Added the defaultNorm() method to the DescriptorExtractor class. This method returns the default norm type for each descriptor type. The tests and C/C++ samples were updated to get the norm type directly from the DescriptorExtractor inherited classes.
This was reported in feature report #2182 (http://code.opencv.org/issues/2182). It will make it possible to get the norm type usually applied matching method for each descriptor, instead of passing it manually.
* #1538 from StevenPuttemans:bugfix_3283
* #1545 from alalek:ocl_test_fix_rng
* #1551 from alalek:cmake_install_win
* #1570 from ilya-lavrenov:ipp_warn_fix
* #1573 from alalek:perf_simple_strategy
* #1574 from alalek:svm_workaround
* #1576 from alalek:ocl_fix_cl_double
* #1577 from ilya-lavrenov:ocl_setto_opencl12
* #1578 from asmorkalov:android_fd_cp_fix
* #1579 from ilya-lavrenov:ocl_norm
* #1582 from sperrholz:ocl-arithm-additions
* #1586 from ilya-lavrenov:ocl_setto_win_fix
* #1589 from ilya-lavrenov:pr1582_fix
* #1591 from alalek:ocl_remove_cl_hpp_h
* #1592 from alalek:ocl_program_cache_update
* #1593 from ilya-lavrenov:ocl_war_on_double
* #1594 from ilya-lavrenov:ocl_perf
* #1595 from alalek:cl_code_cleanup
* #1596 from alalek:test_fix_run_py
* #1597 from alalek:ocl_fix_cleanup
* #1598 from alalek:ocl_fix_build_mac
* #1599 from ilya-lavrenov:ocl_mac_kernel_warnings
* #1601 from ilya-lavrenov:ocl_fix_tvl1_and_sparse
* #1602 from alalek:ocl_test_dump_info
* #1603 from ilya-lavrenov:ocl_disable_svm_noblas
* #1605 from alalek:ocl_fixes
* #1606 from ilya-lavrenov:ocl_imgproc
* #1607 from ilya-lavrenov:ocl_fft_cleanup
* #1608 from alalek:fix_warn_upd_haar
* #1609 from ilya-lavrenov:ocl_some_optimization
* #1610 from alalek:ocl_fix_perf_kalman
* #1612 from alalek:ocl_fix_string_info
* #1614 from ilya-lavrenov:ocl_svm_misprint
* #1616 from ilya-lavrenov:ocl_cvtColor
* #1617 from ilya-lavrenov:ocl_info
* #1622 from a0byte:2.4
* #1625 from ilya-lavrenov:to_string
Conflicts:
cmake/OpenCVConfig.cmake
cmake/OpenCVDetectPython.cmake
cmake/OpenCVGenConfig.cmake
modules/core/CMakeLists.txt
modules/nonfree/src/surf.ocl.cpp
modules/ocl/include/opencv2/ocl/ocl.hpp
modules/ocl/include/opencv2/ocl/private/util.hpp
modules/ocl/perf/main.cpp
modules/ocl/src/arithm.cpp
modules/ocl/src/cl_operations.cpp
modules/ocl/src/cl_programcache.cpp
modules/ocl/src/color.cpp
modules/ocl/src/fft.cpp
modules/ocl/src/filtering.cpp
modules/ocl/src/gemm.cpp
modules/ocl/src/haar.cpp
modules/ocl/src/imgproc.cpp
modules/ocl/src/matrix_operations.cpp
modules/ocl/src/pyrlk.cpp
modules/ocl/src/split_merge.cpp
modules/ocl/src/svm.cpp
modules/ocl/test/main.cpp
modules/ocl/test/test_fft.cpp
modules/ocl/test/test_moments.cpp
modules/ocl/test/test_objdetect.cpp
modules/ocl/test/test_optflow.cpp
modules/ocl/test/utility.hpp
modules/python/CMakeLists.txt
modules/ts/include/opencv2/ts.hpp
modules/ts/src/ts_perf.cpp
samples/android/face-detection/jni/DetectionBasedTracker_jni.cpp
Fixed visualization by choosing the color appropriate to the detection
score.
Previously the example showed all detections with the same color
disregarding the confidence. This led to the impression that the object
detection did not work at all because there are many detections with low
confidences.
PR to master was
https://github.com/Itseez/opencv/pull/320
