/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // Intel License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of Intel Corporation may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "test_precomp.hpp" #include #include #include using namespace cv; namespace internal { void __wrap_printf_func(const char* fmt, ...) { va_list args; va_start(args, fmt); char buffer[256]; vsprintf (buffer, fmt, args); cvtest::TS::ptr()->printf(cvtest::TS::SUMMARY, buffer); va_end(args); } #define PRINT_TO_LOG __wrap_printf_func } using internal::PRINT_TO_LOG; #define SHOW_IMAGE #undef SHOW_IMAGE //////////////////////////////////////////////////////////////////////////////////////////////////////// // ImageWarpBaseTest //////////////////////////////////////////////////////////////////////////////////////////////////////// class CV_ImageWarpBaseTest : public cvtest::BaseTest { public: enum { cell_size = 10 }; CV_ImageWarpBaseTest(); virtual ~CV_ImageWarpBaseTest(); virtual void run(int); protected: virtual void generate_test_data(); virtual void run_func() = 0; virtual void run_reference_func() = 0; virtual void validate_results() const; virtual void prepare_test_data_for_reference_func(); Size randSize(RNG& rng) const; const char* interpolation_to_string(int inter_type) const; int interpolation; Mat src; Mat dst; Mat reference_dst; }; CV_ImageWarpBaseTest::CV_ImageWarpBaseTest() : BaseTest(), interpolation(-1), src(), dst(), reference_dst() { test_case_count = 40; ts->set_failed_test_info(cvtest::TS::OK); } CV_ImageWarpBaseTest::~CV_ImageWarpBaseTest() { } const char* CV_ImageWarpBaseTest::interpolation_to_string(int inter) const { if (inter == INTER_NEAREST) return "INTER_NEAREST"; if (inter == INTER_LINEAR) return "INTER_LINEAR"; if (inter == INTER_AREA) return "INTER_AREA"; if (inter == INTER_CUBIC) return "INTER_CUBIC"; if (inter == INTER_LANCZOS4) return "INTER_LANCZOS4"; if (inter == INTER_LANCZOS4 + 1) return "INTER_AREA_FAST"; return "Unsupported/Unkown interpolation type"; } Size CV_ImageWarpBaseTest::randSize(RNG& rng) const { Size size; size.width = saturate_cast(std::exp(rng.uniform(1.0f, 7.0f))); size.height = saturate_cast(std::exp(rng.uniform(1.0f, 7.0f))); return size; } void CV_ImageWarpBaseTest::generate_test_data() { RNG& rng = ts->get_rng(); // generating the src matrix structure Size ssize = randSize(rng), dsize; int depth = rng.uniform(0, CV_64F); while (depth == CV_8S || depth == CV_32S) depth = rng.uniform(0, CV_64F); int cn = rng.uniform(1, 4); while (cn == 2) cn = rng.uniform(1, 4); src.create(ssize, CV_MAKE_TYPE(depth, cn)); // generating the src matrix int x, y; if (cvtest::randInt(rng) % 2) { for (y = 0; y < ssize.height; y += cell_size) for (x = 0; x < ssize.width; x += cell_size) rectangle(src, Point(x, y), Point(x + std::min(cell_size, ssize.width - x), y + std::min(cell_size, ssize.height - y)), Scalar::all((x + y) % 2 ? 255: 0), CV_FILLED); } else { src = Scalar::all(255); for (y = cell_size; y < src.rows; y += cell_size) line(src, Point2i(0, y), Point2i(src.cols, y), Scalar::all(0), 1); for (x = cell_size; x < src.cols; x += cell_size) line(src, Point2i(x, 0), Point2i(x, src.rows), Scalar::all(0), 1); } // generating an interpolation type interpolation = rng.uniform(0, CV_INTER_LANCZOS4 + 1); // generating the dst matrix structure double scale_x = 2, scale_y = 2; if (interpolation == INTER_AREA) { bool area_fast = rng.uniform(0., 1.) > 0.5; if (area_fast) { scale_x = rng.uniform(2, 5); scale_y = rng.uniform(2, 5); } else { scale_x = rng.uniform(1.0, 3.0); scale_y = rng.uniform(1.0, 3.0); } } else { scale_x = rng.uniform(0.4, 4.0); scale_y = rng.uniform(0.4, 4.0); } CV_Assert(scale_x > 0.0f && scale_y > 0.0f); dsize.width = saturate_cast((ssize.width + scale_x - 1) / scale_x); dsize.height = saturate_cast((ssize.height + scale_y - 1) / scale_y); dst = Mat::zeros(dsize, src.type()); reference_dst = Mat::zeros(dst.size(), CV_MAKE_TYPE(CV_32F, dst.channels())); if (interpolation == INTER_AREA && (scale_x < 1.0 || scale_y < 1.0)) interpolation = INTER_LINEAR; } void CV_ImageWarpBaseTest::run(int) { for (int i = 0; i < test_case_count; ++i) { generate_test_data(); run_func(); run_reference_func(); if (ts->get_err_code() < 0) break; validate_results(); if (ts->get_err_code() < 0) break; ts->update_context(this, i, true); } ts->set_gtest_status(); } void CV_ImageWarpBaseTest::validate_results() const { Mat _dst; dst.convertTo(_dst, reference_dst.depth()); Size dsize = dst.size(), ssize = src.size(); int cn = _dst.channels(); dsize.width *= cn; float t = 1.0f; if (interpolation == INTER_CUBIC) t = 1.0f; else if (interpolation == INTER_LANCZOS4) t = 1.0f; else if (interpolation == INTER_NEAREST) t = 1.0f; else if (interpolation == INTER_AREA) t = 2.0f; for (int dy = 0; dy < dsize.height; ++dy) { const float* rD = reference_dst.ptr(dy); const float* D = _dst.ptr(dy); for (int dx = 0; dx < dsize.width; ++dx) if (fabs(rD[dx] - D[dx]) > t && // fabs(rD[dx] - D[dx]) < 250.0f && rD[dx] <= 255.0f && D[dx] <= 255.0f && rD[dx] >= 0.0f && D[dx] >= 0.0f) { PRINT_TO_LOG("\nNorm of the difference: %lf\n", norm(reference_dst, _dst, NORM_INF)); PRINT_TO_LOG("Error in (dx, dy): (%d, %d)\n", dx / cn + 1, dy + 1); PRINT_TO_LOG("Tuple (rD, D): (%f, %f)\n", rD[dx], D[dx]); PRINT_TO_LOG("Dsize: (%d, %d)\n", dsize.width / cn, dsize.height); PRINT_TO_LOG("Ssize: (%d, %d)\n", src.cols, src.rows); float scale_x = static_cast(ssize.width) / dsize.width, scale_y = static_cast(ssize.height) / dsize.height; PRINT_TO_LOG("Interpolation: %s\n", interpolation_to_string(interpolation == INTER_AREA && fabs(scale_x - cvRound(scale_x)) < FLT_EPSILON && fabs(scale_y - cvRound(scale_y)) < FLT_EPSILON ? INTER_LANCZOS4 + 1 : interpolation)); PRINT_TO_LOG("Scale (x, y): (%lf, %lf)\n", scale_x, scale_y); PRINT_TO_LOG("Elemsize: %d\n", src.elemSize1()); PRINT_TO_LOG("Channels: %d\n", cn); #ifdef SHOW_IMAGE const std::string w1("OpenCV impl (run func)"), w2("Reference func"), w3("Src image"), w4("Diff"); namedWindow(w1, CV_WINDOW_KEEPRATIO); namedWindow(w2, CV_WINDOW_KEEPRATIO); namedWindow(w3, CV_WINDOW_KEEPRATIO); namedWindow(w4, CV_WINDOW_KEEPRATIO); Mat diff; absdiff(reference_dst, _dst, diff); imshow(w1, dst); imshow(w2, reference_dst); imshow(w3, src); imshow(w4, diff); waitKey(); #endif const int radius = 3; int rmin = MAX(dy - radius, 0), rmax = MIN(dy + radius, dsize.height); int cmin = MAX(dx / cn - radius, 0), cmax = MIN(dx / cn + radius, dsize.width); std::cout << "opencv result:\n" << dst(Range(rmin, rmax), Range(cmin, cmax)) << std::endl; std::cout << "reference result:\n" << reference_dst(Range(rmin, rmax), Range(cmin, cmax)) << std::endl; ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY); return; } } } void CV_ImageWarpBaseTest::prepare_test_data_for_reference_func() { if (src.depth() != CV_32F) { Mat tmp; src.convertTo(tmp, CV_32F); src = tmp; } } //////////////////////////////////////////////////////////////////////////////////////////////////////// // Resize //////////////////////////////////////////////////////////////////////////////////////////////////////// class CV_Resize_Test : public CV_ImageWarpBaseTest { public: CV_Resize_Test(); virtual ~CV_Resize_Test(); protected: virtual void generate_test_data(); virtual void run_func(); virtual void run_reference_func(); private: double scale_x; double scale_y; bool area_fast; void resize_generic(); void resize_area(); double getWeight(double a, double b, int x); typedef std::vector > dim; void generate_buffer(double scale, dim& _dim); void resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _dim); }; CV_Resize_Test::CV_Resize_Test() : CV_ImageWarpBaseTest(), scale_x(), scale_y(), area_fast(false) { } CV_Resize_Test::~CV_Resize_Test() { } namespace internal { void interpolateLinear(float x, float* coeffs) { coeffs[0] = 1.f - x; coeffs[1] = x; } void interpolateCubic(float x, float* coeffs) { const float A = -0.75f; coeffs[0] = ((A*(x + 1) - 5*A)*(x + 1) + 8*A)*(x + 1) - 4*A; coeffs[1] = ((A + 2)*x - (A + 3))*x*x + 1; coeffs[2] = ((A + 2)*(1 - x) - (A + 3))*(1 - x)*(1 - x) + 1; coeffs[3] = 1.f - coeffs[0] - coeffs[1] - coeffs[2]; } void interpolateLanczos4(float x, float* coeffs) { static const double s45 = 0.70710678118654752440084436210485; static const double cs[][2]= {{1, 0}, {-s45, -s45}, {0, 1}, {s45, -s45}, {-1, 0}, {s45, s45}, {0, -1}, {-s45, s45}}; if( x < FLT_EPSILON ) { for( int i = 0; i < 8; i++ ) coeffs[i] = 0; coeffs[3] = 1; return; } float sum = 0; double y0=-(x+3)*CV_PI*0.25, s0 = sin(y0), c0=cos(y0); for(int i = 0; i < 8; i++ ) { double y = -(x+3-i)*CV_PI*0.25; coeffs[i] = (float)((cs[i][0]*s0 + cs[i][1]*c0)/(y*y)); sum += coeffs[i]; } sum = 1.f/sum; for(int i = 0; i < 8; i++ ) coeffs[i] *= sum; } typedef void (*interpolate_method)(float x, float* coeffs); interpolate_method inter_array[] = { &interpolateLinear, &interpolateCubic, &interpolateLanczos4 }; } void CV_Resize_Test::generate_test_data() { CV_ImageWarpBaseTest::generate_test_data(); scale_x = src.cols / static_cast(dst.cols); scale_y = src.rows / static_cast(dst.rows); area_fast = interpolation == INTER_AREA && fabs(scale_x - cvRound(scale_x)) < FLT_EPSILON && fabs(scale_y - cvRound(scale_y)) < FLT_EPSILON; if (area_fast) { scale_x = cvRound(scale_x); scale_y = cvRound(scale_y); } } void CV_Resize_Test::run_func() { cv::resize(src, dst, dst.size(), 0, 0, interpolation); } void CV_Resize_Test::run_reference_func() { CV_ImageWarpBaseTest::prepare_test_data_for_reference_func(); if (interpolation == INTER_AREA) resize_area(); else resize_generic(); } double CV_Resize_Test::getWeight(double a, double b, int x) { float w = std::min(x + 1, b) - std::max(x, a); CV_Assert(w >= 0); return w; } void CV_Resize_Test::resize_area() { Size ssize = src.size(), dsize = reference_dst.size(); CV_Assert(ssize.area() > 0 && dsize.area() > 0); int cn = src.channels(); CV_Assert(scale_x >= 1.0 && scale_y >= 1.0); double fsy0 = 0, fsy1 = scale_y; for (int dy = 0; dy < dsize.height; ++dy) { float* yD = reference_dst.ptr(dy); int isy0 = cvFloor(fsy0), isy1 = std::min(cvFloor(fsy1), ssize.height - 1); CV_Assert(isy1 <= ssize.height && isy0 < ssize.height); float fsx0 = 0, fsx1 = scale_x; for (int dx = 0; dx < dsize.width; ++dx) { float* xyD = yD + cn * dx; int isx0 = cvFloor(fsx0), isx1 = std::min(ssize.width - 1, cvFloor(fsx1)); CV_Assert(isx1 <= ssize.width); CV_Assert(isx0 < ssize.width); // for each pixel of dst for (int r = 0; r < cn; ++r) { xyD[r] = 0.0f; double area = 0.0; for (int sy = isy0; sy <= isy1; ++sy) { const float* yS = src.ptr(sy); for (int sx = isx0; sx <= isx1; ++sx) { double wy = getWeight(fsy0, fsy1, sy); double wx = getWeight(fsx0, fsx1, sx); double w = wx * wy; xyD[r] += yS[sx * cn + r] * w; area += w; } } CV_Assert(area != 0); // norming pixel xyD[r] /= area; } fsx1 = std::min((fsx0 = fsx1) + scale_x, ssize.width); } fsy1 = std::min((fsy0 = fsy1) + scale_y, ssize.height); } } // for interpolation type : INTER_LINEAR, INTER_LINEAR, INTER_CUBIC, INTER_LANCZOS4 void CV_Resize_Test::resize_1d(const Mat& _src, Mat& _dst, int dy, const dim& _dim) { Size dsize = _dst.size(); int cn = _dst.channels(); float* yD = _dst.ptr(dy); if (interpolation == INTER_NEAREST) { const float* yS = _src.ptr(dy); for (int dx = 0; dx < dsize.width; ++dx) { int isx = _dim[dx].first; const float* xyS = yS + isx * cn; float* xyD = yD + dx * cn; for (int r = 0; r < cn; ++r) xyD[r] = xyS[r]; } } else if (interpolation == INTER_LINEAR || interpolation == INTER_CUBIC || interpolation == INTER_LANCZOS4) { internal::interpolate_method inter_func = internal::inter_array[interpolation - (interpolation == INTER_LANCZOS4 ? 2 : 1)]; int elemsize = _src.elemSize(); int ofs = 0, ksize = 2; if (interpolation == INTER_CUBIC) ofs = 1, ksize = 4; else if (interpolation == INTER_LANCZOS4) ofs = 3, ksize = 8; Mat _extended_src_row(1, _src.cols + ksize * 2, _src.type()); uchar* srow = _src.data + dy * _src.step; memcpy(_extended_src_row.data + elemsize * ksize, srow, _src.step); for (int k = 0; k < ksize; ++k) { memcpy(_extended_src_row.data + k * elemsize, srow, elemsize); memcpy(_extended_src_row.data + (ksize + k) * elemsize + _src.step, srow + _src.step - elemsize, elemsize); } for (int dx = 0; dx < dsize.width; ++dx) { int isx = _dim[dx].first; double fsx = _dim[dx].second; float *xyD = yD + dx * cn; const float* xyS = _extended_src_row.ptr(0) + (isx + ksize - ofs) * cn; float w[ksize]; inter_func(fsx, w); for (int r = 0; r < cn; ++r) { xyD[r] = 0; for (int k = 0; k < ksize; ++k) xyD[r] += w[k] * xyS[k * cn + r]; xyD[r] = xyD[r]; } } } else CV_Assert(0); } void CV_Resize_Test::generate_buffer(double scale, dim& _dim) { int length = _dim.size(); for (int dx = 0; dx < length; ++dx) { double fsx = scale * (dx + 0.5f) - 0.5f; int isx = cvFloor(fsx); _dim[dx] = std::make_pair(isx, fsx - isx); } } void CV_Resize_Test::resize_generic() { Size dsize = reference_dst.size(), ssize = src.size(); CV_Assert(dsize.area() > 0 && ssize.area() > 0); dim dims[] = { dim(dsize.width), dim(dsize.height) }; if (interpolation == INTER_NEAREST) { for (int dx = 0; dx < dsize.width; ++dx) dims[0][dx].first = std::min(cvFloor(dx * scale_x), ssize.width - 1); for (int dy = 0; dy < dsize.height; ++dy) dims[1][dy].first = std::min(cvFloor(dy * scale_y), ssize.height - 1); } else { generate_buffer(scale_x, dims[0]); generate_buffer(scale_y, dims[1]); } Mat tmp(ssize.height, dsize.width, reference_dst.type()); for (int dy = 0; dy < tmp.rows; ++dy) resize_1d(src, tmp, dy, dims[0]); transpose(tmp, tmp); transpose(reference_dst, reference_dst); for (int dy = 0; dy < tmp.rows; ++dy) resize_1d(tmp, reference_dst, dy, dims[1]); transpose(reference_dst, reference_dst); } //////////////////////////////////////////////////////////////////////////////////////////////////////// // remap //////////////////////////////////////////////////////////////////////////////////////////////////////// class CV_Remap_Test : public CV_ImageWarpBaseTest { public: CV_Remap_Test(); virtual ~CV_Remap_Test(); private: typedef void (CV_Remap_Test::*remap_func)(const Mat&, Mat&); protected: virtual void generate_test_data(); virtual void prepare_test_data_for_reference_func(); virtual void run_func(); virtual void run_reference_func(); Mat mapx, mapy; int borderType; Scalar borderValue; remap_func funcs[2]; private: void remap_nearest(const Mat&, Mat&); void remap_generic(const Mat&, Mat&); void convert_maps(); const char* borderType_to_string() const; virtual void validate_results() const; }; CV_Remap_Test::CV_Remap_Test() : CV_ImageWarpBaseTest(), mapx(), mapy(), borderType(-1), borderValue() { funcs[0] = &CV_Remap_Test::remap_nearest; funcs[1] = &CV_Remap_Test::remap_generic; } CV_Remap_Test::~CV_Remap_Test() { } void CV_Remap_Test::generate_test_data() { CV_ImageWarpBaseTest::generate_test_data(); RNG& rng = ts->get_rng(); borderType = rng.uniform(1, BORDER_WRAP); borderValue = Scalar::all(rng.uniform(0, 255)); // generating the mapx, mapy matrices static const int mapx_types[] = { CV_16SC2, CV_32FC1, CV_32FC2 }; mapx.create(dst.size(), mapx_types[rng.uniform(0, sizeof(mapx_types) / sizeof(int))]); mapy = Mat(); const int n = std::min(std::min(src.cols, src.rows) / 10 + 1, 2); float _n = 0; //static_cast(-n); switch (mapx.type()) { case CV_16SC2: { MatIterator_ begin_x = mapx.begin(), end_x = mapx.end(); for ( ; begin_x != end_x; ++begin_x) { begin_x[0] = rng.uniform(static_cast(_n), std::max(src.cols + n - 1, 0)); begin_x[1] = rng.uniform(static_cast(_n), std::max(src.rows + n - 1, 0)); } if (interpolation != INTER_NEAREST) { static const int mapy_types[] = { CV_16UC1, CV_16SC1 }; mapy.create(dst.size(), mapy_types[rng.uniform(0, sizeof(mapy_types) / sizeof(int))]); switch (mapy.type()) { case CV_16UC1: { MatIterator_ begin_y = mapy.begin(), end_y = mapy.end(); for ( ; begin_y != end_y; ++begin_y) begin_y[0] = rng.uniform(0, 1024); } break; case CV_16SC1: { MatIterator_ begin_y = mapy.begin(), end_y = mapy.end(); for ( ; begin_y != end_y; ++begin_y) begin_y[0] = rng.uniform(0, 1024); } break; } } } break; case CV_32FC1: { mapy.create(dst.size(), CV_32FC1); float fscols = static_cast(std::max(src.cols - 1 + n, 0)), fsrows = static_cast(std::max(src.rows - 1 + n, 0)); MatIterator_ begin_x = mapx.begin(), end_x = mapx.end(); MatIterator_ begin_y = mapy.begin(); for ( ; begin_x != end_x; ++begin_x, ++begin_y) { begin_x[0] = rng.uniform(_n, fscols); begin_y[0] = rng.uniform(_n, fsrows); } } break; case CV_32FC2: { MatIterator_ begin_x = mapx.begin(), end_x = mapx.end(); float fscols = static_cast(std::max(src.cols - 1 + n, 0)), fsrows = static_cast(std::max(src.rows - 1 + n, 0)); for ( ; begin_x != end_x; ++begin_x) { begin_x[0] = rng.uniform(_n, fscols); begin_x[1] = rng.uniform(_n, fsrows); } } break; default: assert(0); break; } } void CV_Remap_Test::run_func() { remap(src, dst, mapx, mapy, interpolation, borderType, borderValue); } void CV_Remap_Test::convert_maps() { if (mapx.type() != CV_16SC2) convertMaps(mapx.clone(), mapy.clone(), mapx, mapy, CV_16SC2, interpolation == INTER_NEAREST); else if (interpolation != INTER_NEAREST) if (mapy.type() != CV_16UC1) mapy.clone().convertTo(mapy, CV_16UC1); if (interpolation == INTER_NEAREST) mapy = Mat(); CV_Assert(( (interpolation == INTER_NEAREST && !mapy.data) || mapy.type() == CV_16UC1 || mapy.type() == CV_16SC1) && mapx.type() == CV_16SC2); } const char* CV_Remap_Test::borderType_to_string() const { if (borderType == BORDER_CONSTANT) return "BORDER_CONSTANT"; if (borderType == BORDER_REPLICATE) return "BORDER_REPLICATE"; if (borderType == BORDER_REFLECT) return "BORDER_REFLECT"; return "Unsupported/Unkown border type"; } void CV_Remap_Test::prepare_test_data_for_reference_func() { CV_ImageWarpBaseTest::prepare_test_data_for_reference_func(); convert_maps(); /* const int ksize = 3; Mat kernel = getStructuringElement(CV_MOP_ERODE, Size(ksize, ksize)); Mat mask(src.size(), CV_8UC1, Scalar::all(255)), dst_mask; cv::erode(src, erode_src, kernel); cv::erode(mask, dst_mask, kernel, Point(-1, -1), 1, BORDER_CONSTANT, Scalar::all(0)); bitwise_not(dst_mask, mask); src.copyTo(erode_src, mask); dst_mask.release(); mask = Scalar::all(0); kernel = getStructuringElement(CV_MOP_DILATE, kernel.size()); cv::dilate(src, dilate_src, kernel); cv::dilate(mask, dst_mask, kernel, Point(-1, -1), 1, BORDER_CONSTANT, Scalar::all(255)); src.copyTo(dilate_src, dst_mask); dst_mask.release(); */ } void CV_Remap_Test::run_reference_func() { prepare_test_data_for_reference_func(); if (interpolation == INTER_AREA) interpolation = INTER_LINEAR; int index = interpolation == INTER_NEAREST ? 0 : 1; (this->*funcs[index])(src, reference_dst); } void CV_Remap_Test::remap_nearest(const Mat& _src, Mat& _dst) { CV_Assert(_src.depth() == CV_32F && _dst.type() == _src.type()); CV_Assert(mapx.type() == CV_16SC2 && !mapy.data); Size ssize = _src.size(), dsize = _dst.size(); CV_Assert(ssize.area() > 0 && dsize.area() > 0); int cn = _src.channels(); for (int dy = 0; dy < dsize.height; ++dy) { const short* yM = mapx.ptr(dy); float* yD = _dst.ptr(dy); for (int dx = 0; dx < dsize.width; ++dx) { float* xyD = yD + cn * dx; int sx = yM[dx * 2], sy = yM[dx * 2 + 1]; if (sx >= 0 && sx < ssize.width && sy >= 0 && sy < ssize.height) { const float *xyS = _src.ptr(sy) + sx * cn; for (int r = 0; r < cn; ++r) xyD[r] = xyS[r]; } else if (borderType != BORDER_TRANSPARENT) { if (borderType == BORDER_CONSTANT) for (int r = 0; r < cn; ++r) xyD[r] = borderValue[r]; else { sx = borderInterpolate(sx, ssize.width, borderType); sy = borderInterpolate(sy, ssize.height, borderType); CV_Assert(sx >= 0 && sy >= 0 && sx < ssize.width && sy < ssize.height); const float *xyS = _src.ptr(sy) + sx * cn; for (int r = 0; r < cn; ++r) xyD[r] = xyS[r]; } } } } } void CV_Remap_Test::remap_generic(const Mat& _src, Mat& _dst) { CV_Assert(mapx.type() == CV_16SC2 && mapy.type() == CV_16UC1); int ksize; if (interpolation == INTER_LINEAR) ksize = 2; else if (interpolation == INTER_CUBIC) ksize = 4; else if (interpolation == INTER_LANCZOS4) ksize = 8; else ksize = 0; assert(ksize); int ofs = (ksize / 2) - 1; CV_Assert(_src.depth() == CV_32F && _dst.type() == _src.type()); Size ssize = _src.size(), dsize = _dst.size(); int cn = _src.channels(), width1 = std::max(ssize.width - ksize + 1, 0), height1 = std::max(ssize.height - ksize + 1, 0); float ix[8], w[16]; internal::interpolate_method inter_func = internal::inter_array[interpolation - (interpolation == INTER_LANCZOS4 ? 2 : 1)]; for (int dy = 0; dy < dsize.height; ++dy) { const short* yMx = mapx.ptr(dy); const ushort* yMy = mapy.ptr(dy); float* yD = _dst.ptr(dy); for (int dx = 0; dx < dsize.width; ++dx) { float* xyD = yD + dx * cn; float sx = yMx[dx * 2], sy = yMx[dx * 2 + 1]; int isx = cvFloor(sx), isy = cvFloor(sy); inter_func((yMy[dx] & (INTER_TAB_SIZE - 1)) / static_cast(INTER_TAB_SIZE), w); inter_func(((yMy[dx] >> INTER_BITS) & (INTER_TAB_SIZE - 1)) / static_cast(INTER_TAB_SIZE), w + ksize); isx -= ofs; isy -= ofs; if (isx >= 0 && isx < width1 && isy >= 0 && isy < height1) { for (int r = 0; r < cn; ++r) { for (int y = 0; y < ksize; ++y) { const float* xyS = _src.ptr(isy + y) + isx * cn; ix[y] = 0; for (int i = 0; i < ksize; ++i) ix[y] += w[i] * xyS[i * cn + r]; } xyD[r] = 0; for (int i = 0; i < ksize; ++i) xyD[r] += w[ksize + i] * ix[i]; } } else if (borderType != BORDER_TRANSPARENT) { int ar_x[8], ar_y[8]; for (int k = 0; k < ksize; k++) { ar_x[k] = borderInterpolate(isx + k, ssize.width, borderType) * cn; ar_y[k] = borderInterpolate(isy + k, ssize.height, borderType); } for (int r = 0; r < cn; r++) { xyD[r] = 0; for (int i = 0; i < ksize; ++i) { ix[i] = 0; if (ar_y[i] >= 0) { const float* yS = _src.ptr(ar_y[i]); for (int j = 0; j < ksize; ++j) ix[i] += (ar_x[j] >= 0 ? yS[ar_x[j] + r] : borderValue[r]) * w[j]; } else for (int j = 0; j < ksize; ++j) ix[i] += borderValue[r] * w[j]; } for (int i = 0; i < ksize; ++i) xyD[r] += w[ksize + i] * ix[i]; } } } } } void CV_Remap_Test::validate_results() const { CV_ImageWarpBaseTest::validate_results(); if (cvtest::TS::ptr()->get_err_code() == cvtest::TS::FAIL_BAD_ACCURACY) { PRINT_TO_LOG("BorderType: %s\n", borderType_to_string()); PRINT_TO_LOG("BorderValue: (%f, %f, %f, %f)\n", borderValue[0], borderValue[1], borderValue[2], borderValue[3]); } } //////////////////////////////////////////////////////////////////////////////////////////////////////// // warpAffine //////////////////////////////////////////////////////////////////////////////////////////////////////// class CV_WarpAffine_Test : public CV_Remap_Test { public: CV_WarpAffine_Test(); virtual ~CV_WarpAffine_Test(); protected: virtual void generate_test_data(); virtual void prepare_test_data_for_reference_func(); virtual void run_func(); virtual void run_reference_func(); Mat M; private: void warpAffine(const Mat&, Mat&); }; CV_WarpAffine_Test::CV_WarpAffine_Test() : CV_Remap_Test() { } CV_WarpAffine_Test::~CV_WarpAffine_Test() { } void CV_WarpAffine_Test::generate_test_data() { CV_Remap_Test::generate_test_data(); RNG& rng = ts->get_rng(); // generating the M 2x3 matrix static const int depths[] = { CV_32FC1, CV_64FC1 }; // generating 2d matrix M = getRotationMatrix2D(Point2f(src.cols / 2.f, src.rows / 2.f), rng.uniform(-180.f, 180.f), rng.uniform(0.4f, 2.0f)); int depth = depths[rng.uniform(0, sizeof(depths) / sizeof(depths[0]))]; if (M.depth() != depth) { Mat tmp; M.convertTo(tmp, depth); M = tmp; } // warp_matrix is inverse if (rng.uniform(0., 1.) > 0) interpolation |= CV_WARP_INVERSE_MAP; } void CV_WarpAffine_Test::run_func() { cv::warpAffine(src, dst, M, dst.size(), interpolation, borderType, borderValue); } void CV_WarpAffine_Test::prepare_test_data_for_reference_func() { CV_ImageWarpBaseTest::prepare_test_data_for_reference_func(); } void CV_WarpAffine_Test::run_reference_func() { prepare_test_data_for_reference_func(); warpAffine(src, reference_dst); } void CV_WarpAffine_Test::warpAffine(const Mat& _src, Mat& _dst) { Size dsize = _dst.size(); CV_Assert(_src.size().area() > 0); CV_Assert(dsize.area() > 0); CV_Assert(_src.type() == _dst.type()); Mat tM; M.convertTo(tM, CV_64F); int inter = interpolation & INTER_MAX; if (inter == INTER_AREA) inter = INTER_LINEAR; mapx.create(dsize, CV_16SC2); if (inter != INTER_NEAREST) mapy.create(dsize, CV_16SC1); else mapy = Mat(); if (!(interpolation & CV_WARP_INVERSE_MAP)) invertAffineTransform(tM.clone(), tM); const int AB_BITS = MAX(10, (int)INTER_BITS); const int AB_SCALE = 1 << AB_BITS; int round_delta = (inter == INTER_NEAREST) ? AB_SCALE / 2 : (AB_SCALE / INTER_TAB_SIZE / 2); const double* data_tM = tM.ptr(0); for (int dy = 0; dy < dsize.height; ++dy) { short* yM = mapx.ptr(dy); for (int dx = 0; dx < dsize.width; ++dx, yM += 2) { int v1 = saturate_cast(saturate_cast(data_tM[0] * dx * AB_SCALE) + saturate_cast((data_tM[1] * dy + data_tM[2]) * AB_SCALE) + round_delta), v2 = saturate_cast(saturate_cast(data_tM[3] * dx * AB_SCALE) + saturate_cast((data_tM[4] * dy + data_tM[5]) * AB_SCALE) + round_delta); v1 >>= AB_BITS - INTER_BITS; v2 >>= AB_BITS - INTER_BITS; yM[0] = saturate_cast(v1 >> INTER_BITS); yM[1] = saturate_cast(v2 >> INTER_BITS); if (inter != INTER_NEAREST) mapy.ptr(dy)[dx] = ((v2 & (INTER_TAB_SIZE - 1)) * INTER_TAB_SIZE + (v1 & (INTER_TAB_SIZE - 1))); } } CV_Assert(mapx.type() == CV_16SC2 && ((inter == INTER_NEAREST && !mapy.data) || mapy.type() == CV_16SC1)); cv::remap(_src, _dst, mapx, mapy, inter, borderType, borderValue); } //////////////////////////////////////////////////////////////////////////////////////////////////////// // warpPerspective //////////////////////////////////////////////////////////////////////////////////////////////////////// class CV_WarpPerspective_Test : public CV_WarpAffine_Test { public: CV_WarpPerspective_Test(); virtual ~CV_WarpPerspective_Test(); protected: virtual void generate_test_data(); virtual void run_func(); virtual void run_reference_func(); private: void warpPerspective(const Mat&, Mat&); }; CV_WarpPerspective_Test::CV_WarpPerspective_Test() : CV_WarpAffine_Test() { } CV_WarpPerspective_Test::~CV_WarpPerspective_Test() { } void CV_WarpPerspective_Test::generate_test_data() { CV_Remap_Test::generate_test_data(); // generating the M 3x3 matrix RNG& rng = ts->get_rng(); Point2f sp[] = { Point2f(0, 0), Point2f(src.cols, 0), Point2f(0, src.rows), Point2f(src.cols, src.rows) }; Point2f dp[] = { Point2f(rng.uniform(0, src.cols), rng.uniform(0, src.rows)), Point2f(rng.uniform(0, src.cols), rng.uniform(0, src.rows)), Point2f(rng.uniform(0, src.cols), rng.uniform(0, src.rows)), Point2f(rng.uniform(0, src.cols), rng.uniform(0, src.rows)) }; M = getPerspectiveTransform(sp, dp); static const int depths[] = { CV_32F, CV_64F }; int depth = depths[rng.uniform(0, 2)]; M.clone().convertTo(M, depth); } void CV_WarpPerspective_Test::run_func() { cv::warpPerspective(src, dst, M, dst.size(), interpolation, borderType, borderValue); } void CV_WarpPerspective_Test::run_reference_func() { prepare_test_data_for_reference_func(); warpPerspective(src, reference_dst); } void CV_WarpPerspective_Test::warpPerspective(const Mat& _src, Mat& _dst) { Size ssize = _src.size(), dsize = _dst.size(); CV_Assert(ssize.area() > 0); CV_Assert(dsize.area() > 0); CV_Assert(_src.type() == _dst.type()); if (M.depth() != CV_64F) { Mat tmp; M.convertTo(tmp, CV_64F); M = tmp; } if (!(interpolation & CV_WARP_INVERSE_MAP)) { Mat tmp; invert(M, tmp); M = tmp; } int inter = interpolation & INTER_MAX; if (inter == INTER_AREA) inter = INTER_LINEAR; mapx.create(dsize, CV_16SC2); if (inter != INTER_NEAREST) mapy.create(dsize, CV_16SC1); else mapy = Mat(); double* tM = M.ptr(0); for (int dy = 0; dy < dsize.height; ++dy) { short* yMx = mapx.ptr(dy); for (int dx = 0; dx < dsize.width; ++dx, yMx += 2) { double den = tM[6] * dx + tM[7] * dy + tM[8]; den = den ? 1.0 / den : 0.0; if (inter == INTER_NEAREST) { yMx[0] = saturate_cast((tM[0] * dx + tM[1] * dy + tM[2]) * den); yMx[1] = saturate_cast((tM[3] * dx + tM[4] * dy + tM[5]) * den); continue; } den *= INTER_TAB_SIZE; int v0 = saturate_cast((tM[0] * dx + tM[1] * dy + tM[2]) * den); int v1 = saturate_cast((tM[3] * dx + tM[4] * dy + tM[5]) * den); yMx[0] = saturate_cast(v0 >> INTER_BITS); yMx[1] = saturate_cast(v1 >> INTER_BITS); mapy.ptr(dy)[dx] = saturate_cast((v1 & (INTER_TAB_SIZE - 1)) * INTER_TAB_SIZE + (v0 & (INTER_TAB_SIZE - 1))); } } CV_Assert(mapx.type() == CV_16SC2 && ((inter == INTER_NEAREST && !mapy.data) || mapy.type() == CV_16SC1)); cv::remap(_src, _dst, mapx, mapy, inter, borderType, borderValue); } //////////////////////////////////////////////////////////////////////////////////////////////////////// // Tests //////////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Imgproc_Resize_Test, accuracy) { CV_Resize_Test test; test.safe_run(); } TEST(Imgproc_Remap_Test, accuracy) { CV_Remap_Test test; test.safe_run(); } TEST(Imgproc_WarpAffine_Test, accuracy) { CV_WarpAffine_Test test; test.safe_run(); } TEST(Imgproc_WarpPerspective_Test, accuracy) { CV_WarpPerspective_Test test; test.safe_run(); }