHA1 (patch-3rdparty_ippicv_downloader.cmake) = a0b7c1b52f9ec4f35ff3f846785fbbfec1eeac51 d12 1 a12 1 SHA1 (patch-modules_core_src_parallel__pthreads.cpp) = c64ef8872c120db0ab92582496235858eec9bf92 d16 1 a16 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = 96f33b2b209776ff8f38127c611d49413b308123 @ 1.36 log @gcc6 build fix @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.35 2016/03/01 20:14:24 joerg Exp $ d3 4 a6 4 SHA1 (opencv-3.1.0.zip) = 8c932b68fe2e1575e88dde759ab1ed1d53d6f41b RMD160 (opencv-3.1.0.zip) = d7a811c67cfb16243470822150760252d5770165 SHA512 (opencv-3.1.0.zip) = b4915e8838fce8ba9e1af8b11e46678624435e9a41592e645413dfdc830993eaa017d337fe4c212a49f096421a6317a1892546087fbc3cfdab554522336c0f1a Size (opencv-3.1.0.zip) = 79186131 bytes a7 3 SHA1 (patch-apps_annotation_CMakeLists.txt) = 4c3a00b0dfef5e978b10ba966f68d050a06208fe SHA1 (patch-apps_createsamples_CMakeLists.txt) = 2d60ecc0e1674cde4414e91e837c24fa464d42aa SHA1 (patch-apps_traincascade_CMakeLists.txt) = 7114cc4c2057e12dc8e47bc61334cb8e175987eb a8 2 SHA1 (patch-cmake_OpenCVModule.cmake) = 7667f19f3e9c6ff757d92a6a49e7c3430c6c080d SHA1 (patch-cmake_OpenCVPCHSupport.cmake) = 237fa2d000c402c55dfdbec3e27c89cffdfde8b1 a13 2 SHA1 (patch-modules_java_CMakeLists.txt) = 020a8d2048d927e5d3819867df0d889bb516d8b4 SHA1 (patch-modules_objdetect_include_opencv_objdetect_detection__based__tracker.hpp) = 83575857156321ae07f3fb03d1b3c61b804b3832 d15 1 a15 1 SHA1 (patch-modules_videoio_src_cap__v4l.cpp) = f8f786f97a9b8c047180b79e399b83f71735f91e @ 1.35 log @NetBSD's v4l2 emulation doesn't currently have focus-related settings, so conditionalize parts. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.34 2016/02/21 14:10:46 fhajny Exp $ d13 1 @ 1.34 log @Update graphics/opencv to 3.1.0. * A lot of new functionality has been introduced during GSoC 2015: - "Omnidirectional Cameras Calibration and Stereo 3D Reconstruction" opencv_contrib/ccalib module - "Structure From Motion" - opencv_contrib/sfm module - "Improved Deformable Part-based Models" - opencv_contrib/dpm module - "Real-time Multi-object Tracking using Kernelized Correlation Filter" - opencv_contrib/tracking module - "Improved and expanded Scene Text Detection" - opencv_contrib/text module - "Stereo correspondence improvements" - opencv_contrib/stereo module - "Structured-Light System Calibration" - opencv_contrib/structured_light - "Chessboard+ArUco for camera calibration" - opencv_contrib/aruco - "Implementation of universal interface for deep neural network frameworks" - opencv_contrib/dnn module - "Recent advances in edge-aware filtering, improved SGBM stereo algorithm" - opencv/calib3d and opencv_contrib/ximgproc - "Improved ICF detector, waldboost implementation" - opencv_contrib/xobjdetect - "Multi-target TLD tracking" - opencv_contrib/tracking module - "3D pose estimation using CNNs" - opencv_contrib/cnn_3dobj * Many great contributions made by the community, such as: - Support for HDF5 format - New/Improved optical flow algorithms - Multiple new image processing algorithms for filtering, segmentation and feature detection - Superpixel segmentation * IPPICV is now based on IPP 9.0.1, which should make OpenCV even faster on modern Intel chips * opencv_contrib modules can now be included into the opencv2.framework for iOS * Newest operating systems are supported: Windows 10 and OSX 10.11 (Visual Studio 2015 and XCode 7.1.1) * Interoperability between T-API and OpenCL, OpenGL, DirectX and Video Acceleration API on Linux, as well as Android 5 camera. * HAL (Hardware Acceleration Layer) module functionality has been moved into corresponding basic modules; the HAL replacement mechanism has been implemented along with the examples See full changelog: https://github.com/Itseez/opencv/wiki/ChangeLog @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.33 2016/02/08 02:04:18 dbj Exp $ d21 1 @ 1.33 log @fix broken dynamic library handling on Darwin @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.32 2015/11/03 21:34:11 agc Exp $ d3 5 a7 5 SHA1 (opencv-3.0.0.zip) = 7b7cd6cb3b7bad537cacad04bb7aa264a897d545 RMD160 (opencv-3.0.0.zip) = 7b4dff26502e71e6570c2452c35fd03a1982bc7e SHA512 (opencv-3.0.0.zip) = 108d0fdcc60b5688ebf61c930fb965ec81f0d3c36bb1797f6cc571fac35331f540773207fd1cb81b12c05c8f4d1af20c4a2452d9f75cd0cae4acd8131be92375 Size (opencv-3.0.0.zip) = 100980799 bytes SHA1 (patch-3rdparty_ippicv_downloader.cmake) = 8d99b26a39aa184a4dfc03e4928ea7b7b62e71d9 d12 1 a12 1 SHA1 (patch-cmake_OpenCVModule.cmake) = 440788935a55ae1056407243b730fc13328e12f5 d15 1 a15 1 SHA1 (patch-modules_core_src_parallel__pthreads.cpp) = dba43f8252eda7807379469cf9359581bf4d41ad d19 1 a19 2 SHA1 (patch-modules_objdetect_include_opencv_objdetect_detection__based__tracker.hpp) = 2f4d2f43afe370eef748e05bec199bc963e1ecab SHA1 (patch-modules_python_common.cmake) = 23d5c21ad4b2e09f1223f02c45bd51e373d1b520 @ 1.32 log @Add SHA512 digests for distfiles for graphics category Problems found with existing digests: Package fotoxx distfile fotoxx-14.03.1.tar.gz ac2033f87de2c23941261f7c50160cddf872c110 [recorded] 118e98a8cc0414676b3c4d37b8df407c28a1407c [calculated] Package ploticus-examples distfile ploticus-2.00/plnode200.tar.gz 34274a03d0c41fae5690633663e3d4114b9d7a6d [recorded] da39a3ee5e6b4b0d3255bfef95601890afd80709 [calculated] Problems found locating distfiles: Package AfterShotPro: missing distfile AfterShotPro-1.1.0.30/AfterShotPro_i386.deb Package pgraf: missing distfile pgraf-20010131.tar.gz Package qvplay: missing distfile qvplay-0.95.tar.gz Otherwise, existing SHA1 digests verified and found to be the same on the machine holding the existing distfiles (morden). All existing SHA1 digests retained for now as an audit trail. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.31 2015/10/13 14:37:42 joerg Exp $ d8 3 d12 1 d18 1 d20 1 a20 1 SHA1 (patch-modules_python_common.cmake) = d6289a316712bb8be4d590965c87f6bb3525a938 @ 1.31 log @Don't fetch 3rd party modules during build from the Internet. Don't require C++14 for no obvious reason. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.30 2015/10/08 17:45:59 fhajny Exp $ d5 1 @ 1.30 log @Update graphics/opencv to 3.0.0. Major changes (besides bugfixes): - opencv_contrib (http://github.com/itseez/opencv_contrib) repository has been added. - a subset of Intel IPP (IPPCV) is given to us and our users free of charge, free of licensing fees, for commercial and non-commerical use. - T-API (transparent API) has been introduced, this is transparent GPU acceleration layer using OpenCL. It does not add any compile-time or runtime dependency of OpenCL. When OpenCL is available, it's detected and used, but it can be disabled at compile time or at runtime. - ~40 OpenCV functions have been accelerated using NEON intrinsics and because these are mostly basic functions, some higher-level functions got accelerated as well. - There is also new OpenCV HAL layer that will simplifies creation of NEON-optimized code and that should form a base for the open-source and proprietary OpenCV accelerators. - The documentation is now in Doxygen: http://docs.opencv.org/master/ - We cleaned up API of many high-level algorithms from features2d, calib3d, objdetect etc. They now follow the uniform "abstract interface - hidden implementation" pattern and make extensive use of smart pointers (Ptr<>). - Greatly improved and extended Python & Java bindings (also, see below on the Python bindings), newly introduced Matlab bindings - Improved Android support - now OpenCV Manager is in Java and supports both 2.4 and 3.0. - Greatly improved WinRT support, including video capturing and multi-threading capabilities. Thanks for Microsoft team for this! - Big thanks to Google who funded several successive GSoC programs and let OpenCV in. The results of many successful GSoC 2013 and 2014 projects have been integrated in opencv 3.0 and opencv_contrib (earlier results are also available in OpenCV 2.4.x). We can name: - text detection - many computational photography algorithms (HDR, inpainting, edge-aware filters, superpixels,...) - tracking and optical flow algorithms - new features, including line descriptors, KAZE/AKAZE - general use optimization (hill climbing, linear programming) - greatly improved Python support, including Python 3.0 support, many new tutorials & samples on how to use OpenCV with Python. - 2d shape matching module and 3d surface matching module - RGB-D module - VTK-based 3D visualization module For full changelog see: http://code.opencv.org/projects/opencv/wiki/ChangeLog For 2.4 to 3.0 transition, see the transition guide: http://docs.opencv.org/master/db/dfa/tutorial_transition_guide.html @ text @d1 1 a1 1 $NetBSD$ d6 1 d13 1 @ 1.29 log @graphics/opencv: fix build on fbsd + clang * under clang, C-style cast from nullptr_t to enum are not allowed. Ok@@ wiz @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.28 2015/02/26 17:52:12 tnn Exp $ d3 7 a9 7 SHA1 (opencv-2.4.9.zip) = 4f5166e2bd22bd6167cb56dd04f2c6ed68148b2c RMD160 (opencv-2.4.9.zip) = 1b0b80ecb50270fa7e4b1dea6f075982b5d15d81 Size (opencv-2.4.9.zip) = 91684751 bytes SHA1 (patch-cmake_OpenCVFindLibsVideo.cmake) = ffe4d102dc9e0bd467dccd8fab02f3cc2d7d7fa3 SHA1 (patch-modules_contrib_src_inputoutput.cpp) = dc3413182c94b670823d509ab38f21ce36d4f432 SHA1 (patch-modules_contrib_src_spinimages.cpp) = b3e465700059616be991d597230bc8dc42f15be1 SHA1 (patch-modules_core_include_opencv2_core_types_c.h) = c056068c01c417dc262f21c00324da7f86c0cd8e d12 2 a13 4 SHA1 (patch-modules_legacy_src_calibfilter.cpp) = a388e646cd0b09af1b9ad4844f1097855808f316 SHA1 (patch-modules_ocl_src_gftt.cpp) = fe1107c1613881d050ec5a87fad12b916ac8b8fc SHA1 (patch-modules_python_src2_cv2.cv.hpp) = 477bc2dd2090fd2aa955a7335717e7a0f23ebdf8 SHA1 (patch-modules_ts_src_ts.cpp) = 61e4ab59f2ca57f75212743bf869616dfc9e5f13 @ 1.28 log @OSX ffmpeg option build fixes adapted from upstream 2.4 branch. From Mansour Moufid in private mail. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.27 2014/07/24 17:16:02 jperkin Exp $ d14 1 @ 1.27 log @Avoid GS define from sys/regset.h on SunOS. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.26 2014/07/09 19:57:36 ryoon Exp $ d6 1 @ 1.26 log @Update to 2.4.9 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). @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.25 2014/05/27 09:57:21 joerg Exp $ d12 1 @ 1.25 log @Avoid two tautological checks. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.24 2013/08/07 13:01:20 fhajny Exp $ d3 3 a5 3 SHA1 (opencv-2.4.6.1.tar.gz) = e015bd67218844b38daf3cea8aab505b592a66c0 RMD160 (opencv-2.4.6.1.tar.gz) = 805193fc2e129bc4183c48057ca305774dfa5ed4 Size (opencv-2.4.6.1.tar.gz) = 80762052 bytes a11 2 SHA1 (patch-modules_legacy_src_dpstereo.cpp) = da9955fb6cc81054427b69efb97a58160b64f262 SHA1 (patch-modules_ts_include_opencv2_ts_ts__perf.hpp) = ecaba97683c0f389aa911d405d8a9f37a58be541 @ 1.24 log @Fix bad patch file. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.23 2013/08/05 12:27:48 fhajny Exp $ d11 1 @ 1.23 log @Update opencv to 2.4.6.1 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 @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.22 2013/06/19 11:54:04 fhajny Exp $ d12 1 a12 1 SHA1 (patch-modules_ts_include_opencv2_ts_ts__perf.hpp) = 3d12be4031ad60ca9cf571feacbbb58a0189378a @ 1.22 log @Fix build with SunOS and GCC 4.7. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.21 2013/06/14 21:28:42 wiz Exp $ d3 3 a5 3 SHA1 (opencv-2.4.5.tar.gz) = 9e25f821db9e25aa454a31976ba6b5a3a50b6fa4 RMD160 (opencv-2.4.5.tar.gz) = 3b7dc9da2e0b616a19e50ed5999ca0dd65c45d5f Size (opencv-2.4.5.tar.gz) = 81884985 bytes d12 1 a12 1 SHA1 (patch-modules_ts_include_opencv2_ts_ts__perf.hpp) = 8a7f08b176cedec85fd613e715d7b12d666a3e45 @ 1.21 log @Update to 2.4.5: 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. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.20 2013/06/12 10:13:58 jperkin Exp $ d13 1 a13 1 SHA1 (patch-modules_ts_src_ts.cpp) = c30482215db80285aa7a5ad039308cbfca033672 @ 1.20 log @Add patches required for SunOS support. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.19 2013/05/06 14:48:22 joerg Exp $ d3 3 a5 3 SHA1 (OpenCV-2.4.3.tar.bz2) = 982be2c3e52dfc3e9d14692c60bc856b2b766be2 RMD160 (OpenCV-2.4.3.tar.bz2) = b862ddd9e7fefd885d78835660a9f5c9320889c2 Size (OpenCV-2.4.3.tar.bz2) = 67240491 bytes @ 1.19 log @Add missing include. Require C++11 when building with Clang. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.18 2013/04/29 21:31:11 joerg Exp $ d6 1 d10 1 d13 1 @ 1.18 log @Add a number of includes hidden by libstdc++'s name space pollution. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.17 2013/02/26 23:38:08 joerg Exp $ d6 1 @ 1.17 log @Honor sequence point rules. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.16 2012/12/07 21:37:10 adam Exp $ d7 1 @ 1.16 log @Fix oversaturated int type compilation error for programs depending on opencv @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.15 2012/12/03 13:04:24 ryoon Exp $ d7 2 @ 1.15 log @Update to 2.4.3 Changelog: * Add universal parallell mechianism support * Add sample codes * Add some new algorithms * Many improvements in GPU support * Many bugfixes @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.14 2012/07/13 18:13:59 prlw1 Exp $ d6 1 @ 1.14 log @Update OpenCV to 2.4.2, highlights include: - New keypoint descriptor FREAK contributed by EPFL group - Improved face recognizer class and tutorial added by Philipp Wagner @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.13 2012/06/02 11:56:35 wiz Exp $ d3 3 a5 3 SHA1 (OpenCV-2.4.2.tar.bz2) = 96ff27b87e0f028d1d16201afebabec4e0c72367 RMD160 (OpenCV-2.4.2.tar.bz2) = 496964503629b0ff4432fbdd276837ab3f134411 Size (OpenCV-2.4.2.tar.bz2) = 52562911 bytes @ 1.13 log @adam reports that OS X 10.6 patch is not needed any longer, remove it. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.12 2012/06/01 21:24:57 wiz Exp $ d3 3 a5 4 SHA1 (OpenCV-2.4.1.tar.bz2) = bc6f23c62c8e3e0746f6f95067d54340d12aed56 RMD160 (OpenCV-2.4.1.tar.bz2) = c28fec73cc9fcf2a7ca38990a315babc0310f501 Size (OpenCV-2.4.1.tar.bz2) = 47211018 bytes SHA1 (patch-CMakeLists.txt) = 67660c0ed98db2c24b3348a47b5ea2d18903ed11 @ 1.12 log @Add upstream bug report URLs. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.11 2012/06/01 20:53:56 wiz Exp $ a6 1 SHA1 (patch-modules_core_include_opencv2_core_core.hpp) = ca4a861d0a1ac0c9416001ae9ed40cb0e924895a @ 1.11 log @Update to 2.4.1. Now builds with clang. Python option 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_" 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_ 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 "/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 d = new BriefDescriptorExtractor; @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.10 2012/04/15 03:49:00 markd Exp $ d6 2 a7 2 SHA1 (patch-CMakeLists.txt) = d4a48460328c6ef30bd1abd9d90895d186758565 SHA1 (patch-modules_core_include_opencv2_core_core.hpp) = 3936d23ad51f82536bb73428754d131259b8bf05 @ 1.10 log @Update to 2.3.1 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. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.9 2012/04/03 18:57:22 adam Exp $ d3 4 a6 4 SHA1 (OpenCV-2.3.1a.tar.bz2) = 9784e6824c5f677fac82ae83a2f366743adb3299 RMD160 (OpenCV-2.3.1a.tar.bz2) = f2f459bf7c163acb90427db2b0b425ab8008cde5 Size (OpenCV-2.3.1a.tar.bz2) = 32669613 bytes SHA1 (patch-CMakeLists.txt) = eb27b6cf8877b22bce4a27b7c27e637f5f3b4c52 @ 1.9 log @Fix building on Mac OS X (PR#46117) @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.8 2011/12/14 18:27:22 marino Exp $ d3 4 a6 6 SHA1 (OpenCV-2.2.0.tar.bz2) = 984ed71672d50391d0617fce2ef58e7590ec0fd7 RMD160 (OpenCV-2.2.0.tar.bz2) = 57aedb7678964f43af3f1c838a8266c7b4869b01 Size (OpenCV-2.2.0.tar.bz2) = 19800873 bytes SHA1 (patch-CMakeLists.txt) = f9954b7bf2972d0cfa0a653e62b7a65147441bb9 SHA1 (patch-aa) = 3a95649075b2ca94d39ced3c00da6a90b5834881 SHA1 (patch-ab) = 66936658e5ec12c479c29388916edd399c7feca6 @ 1.8 log @graphics/opencv: Add support for DragonFly @ text @d1 1 a1 1 $NetBSD$ d6 1 a6 1 SHA1 (patch-CMakeLists.txt) = 3c58828d9122105942820320a44f54e93effa33a d9 1 @ 1.7 log @Add upstream bug report. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.6 2011/01/14 11:22:37 wiz Exp $ d6 2 a7 1 SHA1 (patch-aa) = 58ac9aef394eedaf0be9afd725820b1acf54cd36 @ 1.6 log @Fix build with png-1.5. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.5 2010/12/06 16:55:23 wiz Exp $ d7 1 a7 1 SHA1 (patch-ab) = 58686f3ced10cdb432671031528825cb7dae02de @ 1.5 log @Add upstream bug report URL. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.4 2010/12/05 10:36:40 wiz Exp $ d7 1 @ 1.4 log @Update to 2.2.0. 2.2 (December, 2010) General Modifications and Improvements * The library has been reorganized. Instead of cxcore, cv, cvaux, highgui and ml we now have several smaller modules: * opencv_core - core functionality (basic structures, arithmetics and linear algebra, dft, XML and YAML I/O ...). * opencv_imgproc - image processing (filter, GaussianBlur, erode, dilate, resize, remap, cvtColor, calcHist etc.) * opencv_highgui - GUI and image & video I/O * opencv_ml - statistical machine learning models (SVM, Decision Trees, Boosting etc.) * opencv_features2d - 2D feature detectors and descriptors (SURF, FAST etc., * including the new feature detectors-descriptor-matcher framework) * opencv_video - motion analysis and object tracking (optical flow, motion templates, background subtraction) * opencv_objdetect - object detection in images (Haar & LBP face detectors, HOG people detector etc.) * opencv_calib3d - camera calibration, stereo correspondence and elements of 3D data processing * opencv_flann - the Fast Library for Approximate Nearest Neighbors (FLANN 1.5) and the OpenCV wrappers * opencv_contrib - contributed code that is not mature enough * opencv_legacy - obsolete code, preserved for backward compatibility * opencv_gpu - acceleration of some OpenCV functionality using CUDA (relatively unstable, yet very actively developed part of OpenCV) * If you detected OpenCV and configured your make scripts using CMake or pkg-config tool, your code will likely build fine without any changes. Otherwise, you will need to modify linker parameters (change the library names) and update the include paths. * It is still possible to use #include etc. but the recommended notation is: * #include "opencv2/imgproc/imgproc.hpp" * .. * Please, check the new C and C++ samples (https://code.ros.org/svn/opencv/trunk/opencv/samples), which now include the new-style headers. * The new-style wrappers now cover much more of OpenCV 2.x API. The documentation and samples are to be added later. You will need numpy in order to use the extra added functionality. * SWIG-based Python wrappers are not included anymore. * OpenCV can now be built for Android (GSoC 2010 project), thanks to Ethan Rublee; and there are some samples too. Please, check http://opencv.willowgarage.com/wiki/Android * The completely new opencv_gpu acceleration module has been created with support by NVidia. See below for details. New Functionality, Features * core: * The new cv::Matx type for fixed-type fixed-size matrices has been added. Vec is now derived from Matx. The class can be used for very small matrices, where cv::Mat use implies too much overhead. The operators to convert Matx to Mat and backwards are available. * cv::Mat and cv::MatND are made the same type: typedef cv::Mat cv::MatND. Note that many functions do not check the matrix dimensionality yet, so be careful when processing 3-, 4- ... dimensional matrices using OpenCV. * Experimental support for Eigen 2.x/3.x is added (WITH_EIGEN2 option in CMake). Again, there are convertors from Eigen2 matrices to cv::Mat and backwards. See modules/core/include/opencv2/core/eigen.hpp. * cv::Mat can now be print with "<<" operator. See opencv/samples/cpp/cout_mat.cpp. * cv::exp and cv::log are now much faster thanks to SSE2 optimization. * imgproc: * color conversion functions have been rewritten; * RGB->Lab & RGB->Luv performance has been noticeably improved. Now the functions assume sRGB input color space (e.g. gamma=2.2). If you want the original linear RGB->L** conversion (i.e. with gamma=1), use CV_LBGR2LAB etc. * VNG algorithm for Bayer->RGB conversion has been added. It's much slower than the simple interpolation algorithm, but returns significantly more detailed images * The new flavors of RGB->HSV/HLS conversion functions have been added for 8-bit images. They use the whole 0..255 range for the H channel instead of 0..179. The conversion codes are CV_RGB2HSV_FULL etc. * special variant of initUndistortRectifyMap for wide-angle cameras has been added: initWideAngleProjMap() * features2d: * the unified framework for keypoint extraction, computing the descriptors and matching them has been introduced. The previously available and some new detectors and descriptors, like SURF, Fast, StarDetector etc. have been wrapped to be used through the framework. The key advantage of the new framework (besides the uniform API for different detectors and descriptors) is that it also provides high-level tools for image matching and textured object detection. Please, see documentation http://opencv.willowgarage.com/documentation/cpp/features2d_common_interfaces_of_feature_detectors.html * and the C++ samples: * descriptor_extractor_matcher.cpp - finding object in a scene using keypoints and their descriptors. * generic_descriptor_matcher.cpp - variation of the above sample where the descriptors do not have to be computed explicitly. * bagofwords_classification.cpp - example of extending the framework and using it to process data from the VOC databases: * http://pascallin.ecs.soton.ac.uk/challenges/VOC/ * the newest super-fast keypoint descriptor BRIEF by Michael Calonder has been integrated by Ethan Rublee. See the sample opencv/samples/cpp/video_homography.cpp * SURF keypoint detector has been parallelized using TBB (the patch is by imahon and yvo2m) * objdetect: * LatentSVM object detector, implementing P. Felzenszwalb algorithm, has been contributed by Nizhniy Novgorod State University (NNSU) team. See * opencv/samples/c/latentsvmdetect.cpp * calib3d: * The new rational distortion model: * x' = x*(1 + k1*r2 + k2*r4 + k3*r6)/(1 + k4*r2 + k5*r4 + k6*r6) + , y' = y*(1 + k1*r2 + k2*r4 + k3*r6)/(1 + k4*r2 + k5*r4 + k6*r6) + * has been introduced. It is useful for calibration of cameras with wide-angle lenses. Because of the increased number of parameters to optimize you need to supply more data to robustly estimate all of them. Or, simply initialize the distortion vectors with zeros and pass CV_CALIB_RATIONAL_MODEL to enable the new model + CV_CALIB_FIX_K3 + CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5 or other such combinations to selectively enable or disable certain coefficients. * rectification of trinocular camera setup, where all 3 heads are on the same line, is added. see samples/cpp/3calibration.cpp * ml: * Gradient boosting trees model has been contributed by NNSU team. * highgui: * Experimental Qt backend for OpenCV has been added as a result of GSoC 2010 project, completed by Yannick Verdie. The backend has a few extra features, not present in the other backends, like text rendering using TTF fonts, separate "control panel" with sliders, push-buttons, checkboxes and radio buttons, interactive zooming, panning of the images displayed in highgui windows, "save as" etc. Please, check the youtube videos where Yannick demonstrates the new features: http://www.youtube.com/user/MrFrenchCookie#p/u * The new API is described here: http://opencv.willowgarage.com/documentation/cpp/highgui_qt_new_functions.html To make use of the new API, you need to have Qt SDK (or libqt4 with development packages) installed on your machine, and build OpenCV with Qt support (pass -DWITH_QT=ON to CMake; watch the output, make sure Qt is used as GUI backend) * 16-bit and LZW-compressed TIFFs are now supported. * You can now set the mode for IEEE1394 cameras on Linux. * contrib: * Chamfer matching algorithm has been contributed by Marius Muja, Antonella Cascitelli, Marco Di Stefano and Stefano Fabri. See samples/cpp/chamfer.cpp * gpu: * This is completely new part of OpenCV, created with the support by NVidia. Note that the package is at alpha, probably early beta state, so use it with care and check OpenCV SVN for updates. In order to use it, you need to have the latest NVidia CUDA SDK installed, and build OpenCV with CUDA support (-DWITH_CUDA=ON CMake flag). All the functionality is put to cv::gpu namespace. The full list of functions and classes can be found at opencv/modules/gpu/include/opencv2/gpu/gpu.hpp, and here are some major components of the API: * image arithmetics, filtering operations, morphology, geometrical transformations, histograms * 3 stereo correspondence algorithms: Block Matching, Belief Propagation and Constant-Space Belief Propagation. * HOG-based object detector. It runs more than order of magnitude faster than the CPU version! * See opencv/samples/cpp/ * python bindings: * A lot more of OpenCV 2.x functionality is now covered by Python bindings. Documentation, Samples * Links to wiki pages (mostly empty) have been added to each function description, see http://opencv.willowgarage.com * All the samples have been documented; most samples have been converted to C++ to use the new OpenCV API. Bug Fixes * Over 300 issues have been resolved. Most of the issues (closed and still open) are listed at https://code.ros.org/trac/opencv/report/6. @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.3 2010/12/05 10:01:52 wiz Exp $ d6 1 a6 1 SHA1 (patch-aa) = 05dac7aef61514e3ec16a90f42ebaa06b0777491 @ 1.3 log @Update to 2.1. Changelog of most insteresting changes: 2.1 (April, 2010) General Modifications - 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. - 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) Bug Fixes * - about 200 bugs have been fixed 2.0 (September, 2009) New functionality, features: * - General: * New Python interface officially in. - 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. 2.0 beta (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 reorganized; now all the external headers are placed in the single directory on all platforms. * The primary build system is CMake, * CXCORE, CV, CVAUX: * CXCORE now uses Lapack (CLapack 3.1.1.1 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 Leinhar * 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. * LBP (Local Binary Pattern) features * Extended variant of the Haar feature-based object detector - implemented by Maria Dimashova. It now supports Haar features and LBPs, other features can be added in the same way. * 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.hp * 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) * Samples, misc.: * Better eye detector has been contributed by Shiqi Yu, see opencv/data/haarcascades/*[lefteye|righteye]*.xml * sample LBP (Local Binary Pattern) 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 1.1pre1 (October, 2008) New functionality/features: * General: * Octave bindings have been added. See interfaces/swig/octave (for now, Linux only) * 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) @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.2 2006/11/19 23:13:42 rillig Exp $ d3 4 a6 5 SHA1 (OpenCV-2.1.0.tar.bz2) = 8e2d6b653296364ab2ca0fa5a5e6b0edfca114a7 RMD160 (OpenCV-2.1.0.tar.bz2) = e31cdbd30e7925e3725f5957616ffc59c58db247 Size (OpenCV-2.1.0.tar.bz2) = 14459566 bytes SHA1 (patch-aa) = 63c22048e3027000dd8600e4c6791bbd447a7733 SHA1 (patch-ab) = 91ddf39e1ab31102771ba571587391c08621e97b @ 1.2 log @Fixed "test ==" and the path to the Python interpreter, but did not add a dependency. PKGREVISION++ @ text @d1 1 a1 1 $NetBSD: distinfo,v 1.1.1.1 2006/11/09 05:13:41 uebayasi Exp $ d3 5 a7 6 SHA1 (opencv-1.0.0.tar.gz) = c7dd500703b0060cedfa049fcb33de0846e631fb RMD160 (opencv-1.0.0.tar.gz) = f041798ea63101b90e945957e0d0ad3f7497dcd4 Size (opencv-1.0.0.tar.gz) = 11146334 bytes SHA1 (patch-aa) = 2411f8ccfc2c9b1d5713840bbea939caee1b5bca SHA1 (patch-ab) = 7ece3d9908fa5cda8fc6d0cf81154a2aa899862a SHA1 (patch-ac) = b2e20615b2d295991ee7146b937ed43e3192f255 @ 1.1 log @Initial revision @ text @d1 1 a1 1 $NetBSD$ d7 2 @ 1.1.1.1 log @Import OpenCV 1.0.0, pkg/34655 from Anthony Mallet. OpenCV means Intel(R) Open Source Computer Vision Library. It is a collection of C functions and a few C++ classes that implement many popular Image Processing and Computer Vision algorithms. OpenCV provides cross-platform middle-to-high level API that includes about 300 C functions and a few C++ classes. Also there are Python bindings to OpenCV. OpenCV has no strict dependencies on external libraries, though it can use some (such as libjpeg, ffmpeg, GTK+ etc.) OpenCV provides transparent interface to Intel(R) Integrated Performance Primitives (IPP). That is, it loads automatically IPP libraries optimized for specific processor at runtime, if they are available. @ text @@