opencv

Commit Graph

Author	SHA1	Message	Date
Clement Courbet	da555a2c9b	Optimize opencv dft by vectorizing radix2 and radix3. This is useful for non power-of-two sizes when WITH_IPP is not an option. This shows consistent improvement over openCV benchmarks, and we measure even larger improvements on our internal workloads. For example, for 320x480, `32FC`, we can see a ~5% improvement}, as `320=2^65` and `480=2^535`, so the improved radix3 version is used. `64FC*` is flat as expected, as we do not specialize the functors for `double` in this change. ``` dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, 0, false) 1.239 1.153 1.07 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, 0, true) 0.991 0.926 1.07 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_COMPLEX_OUTPUT, false) 1.367 1.281 1.07 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_COMPLEX_OUTPUT, true) 1.114 1.049 1.06 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_INVERSE, false) 1.313 1.254 1.05 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_INVERSE, true) 1.027 0.977 1.05 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 1.296 1.217 1.06 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 1.039 0.963 1.08 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_ROWS, false) 0.542 0.524 1.04 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_ROWS, true) 0.293 0.277 1.06 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_SCALE, false) 1.265 1.175 1.08 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC1, DFT_SCALE, true) 1.004 0.942 1.07 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, 0, false) 1.292 1.280 1.01 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, 0, true) 1.038 1.030 1.01 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_COMPLEX_OUTPUT, false) 1.484 1.488 1.00 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_COMPLEX_OUTPUT, true) 1.222 1.224 1.00 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_INVERSE, false) 1.380 1.355 1.02 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_INVERSE, true) 1.117 1.133 0.99 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 1.372 1.383 0.99 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 1.117 1.127 0.99 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_ROWS, false) 0.546 0.539 1.01 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_ROWS, true) 0.293 0.299 0.98 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_SCALE, false) 1.351 1.339 1.01 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 64FC1, DFT_SCALE, true) 1.099 1.092 1.01 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, 0, false) 2.235 2.123 1.05 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, 0, true) 1.843 1.727 1.07 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_COMPLEX_OUTPUT, false) 2.189 2.109 1.04 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_COMPLEX_OUTPUT, true) 1.827 1.754 1.04 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_INVERSE, false) 2.392 2.309 1.04 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_INVERSE, true) 1.951 1.865 1.05 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 2.391 2.293 1.04 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 1.954 1.882 1.04 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_ROWS, false) 0.811 0.815 0.99 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_ROWS, true) 0.426 0.437 0.98 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_SCALE, false) 2.268 2.152 1.05 dft::Size_MatType_FlagsType_NzeroRows::(320x480, 32FC2, DFT_SCALE, true) 1.893 1.788 1.06 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, 0, false) 4.546 4.395 1.03 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, 0, true) 3.616 3.426 1.06 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_COMPLEX_OUTPUT, false) 4.843 4.668 1.04 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_COMPLEX_OUTPUT, true) 3.825 3.748 1.02 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_INVERSE, false) 4.720 4.525 1.04 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_INVERSE, true) 3.743 3.601 1.04 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 4.755 4.527 1.05 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 3.744 3.586 1.04 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_ROWS, false) 1.992 2.012 0.99 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_ROWS, true) 1.048 1.048 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_SCALE, false) 4.625 4.451 1.04 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC1, DFT_SCALE, true) 3.643 3.491 1.04 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, 0, false) 4.499 4.488 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, 0, true) 3.559 3.555 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_COMPLEX_OUTPUT, false) 5.155 5.165 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_COMPLEX_OUTPUT, true) 4.103 4.101 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_INVERSE, false) 5.484 5.474 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_INVERSE, true) 4.617 4.518 1.02 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 5.547 5.509 1.01 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 4.553 4.554 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_ROWS, false) 2.067 2.018 1.02 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_ROWS, true) 1.104 1.079 1.02 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_SCALE, false) 4.665 4.619 1.01 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 64FC1, DFT_SCALE, true) 3.698 3.681 1.00 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, 0, false) 8.774 8.275 1.06 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, 0, true) 6.975 6.527 1.07 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_COMPLEX_OUTPUT, false) 8.720 8.270 1.05 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_COMPLEX_OUTPUT, true) 6.928 6.532 1.06 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_INVERSE, false) 9.272 8.862 1.05 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_INVERSE, true) 7.323 6.946 1.05 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 9.262 8.768 1.06 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 7.298 6.871 1.06 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_ROWS, false) 3.766 3.639 1.03 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_ROWS, true) 1.932 1.889 1.02 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_SCALE, false) 8.865 8.417 1.05 dft::Size_MatType_FlagsType_NzeroRows::(800x600, 32FC2, DFT_SCALE, true) 7.067 6.643 1.06 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, 0, false) 10.014 10.141 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, 0, true) 7.600 7.632 1.00 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_COMPLEX_OUTPUT, false) 11.059 11.283 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_COMPLEX_OUTPUT, true) 8.475 8.552 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_INVERSE, false) 12.678 12.789 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_INVERSE, true) 10.445 10.359 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 12.626 12.925 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 10.538 10.553 1.00 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_ROWS, false) 5.041 5.084 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_ROWS, true) 2.595 2.607 1.00 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_SCALE, false) 10.231 10.330 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC1, DFT_SCALE, true) 7.786 7.815 1.00 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, 0, false) 13.597 13.302 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, 0, true) 10.377 10.207 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_COMPLEX_OUTPUT, false) 15.940 15.545 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_COMPLEX_OUTPUT, true) 12.299 12.230 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_INVERSE, false) 15.270 15.181 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_INVERSE, true) 12.757 12.339 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 15.512 15.157 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 12.505 12.635 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_ROWS, false) 6.359 6.255 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_ROWS, true) 3.314 3.248 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_SCALE, false) 13.937 13.733 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 64FC1, DFT_SCALE, true) 10.782 10.495 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, 0, false) 18.985 18.926 1.00 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, 0, true) 14.256 14.509 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_COMPLEX_OUTPUT, false) 18.696 19.021 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_COMPLEX_OUTPUT, true) 14.290 14.429 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_INVERSE, false) 20.135 20.296 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_INVERSE, true) 15.390 15.512 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 20.121 20.354 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 15.341 15.605 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_ROWS, false) 8.932 9.084 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_ROWS, true) 4.539 4.649 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_SCALE, false) 19.137 19.303 0.99 dft::Size_MatType_FlagsType_NzeroRows::(1280x1024, 32FC2, DFT_SCALE, true) 14.565 14.808 0.98 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, 0, false) 22.553 21.171 1.07 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, 0, true) 17.850 16.390 1.09 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_COMPLEX_OUTPUT, false) 24.062 22.634 1.06 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_COMPLEX_OUTPUT, true) 19.342 17.932 1.08 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_INVERSE, false) 28.609 27.326 1.05 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_INVERSE, true) 24.591 23.289 1.06 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 28.667 27.467 1.04 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 24.671 23.309 1.06 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_ROWS, false) 9.458 9.077 1.04 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_ROWS, true) 4.709 4.566 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_SCALE, false) 22.791 21.583 1.06 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC1, DFT_SCALE, true) 18.029 16.691 1.08 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, 0, false) 25.238 24.427 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, 0, true) 19.636 19.270 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_COMPLEX_OUTPUT, false) 28.342 27.957 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_COMPLEX_OUTPUT, true) 22.413 22.477 1.00 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_INVERSE, false) 26.465 26.085 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_INVERSE, true) 21.972 21.704 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 26.497 26.127 1.01 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 22.010 21.523 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_ROWS, false) 11.188 10.774 1.04 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_ROWS, true) 6.094 5.916 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_SCALE, false) 25.728 24.934 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 64FC1, DFT_SCALE, true) 20.077 19.653 1.02 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, 0, false) 43.834 40.726 1.08 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, 0, true) 35.198 32.218 1.09 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_COMPLEX_OUTPUT, false) 43.743 40.897 1.07 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_COMPLEX_OUTPUT, true) 35.240 32.226 1.09 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_INVERSE, false) 46.022 42.612 1.08 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_INVERSE, true) 36.779 33.961 1.08 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 46.396 42.723 1.09 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 37.025 33.874 1.09 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_ROWS, false) 17.334 16.832 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_ROWS, true) 9.212 8.970 1.03 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_SCALE, false) 44.190 41.211 1.07 dft::Size_MatType_FlagsType_NzeroRows::(1920x1080, 32FC2, DFT_SCALE, true) 35.900 32.888 1.09 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, 0, false) 40.948 38.256 1.07 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, 0, true) 33.825 30.759 1.10 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_COMPLEX_OUTPUT, false) 53.210 53.584 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_COMPLEX_OUTPUT, true) 46.356 46.712 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_INVERSE, false) 47.471 47.213 1.01 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_INVERSE, true) 40.491 41.363 0.98 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 46.724 47.049 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 40.834 41.381 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_ROWS, false) 14.508 14.490 1.00 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_ROWS, true) 7.832 7.828 1.00 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_SCALE, false) 41.491 38.341 1.08 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC1, DFT_SCALE, true) 34.587 31.208 1.11 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, 0, false) 65.155 63.173 1.03 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, 0, true) 56.091 54.752 1.02 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_COMPLEX_OUTPUT, false) 71.549 70.626 1.01 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_COMPLEX_OUTPUT, true) 62.319 61.437 1.01 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_INVERSE, false) 61.480 59.540 1.03 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_INVERSE, true) 54.047 52.650 1.03 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 61.752 61.366 1.01 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 54.400 53.665 1.01 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_ROWS, false) 20.219 19.704 1.03 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_ROWS, true) 11.145 10.868 1.03 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_SCALE, false) 66.220 64.525 1.03 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 64FC1, DFT_SCALE, true) 57.389 56.114 1.02 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, 0, false) 86.761 88.128 0.98 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, 0, true) 75.528 76.725 0.98 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_COMPLEX_OUTPUT, false) 86.750 88.223 0.98 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_COMPLEX_OUTPUT, true) 75.830 76.809 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_INVERSE, false) 91.728 92.161 1.00 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_INVERSE, true) 78.797 79.876 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, false) 92.163 92.177 1.00 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_INVERSE\|DFT_COMPLEX_OUTPUT, true) 78.957 79.863 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_ROWS, false) 24.781 25.576 0.97 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_ROWS, true) 13.226 13.695 0.97 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_SCALE, false) 87.990 89.324 0.99 dft::Size_MatType_FlagsType_NzeroRows::(2048x2048, 32FC2, DFT_SCALE, true) 76.732 77.869 0.99 ```	4 years ago
Alexander Alekhin	cd00d8f3f0	core(trace): lazy quering for OPENCV_TRACE_LOCATION - fixes proper initialization of non-trivial variable	4 years ago
Alexander Alekhin	b3755e617c	ocl: silence warning in case of async cleanup - OpenCL kernel cleanup processing is asynchronous and can be called even after forced clFinish() - buffers are released later in asynchronous mode - silence these false positive cases for asynchronous cleanup	4 years ago
danielenricocahall	ac177b849c	Improve initialization performance of Brisk reformatting Improve initialization performance of Brisk fix formatting Improve initialization performance of Brisk formatting Improve initialization performance of Brisk make a lookup table for ring use cosine/sine lookup table for theta in brisk and utilize trig identity fix ring lookup table use cosine/sine lookup table for theta in brisk and utilize trig identity formatting use cosine/sine lookup table for theta in brisk and utilize trig identity move scale radius product to ring loop to ensure it's not recomputed for each rot revert change move scale radius product to ring loop to ensure it's not recomputed for each rot remove rings lookup table move scale radius product to ring loop to ensure it's not recomputed for each rot fix formatting of for loop move scale radius product to ring loop to ensure it's not recomputed for each rot use sine/cosine approximations for brisk lookup table. add documentation for sine/cosine lookup tables Improve initialization performance of BRISK	4 years ago
Tomoaki Teshima	cc769ff19d	fix build error on odroid-n2-plus	4 years ago
Yosshi999	1834eed809	Merge pull request #18001 from Yosshi999:sift-8bit-descr * 8-bit SIFT descriptors * use clearer parameter * update docs * propagate type info * overload function for avoiding ABI-break * bugfix: some values are undefined when CV_SIMD is absent	4 years ago
Alexander Alekhin	7ec9f52509	highgui: don't terminate if we can't initialize GTK backend - allow Users to handle such case - exception will be thrown instead	4 years ago
nhlsm	68f527267b	Merge pull request #18080 from nhlsm:improve-mat-operator-assign-scalar * improve Mat::operator=(Scalar) * touch * remove trailing whitespace * TEST: check if old code pass test or not * remove CV_Error * remove warning * fix: is -> Scalar * 1) Mat mat -> Mat &mat 2) return bool, add output param add comment	4 years ago
Liubov Batanina	ad63d24dba	Merge pull request #18096 from l-bat:update_onnx_importer * Added ReduceSum to ONNX importer * Fix comments * Fix Mul	4 years ago
Liubov Batanina	339b963e6b	Fix MatMul and Add axes	4 years ago
Alexander Alekhin	00890aecdf	core(ocl): fix ocl::Image2d::isFormatSupported() in case of OPENCV_OPENCL_DEVICE=disabled	4 years ago
Yashas Samaga B L	2171cae8ff	Merge pull request #17976 from YashasSamaga:dnn-fusion-tests-fix-ocl dnn: add exhaustive fusion tests, enable more eltwise fusions * add eltwise fusion tests, enable more eltwise fusions * merge weighted eltwise tests with eltwise tests	4 years ago
Pierre-Emmanuel Viel	3f55152ca0	Add debug assert to check in FLANN the vectors size is multiple of the architecture word size	4 years ago
Liubov Batanina	f3cebb3e1b	Merge pull request #18077 from l-bat:reduce_sum * Supported ReduceSum op * Skip test	4 years ago
Pierre-Emmanuel Viel	98de57c6c4	Refactoring to prepare for other vector types while mutualizing some methods	4 years ago
zhaoyue-zephyrus	e231be86b7	support flownet2 with arbitary input size revise default proto to match the filename in documentations fix a bug beautify python codes fix bug beautify codes add test samples with larger/smaller size remove unless code using bytearray without creating tmp file remove useless codes	4 years ago
Liubov Batanina	6226ea0085	Fix bug in ONNX Gather op	4 years ago
Vadim Pisarevsky	1537ecd931	* added depth-wise convolution; gives ~20-30% performance improvement in MobileSSD networks * hopefully, eliminated compile warnings, errors, as well as failure in one test * * fixed a few typos * decreased buffer size in some cases * added more optimal im2row branch in the case of 1x1 convolutions * tuned fastConv to reduce the number of passes over arrays backport of commit `77b01deb80`	4 years ago
Gabriel	96ce65f021	Document PatchNANs input type	4 years ago
danielenricocahall	8457e471fd	add relu as activation option in darknet add relu option add relu as activation option in darknet simplify the setParams if-else ladder add relu as activation option in darknet correct activation_param type format format add relu as activation option in darknet spacing spacing add relu as activation option in darknet	4 years ago
Ilya Churaev	246de2b7f5	Replaced copy_with_new_args to clone_with_new_inputs	4 years ago
Ilya Churaev	e8c26963e9	Fixed removing is_parameter, is_constant, is_output	4 years ago
pemmanuelviel	793e7c0d9f	Merge pull request #18019 from pemmanuelviel:pev--multiple-kmeans-trees * Possibility to set more than one tree for the hierarchical KMeans (default is still 1 tree). This particularly improves NN retrieval results with binary vectors, allowing better quality compared to LSH for similar processing time when speed is the criterium. * Add explanations on the FLANN's hierarchical KMeans for binary data.	4 years ago
Liubov Batanina	d695208727	Merge pull request #17967 from l-bat:non_const_weights_for_conv * Supported convolution with non-const weights * Fix opencl blobs * Update tests	4 years ago
kadi soheib	613ff61de7	Added reference to paper.	4 years ago
Alexander Alekhin	1c8ee3f957	Merge pull request #17885 from alalek:dnn_ocl_slice_update DNN: OpenCL/slice update * dnn(ocl/slice): make slice kernel VTune friendly - more unique names - inline code of copy functions * dnn(ocl/slice): prefer to spawn more work groups - even in case with 1D copy - perf improvement up to 2x of kernel time (due to changed configuration 128x1x1 => 128x32x1) * dnn(ocl/slice): cache kernel exec info	4 years ago
Yosshi999	922108060d	Merge pull request #17907 from Yosshi999:gsoc_asift-py2cpp * Implement ASIFT in C++ * '>>' should be '> >' within a nested template * add a sample for asift usage * bugfix empty keypoints cause crash * simpler initialization for mask * suppress the number of lines * correct tex document * type casting * add descriptorsize for asift * smaller testdata for asift * more smaller test data * add OpenCV short license header	4 years ago
Suleyman TURKMEN	c262eea84a	Update warpPerspective_demo.cpp	4 years ago
danielenricocahall	f2ca7e664a	add python binding and tests for composePanorama fix tests pick 54039c2afd add python binding and tests for composePanorama	4 years ago
Dmitry Kurtaev	cf8f65d806	Do not use size_t for nGraph layers	4 years ago
Pierre-Emmanuel Viel	bc221bdb90	Cleaner code for hierarchical_clustering	4 years ago
kadi soheib	6bed5c181b	Corrected Comment as requested by reviewer.	4 years ago
Pavel Rojtberg	3c3e131c38	Merge pull request #17977 from paroj:hervec * calib3d: calibrateHandEye - allow using Rodrigues vectors for rotation * calib3d: calibrateHandEye - test rvec representation	4 years ago
Florian Jung	f66fc199a2	Fix build of grfmt_jpeg2000.cpp libjasper has recently changed `jas_matrix_get` from a macro to an inline function (389951d071 in https://github.com/jasper-software/jasper), causing the build to fail.	4 years ago
Namgoo Lee	11ac26bfb4	test code	4 years ago
Namgoo Lee	2241bfb0df	Use "src" not "*this" for source GpuMat	4 years ago
Tomoaki Teshima	19646ad049	let the test pass on Jetson	4 years ago
Alexander Smorkalov	7ed37b3fa5	MP4 autorotation tests and various fixes for Windows - Added test for automated rotation for MP4 videos with metadata - Fix 180 degrees rotation bug - Moved rotation logic to cv::VideoCapture implementation for FFmpeg and restore binary compatibility with FFmpeg wrapper.	4 years ago
Alexey Lapshin	f0271e54d9	Autorotation for mp4 streams with metadata - Add VideoCapture camera orientation property for mp4 videos with camera orientation meta. - Add auto rotation for 90, 180, 270 degrees using cv::rotate	4 years ago
Sinitsina	0ac2f0e04c	mish_functor_update	4 years ago
Alexander Smorkalov	abceef74e0	Added reference to Original Wu's articte about SAUF connected components search method.	4 years ago
Namgoo Lee	9411cd6c07	Use in-place npp function for inplace arguments	4 years ago
Liubov Batanina	a35d4f9029	Support Gather for variable inputs	4 years ago
Alexander Alekhin	e8d4259f9a	release: OpenCV 3.4.11	4 years ago
Alexander Alekhin	83e6813345	imgproc: add missing check into cvtColorTwoPlane()	4 years ago
Alexander Alekhin	81e027eef7	dnn: fix OpenCL implementation of Slice layer	4 years ago
Alexander Alekhin	1c371d07b5	dnn(test): adjust tests for OpenVINO 2020.4	4 years ago
Alexander Alekhin	55e8549839	dnn: eliminate IE deprecation warning	4 years ago
Alexander Alekhin	435b6df989	dnn: use OpenVINO 2020.4 defines original commit: `2813aa7eb9`	4 years ago
Dmitry Kurtaev	cc584760d3	Fix TensorFlow->ONNX imports	4 years ago

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19885 Commits (2d2d72afbb6a4f1936e2fa5ba28fc1744a8047d2)