Pull requests:
#943 from jet47:cuda-5.5-support
#944 from jet47:cmake-2.8.11-cuda-fix
#912 from SpecLad:contributing
#934 from SpecLad:parallel-for
#931 from jet47:gpu-test-fixes
#932 from bitwangyaoyao:2.4_fixBFM
#918 from bitwangyaoyao:2.4_samples
#924 from pengx17:2.4_arithm_fix
#925 from pengx17:2.4_canny_tmp_fix
#927 from bitwangyaoyao:2.4_perf
#930 from pengx17:2.4_haar_ext
#928 from apavlenko:bugfix_3027
#920 from asmorkalov:android_move
#910 from pengx17:2.4_oclgfft
#913 from janm399:2.4
#916 from bitwangyaoyao:2.4_fixPyrLK
#919 from abidrahmank:2.4
#923 from pengx17:2.4_macfix
Conflicts:
modules/calib3d/src/stereobm.cpp
modules/features2d/src/detectors.cpp
modules/gpu/src/error.cpp
modules/gpu/src/precomp.hpp
modules/imgproc/src/distransform.cpp
modules/imgproc/src/morph.cpp
modules/ocl/include/opencv2/ocl/ocl.hpp
modules/ocl/perf/perf_color.cpp
modules/ocl/perf/perf_imgproc.cpp
modules/ocl/perf/perf_match_template.cpp
modules/ocl/perf/precomp.cpp
modules/ocl/perf/precomp.hpp
modules/ocl/src/arithm.cpp
modules/ocl/src/canny.cpp
modules/ocl/src/filtering.cpp
modules/ocl/src/haar.cpp
modules/ocl/src/hog.cpp
modules/ocl/src/imgproc.cpp
modules/ocl/src/opencl/haarobjectdetect.cl
modules/ocl/src/pyrlk.cpp
modules/video/src/bgfg_gaussmix2.cpp
modules/video/src/lkpyramid.cpp
platforms/linux/scripts/cmake_arm_gnueabi_hardfp.sh
platforms/linux/scripts/cmake_arm_gnueabi_softfp.sh
platforms/scripts/ABI_compat_generator.py
samples/ocl/facedetect.cpp
Yes, it's as ludicrous as it sounds, but it's still true. Bizarrely,
the previous commit makes CLAHE run about 10% slower on Android, even
though it doesn't even touch any CLAHE code. Splitting it off fixes that,
although the reason it does is a mystery for the ages.
It's cleaner when it's in its own file, anyway. ;=]
When comparing histograms that look like multi-channel images (e.g a 3D histogram, of 4x4x4 bins, might appear as a CV_32FC4 matrix), cv::compareHist would complain because it was expecting the matrix type() == CV_32F. Now we test matrix depth() == CV_32F instead.
The orientation of convexHull's result is currently the opposite of what the
documentation would suggest:
>>> import cv2, numpy as np
>>> points = np.array([[0,0],[0,1],[1,0]], dtype=np.int32)
>>> cv2.convexHull(points, clockwise=False)
array([[[1, 0]],
[[0, 1]],
[[0, 0]]], dtype=int32)
>>> cv2.convexHull(points, clockwise=True)
array([[[0, 0]],
[[0, 1]],
[[1, 0]]], dtype=int32)
Changing the function itself is probably not a good idea at this point, so
this fixes the documentation by flipping the coordinate system.
I also removed the mention of the origin, since it's irrelevant for this
function.
