Adds fitEllipseDirect to imgproc: The Direct least square (Direct) method by Fitzgibbon1999.
New Tests are included for the methods.
fitEllipseAMS Tests
fitEllipseDirect Tests
Comparative examples are added to fitEllipse.cpp in Samples.
Added gradiantSize param into goodFeaturesToTrack API (#9618)
* Added gradiantSize param into goodFeaturesToTrack API
Removed hardcode value 3 in goodFeaturesToTrack API, and
added new param 'gradinatSize' in this API so that user can
pass any gradiant size as 3, 5 or 7.
Signed-off-by: Vipin Anand <anand.vipin@gmail.com>
Signed-off-by: Nilaykumar Patel<nilay.nilpat@gmail.com>
Signed-off-by: Prashanth Voora <prashanthx85@gmail.com>
* fixed compilation error for java test
Signed-off-by: Vipin Anand <anand.vipin@gmail.com>
* Modifying code for previous binary compatibility and fixing other warnings
fixed ABI break issue
resolved merged conflict
compilation error fix
Signed-off-by: Vipin Anand <anand.vipin@gmail.com>
Signed-off-by: Patel, Nilaykumar K <nilay.nilpat@gmail.com>
* lab_tetra squashed
* initial version is almost written
* unfinished work
* compilation fixed, to be debugged
* Lab test removed
* more fixes
* Luv2RGBinteger: channels order fixed
* Lab structs removed
* good trilinear interpolation added
* several fixes
* removed Luv2RGB interpolations, XYZ tables; 8-cell LUT added
* no_interpolate made 8-cell
* interpolations rewritten to 8-cell, minor fixes
* packed interpolation added for RGB2Luv
* tetra implemented
* removing unnecessary code
* LUT building merged
* changes ported to color.cpp
* minor fixes; try to suppress warnings
* fixed v range of Luv
* fixed incorrect src channel number
* minor fixes
* preliminary version of Luv2RGBinteger is done
* Luv2RGB_b is in progress
* XYZ color constants converted to softfloat
* Luv test: precision fixed
* Luv bit-exactness test added
* warnings fixed
* compilation fixed, error message fixed
* Luv check is limited to [0-2,0-2,0-2] by XYZ
* L->Y generation moved to LUT
* LUTs added for up and vp of Luv2RGB_b
* still works
* fixed-point is done, works at maxerr 2
* vectorized code is done, 2x slower than original
* perf improved by 10%
* extra comments removed
* code moved to color.cpp
* test_lab.cpp updated
* minor refactoring
* test added for Luv2RGB
* OCL Luv2RGB_b: XYZ are limited to [0, 2]; docs updated
* Luv2RGB_b rewritten to universal intrinsics
* test_lab.cpp moved to luv_tetra branch
* Imgproc_ColorLab_Full.accuracy test fixed
* Lab and Luv tests: rewritten, constants explained
* CV_ColorCvtBaseTest: added methods for 8u implementations
* Lab2RGB_b: bit-exactness enabled for all modes; non-vectorized code fixed to comply with vectorized
* srgb support added
* XYZ constants made softdouble
* bit-exact tests written for Lab
* ColorLab_full test fixed
* reverted: no 8u convertors for CV_ColorCvtBaseTest
* added checksum-based test for Lab bit-exactness
* extra declarations removed
* Lab test fix: stop at first mismatch
* test info output improved
* error message fixed
* lab_tetra squashed
* initial version is almost written
* unfinished work
* compilation fixed, to be debugged
* Lab test removed
* more fixes
* Luv2RGBinteger: channels order fixed
* Lab structs removed
* good trilinear interpolation added
* several fixes
* removed Luv2RGB interpolations, XYZ tables; 8-cell LUT added
* no_interpolate made 8-cell
* interpolations rewritten to 8-cell, minor fixes
* packed interpolation added for RGB2Luv
* tetra implemented
* removing unnecessary code
* LUT building merged
* changes ported to color.cpp
* minor fixes; try to suppress warnings
* fixed v range of Luv
* fixed incorrect src channel number
* minor fixes
* preliminary version of Luv2RGBinteger is done
* Luv2RGB_b is in progress
* XYZ color constants converted to softfloat
* Luv test: precision fixed
* Luv bit-exactness test added
* warnings fixed
* compilation fixed, error message fixed
* test_lab.cpp removed
Updated integrations for:
cv::split
cv::merge
cv::insertChannel
cv::extractChannel
cv::Mat::convertTo - now with scaled conversions support
cv::LUT - disabled due to performance issues
Mat::copyTo
Mat::setTo
cv::flip
cv::copyMakeBorder - currently disabled
cv::polarToCart
cv::pow - ipp pow function was removed due to performance issues
cv::hal::magnitude32f/64f - disabled for <= SSE42, poor performance
cv::countNonZero
cv::minMaxIdx
cv::norm
cv::canny - new integration. Disabled for threaded;
cv::cornerHarris
cv::boxFilter
cv::bilateralFilter
cv::integral
Added assertios to remap and warpAffine functions
As @mshabunin said, remap and warpAffine functions do not support more than 4 channels in
Bicubic and Lanczos4 interpolation modes. Assertions were added. Appropriate test was chenged.
resolves#8272
Warping a matrix with more than 4 channels using BORDER_CONSTANT and
INTER_NEAREST, INTER_CUBIC or INTER_LANCZOS4 interpolation led to
undefined behaviour. This commit changes the behavior of these methods
to be similar to that of INTER_LINEAR. Changed the scope of some of the
variables to more local. Modified some tests to be able to detect the
error described.
Add new 5x5 gaussian blur kernel for CV_8UC1 format,
it is 50% ~ 70% faster than current ocl kernel in the perf test.
Signed-off-by: Li Peng <peng.li@intel.com>
Add new OpenCL kernels for bicubic interploation, it is 20% faster
than current warp image kernel with bicubic interploation.
Signed-off-by: Li Peng <peng.li@intel.com>
Add new ocl kernels for warpAffine and warpPerspective,
The average performance improvemnt is about 30%. The new
ocl kernels require CV_8UC1 format and support nearest
neighbor and bilinear interpolation.
Signed-off-by: Li Peng <peng.li@intel.com>
This ocl kernel is 46%~171% faster than current laplacian 3x3
ocl kernel in the perf test, with image format "CV_8UC1".
Signed-off-by: Li Peng <peng.li@intel.com>
Change contour test images to be very wide (#7464)
* Change contour test images to be very wide (#7409, #7458)
Unfortunately, slows down the tests.
* Decrease the number of contour test cases, in order to (at least partially) offset the test run duration increase caused by making the test images wider
* Don't test with very wide images on 32-bit architectures
This ocl kernel is for 3x3 kernel size and CV_8UC1 format
It is 115% ~ 300% faster than current ocl path in perf test
python ./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_GaussianBlurFixture*
Signed-off-by: Li Peng <peng.li@intel.com>
This kernel is for CV_8UC1 format and 3x3 kernel size,
It is about 33% ~ 55% faster than current ocl kernel with below perf test
python ./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_ErodeFixture*
python ./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_DilateFixture*
Also add accuracy test cases for this kernel, the test command is
./bin/opencv_test_imgproc --gtest_filter=OCL_Filter/MorphFilter3x3*
Signed-off-by: Li Peng <peng.li@intel.com>
The optimization is for CV_8UC1 format and 3x3 box filter,
it is 15%~87% faster than current ocl kernel with below perf test
./modules/ts/misc/run.py -t imgproc --gtest_filter=OCL_BlurFixture*
Also add test cases for this ocl kernel.
Signed-off-by: Li Peng <peng.li@intel.com>
* Add Grana's connected components algorithm for 8-way connectivity. That algorithm is faster than Wu's one (currently implemented in opencv). For more details see https://github.com/prittt/YACCLAB.
* New functions signature and distance transform compatibility
* Add tests to imgproc/test/test_connectedcomponents.cpp
* Change of test_connectedcomponents.cpp for c++98 support
IPP_VERSION_MAJOR * 100 + IPP_VERSION_MINOR*10 + IPP_VERSION_UPDATE
to manage changes between updates more easily.
IPP_DISABLE_BLOCK was added to ease tracking of disabled IPP functions;
