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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin 2018-11-14 19:41:09 +00:00
commit 8409aa9eba
6 changed files with 33 additions and 23 deletions
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6
doc/py_tutorials/py_imgproc/py_transforms/py_fourier_transform/py_fourier_transform.markdown
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@ -79,11 +79,11 @@ using **np.ifft2()** function. The result, again, will be a complex number. You
absolute value.
@code{.py}
rows, cols = img.shape
crow,ccol = rows/2 , cols/2
fshift[crow-30:crow+30, ccol-30:ccol+30] = 0
crow,ccol = rows//2 , cols//2
fshift[crow-30:crow+31, ccol-30:ccol+31] = 0
f_ishift = np.fft.ifftshift(fshift)
img_back = np.fft.ifft2(f_ishift)
img_back = np.abs(img_back)
img_back = np.real(img_back)
plt.subplot(131),plt.imshow(img, cmap = 'gray')
plt.title('Input Image'), plt.xticks([]), plt.yticks([])

3
modules/dnn/src/dnn.cpp
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@ -1996,6 +1996,9 @@ struct Net::Impl
}
}
if (preferableBackend != DNN_BACKEND_OPENCV)
continue; // Go to the next layer.
// the optimization #2. if there is no layer that takes max pooling layer's computed
// max indices (and only some semantical segmentation networks might need this;
// many others only take the maximum values), then we switch the max pooling

9
modules/dnn/src/layers/batch_norm_layer.cpp
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@ -10,6 +10,7 @@ Implementation of Batch Normalization layer.
*/
#include "../precomp.hpp"
#include "layers_common.hpp"
#include "../op_halide.hpp"
#include "../op_inf_engine.hpp"
#include <opencv2/dnn/shape_utils.hpp>
@ -284,10 +285,10 @@ public:
v_float32x4 x1 = v_load(srcptr + i + 4);
v_float32x4 x2 = v_load(srcptr + i + 8);
v_float32x4 x3 = v_load(srcptr + i + 12);
x0 = v_muladd(x0, w, b);
x1 = v_muladd(x1, w, b);
x2 = v_muladd(x2, w, b);
x3 = v_muladd(x3, w, b);
x0 = v_muladd(x0, wV, bV);
x1 = v_muladd(x1, wV, bV);
x2 = v_muladd(x2, wV, bV);
x3 = v_muladd(x3, wV, bV);
v_store(dstptr + i, x0);
v_store(dstptr + i + 4, x1);
v_store(dstptr + i + 8, x2);

1
modules/dnn/src/layers/elementwise_layers.cpp
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@ -45,7 +45,6 @@
#include "../op_halide.hpp"
#include "../op_inf_engine.hpp"
#include "../op_vkcom.hpp"
#include "opencv2/imgproc.hpp"
#include <opencv2/dnn/shape_utils.hpp>
#include <iostream>

25
modules/imgproc/src/morph.cpp
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@ -45,6 +45,7 @@
#include "opencl_kernels_imgproc.hpp"
#include <iostream>
#include "hal_replacement.hpp"
#include <opencv2/core/utils/configuration.private.hpp>
/****************************************************************************************\
Basic Morphological Operations: Erosion & Dilation
@ -1405,7 +1406,6 @@ void morph(int op, int src_type, int dst_type,
#define ROUNDUP(sz, n) ((sz) + (n) - 1 - (((sz) + (n) - 1) % (n)))
#ifndef __APPLE__
static bool ocl_morph3x3_8UC1( InputArray _src, OutputArray _dst, InputArray _kernel, Point anchor,
int op, int actual_op = -1, InputArray _extraMat = noArray())
{
@ -1632,7 +1632,6 @@ static bool ocl_morphSmall( InputArray _src, OutputArray _dst, InputArray _kerne
return kernel.run(2, globalsize, NULL, false);
}
#endif
static bool ocl_morphOp(InputArray _src, OutputArray _dst, InputArray _kernel,
Point anchor, int iterations, int op, int borderType,
@ -1652,24 +1651,33 @@ static bool ocl_morphOp(InputArray _src, OutputArray _dst, InputArray _kernel,
if (kernel.empty())
{
kernel = getStructuringElement(MORPH_RECT, Size(1+iterations*2,1+iterations*2));
ksize = Size(1+iterations*2,1+iterations*2);
kernel = getStructuringElement(MORPH_RECT, ksize);
anchor = Point(iterations, iterations);
iterations = 1;
CV_DbgAssert(ksize == kernel.size());
}
else if( iterations > 1 && countNonZero(kernel) == kernel.rows*kernel.cols )
{
ksize = Size(ksize.width + (iterations-1)*(ksize.width-1),
ksize.height + (iterations-1)*(ksize.height-1));
anchor = Point(anchor.x*iterations, anchor.y*iterations);
kernel = getStructuringElement(MORPH_RECT,
Size(ksize.width + (iterations-1)*(ksize.width-1),
ksize.height + (iterations-1)*(ksize.height-1)),
anchor);
kernel = getStructuringElement(MORPH_RECT, ksize, anchor);
iterations = 1;
CV_DbgAssert(ksize == kernel.size());
}
static bool param_use_morph_special_kernels = utils::getConfigurationParameterBool("OPENCV_OPENCL_IMGPROC_MORPH_SPECIAL_KERNEL",
#ifndef __APPLE__
true
#else
false
#endif
);
int esz = CV_ELEM_SIZE(type);
// try to use OpenCL kernel adopted for small morph kernel
if (dev.isIntel() &&
if (param_use_morph_special_kernels && dev.isIntel() &&
((ksize.width < 5 && ksize.height < 5 && esz <= 4) ||
(ksize.width == 5 && ksize.height == 5 && cn == 1)) &&
(iterations == 1)
@ -1681,7 +1689,6 @@ static bool ocl_morphOp(InputArray _src, OutputArray _dst, InputArray _kernel,
if (ocl_morphSmall(_src, _dst, kernel, anchor, borderType, op, actual_op, _extraMat))
return true;
}
#endif
if (iterations == 0 || kernel.rows*kernel.cols == 1)
{

12
modules/imgproc/test/ocl/test_filters.cpp
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@ -442,7 +442,7 @@ OCL_TEST_P(Erode, Mat)
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
Mat kernel = ksize==0 ? Mat() : randomMat(kernelSize, CV_8UC1, 0, 3);
Mat kernel = ksize==0 ? Mat() : randomMat(kernelSize, CV_8UC1, 0, 2);
OCL_OFF(cv::erode(src_roi, dst_roi, kernel, Point(-1, -1), iterations) );
OCL_ON(cv::erode(usrc_roi, udst_roi, kernel, Point(-1, -1), iterations) );
@ -464,7 +464,7 @@ OCL_TEST_P(Dilate, Mat)
for (int j = 0; j < test_loop_times; j++)
{
random_roi();
Mat kernel = ksize==0 ? Mat() : randomMat(kernelSize, CV_8UC1, 0, 3);
Mat kernel = ksize==0 ? Mat() : randomMat(kernelSize, CV_8UC1, 0, 2);
OCL_OFF(cv::dilate(src_roi, dst_roi, kernel, Point(-1, -1), iterations) );
OCL_ON(cv::dilate(usrc_roi, udst_roi, kernel, Point(-1, -1), iterations) );
@ -728,19 +728,19 @@ OCL_INSTANTIATE_TEST_CASE_P(Filter, GaussianBlur_multicols, Combine(
OCL_INSTANTIATE_TEST_CASE_P(Filter, Erode, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4, CV_64FC1, CV_64FC4),
Values(0, 3, 5, 7), // kernel size, 0 means kernel = Mat()
Values(0, 5, 7, 9), // kernel size, 0 means kernel = Mat()
Values(Size(0, 0)), //not used
Values((BorderType)BORDER_CONSTANT),
Values(1.0, 2.0, 3.0),
Values(1.0, 2.0, 3.0, 4.0),
Bool(),
Values(1))); // not used
OCL_INSTANTIATE_TEST_CASE_P(Filter, Dilate, Combine(
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_32FC1, CV_32FC3, CV_32FC4, CV_64FC1, CV_64FC4),
Values(0, 3, 5, 7), // kernel size, 0 means kernel = Mat()
Values(0, 3, 5, 7, 9), // kernel size, 0 means kernel = Mat()
Values(Size(0, 0)), // not used
Values((BorderType)BORDER_CONSTANT),
Values(1.0, 2.0, 3.0),
Values(1.0, 2.0, 3.0, 4.0),
Bool(),
Values(1))); // not used