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Open Source Computer Vision Library
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243 lines
11 KiB
243 lines
11 KiB
// This file is part of OpenCV project. |
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// It is subject to the license terms in the LICENSE file found in the top-level directory |
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// of this distribution and at http://opencv.org/license.html. |
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#include "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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static const int fixedShiftU8 = 8; |
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template <typename T, int fixedShift> |
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void eval4(int64_t xcoeff0, int64_t xcoeff1, int64_t ycoeff0, int64_t ycoeff1, int cn, |
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uint8_t* src_pt00, uint8_t* src_pt01, uint8_t* src_pt10, uint8_t* src_pt11, uint8_t* dst_pt) |
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{ |
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static const int64_t fixedRound = ((1LL << (fixedShift * 2)) >> 1); |
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int64_t val = (((T*)src_pt00)[cn] * xcoeff0 + ((T*)src_pt01)[cn] * xcoeff1) * ycoeff0 + |
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(((T*)src_pt10)[cn] * xcoeff0 + ((T*)src_pt11)[cn] * xcoeff1) * ycoeff1 ; |
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((T*)dst_pt)[cn] = saturate_cast<T>((val + fixedRound) >> (fixedShift * 2)); |
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} |
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TEST(Resize_Bitexact, Linear8U) |
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{ |
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static const int64_t fixedOne = (1L << fixedShiftU8); |
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struct testmode |
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{ |
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int type; |
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Size sz; |
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} modes[] = { |
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{ CV_8UC1, Size( 512, 768) }, // 1/2 1 |
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{ CV_8UC3, Size( 512, 768) }, |
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{ CV_8UC1, Size(1024, 384) }, // 1 1/2 |
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{ CV_8UC4, Size(1024, 384) }, |
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{ CV_8UC1, Size( 512, 384) }, // 1/2 1/2 |
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{ CV_8UC2, Size( 512, 384) }, |
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{ CV_8UC3, Size( 512, 384) }, |
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{ CV_8UC4, Size( 512, 384) }, |
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{ CV_8UC1, Size( 256, 192) }, // 1/4 1/4 |
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{ CV_8UC2, Size( 256, 192) }, |
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{ CV_8UC3, Size( 256, 192) }, |
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{ CV_8UC4, Size( 256, 192) }, |
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{ CV_8UC1, Size( 4, 3) }, // 1/256 1/256 |
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{ CV_8UC2, Size( 4, 3) }, |
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{ CV_8UC3, Size( 4, 3) }, |
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{ CV_8UC4, Size( 4, 3) }, |
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{ CV_8UC1, Size( 342, 384) }, // 1/3 1/2 |
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{ CV_8UC1, Size( 342, 256) }, // 1/3 1/3 |
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{ CV_8UC2, Size( 342, 256) }, |
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{ CV_8UC3, Size( 342, 256) }, |
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{ CV_8UC4, Size( 342, 256) }, |
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{ CV_8UC1, Size( 512, 256) }, // 1/2 1/3 |
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{ CV_8UC1, Size( 146, 110) }, // 1/7 1/7 |
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{ CV_8UC3, Size( 146, 110) }, |
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{ CV_8UC4, Size( 146, 110) }, |
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{ CV_8UC1, Size( 931, 698) }, // 10/11 10/11 |
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{ CV_8UC2, Size( 931, 698) }, |
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{ CV_8UC3, Size( 931, 698) }, |
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{ CV_8UC4, Size( 931, 698) }, |
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{ CV_8UC1, Size( 853, 640) }, // 10/12 10/12 |
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{ CV_8UC3, Size( 853, 640) }, |
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{ CV_8UC4, Size( 853, 640) }, |
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{ CV_8UC1, Size(1004, 753) }, // 251/256 251/256 |
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{ CV_8UC2, Size(1004, 753) }, |
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{ CV_8UC3, Size(1004, 753) }, |
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{ CV_8UC4, Size(1004, 753) }, |
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{ CV_8UC1, Size(2048,1536) }, // 2 2 |
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{ CV_8UC2, Size(2048,1536) }, |
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{ CV_8UC4, Size(2048,1536) }, |
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{ CV_8UC1, Size(3072,2304) }, // 3 3 |
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{ CV_8UC3, Size(3072,2304) }, |
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{ CV_8UC1, Size(7168,5376) } // 7 7 |
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}; |
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for (int modeind = 0, _modecnt = sizeof(modes) / sizeof(modes[0]); modeind < _modecnt; ++modeind) |
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{ |
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int type = modes[modeind].type, depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type); |
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int dcols = modes[modeind].sz.width, drows = modes[modeind].sz.height; |
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int cols = 1024, rows = 768; |
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double inv_scale_x = (double)dcols / cols; |
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double inv_scale_y = (double)drows / rows; |
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softdouble scale_x = softdouble::one() / softdouble(inv_scale_x); |
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softdouble scale_y = softdouble::one() / softdouble(inv_scale_y); |
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Mat src(rows, cols, type), refdst(drows, dcols, type), dst; |
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RNG rnd(0x123456789abcdefULL); |
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for (int j = 0; j < rows; j++) |
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{ |
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uint8_t* line = src.ptr(j); |
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for (int i = 0; i < cols; i++) |
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for (int c = 0; c < cn; c++) |
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{ |
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double val = j < rows / 2 ? ( i < cols / 2 ? ((sin((i + 1)*CV_PI / 256.)*sin((j + 1)*CV_PI / 256.)*sin((cn + 4)*CV_PI / 8.) + 1.)*128.) : |
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(((i / 128 + j / 128) % 2) * 250 + (j / 128) % 2) ) : |
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( i < cols / 2 ? ((i / 128) * (85 - j / 256 * 40) * ((j / 128) % 2) + (7 - i / 128) * (85 - j / 256 * 40) * ((j / 128 + 1) % 2)) : |
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((uchar)rnd) ) ; |
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if (depth == CV_8U) |
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line[i*cn + c] = (uint8_t)val; |
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else if (depth == CV_16U) |
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((uint16_t*)line)[i*cn + c] = (uint16_t)val; |
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else if (depth == CV_16S) |
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((int16_t*)line)[i*cn + c] = (int16_t)val; |
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else if (depth == CV_32S) |
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((int32_t*)line)[i*cn + c] = (int32_t)val; |
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else |
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CV_Assert(0); |
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} |
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} |
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for (int j = 0; j < drows; j++) |
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{ |
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softdouble src_row_flt = scale_y*(softdouble(j) + softdouble(0.5)) - softdouble(0.5); |
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int src_row = cvFloor(src_row_flt); |
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int64_t ycoeff1 = cvRound64((src_row_flt - softdouble(src_row))*softdouble(fixedOne)); |
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int64_t ycoeff0 = fixedOne - ycoeff1; |
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for (int i = 0; i < dcols; i++) |
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{ |
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softdouble src_col_flt = scale_x*(softdouble(i) + softdouble(0.5)) - softdouble(0.5); |
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int src_col = cvFloor(src_col_flt); |
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int64_t xcoeff1 = cvRound64((src_col_flt - softdouble(src_col))*softdouble(fixedOne)); |
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int64_t xcoeff0 = fixedOne - xcoeff1; |
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uint8_t* dst_pt = refdst.ptr(j, i); |
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uint8_t* src_pt00 = src.ptr( src_row < 0 ? 0 : src_row >= rows ? rows - 1 : src_row , |
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src_col < 0 ? 0 : src_col >= cols ? cols - 1 : src_col ); |
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uint8_t* src_pt01 = src.ptr( src_row < 0 ? 0 : src_row >= rows ? rows - 1 : src_row , |
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(src_col + 1) < 0 ? 0 : (src_col + 1) >= cols ? cols - 1 : (src_col + 1)); |
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uint8_t* src_pt10 = src.ptr((src_row + 1) < 0 ? 0 : (src_row + 1) >= rows ? rows - 1 : (src_row + 1), |
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src_col < 0 ? 0 : src_col >= cols ? cols - 1 : src_col ); |
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uint8_t* src_pt11 = src.ptr((src_row + 1) < 0 ? 0 : (src_row + 1) >= rows ? rows - 1 : (src_row + 1), |
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(src_col + 1) < 0 ? 0 : (src_col + 1) >= cols ? cols - 1 : (src_col + 1)); |
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for (int c = 0; c < cn; c++) |
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{ |
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if (depth == CV_8U) |
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eval4< uint8_t, fixedShiftU8>(xcoeff0, xcoeff1, ycoeff0, ycoeff1, c, src_pt00, src_pt01, src_pt10, src_pt11, dst_pt); |
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else if (depth == CV_16U) |
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eval4<uint16_t, fixedShiftU8>(xcoeff0, xcoeff1, ycoeff0, ycoeff1, c, src_pt00, src_pt01, src_pt10, src_pt11, dst_pt); |
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else if (depth == CV_16S) |
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eval4< int16_t, fixedShiftU8>(xcoeff0, xcoeff1, ycoeff0, ycoeff1, c, src_pt00, src_pt01, src_pt10, src_pt11, dst_pt); |
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else if (depth == CV_32S) |
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eval4< int32_t, fixedShiftU8>(xcoeff0, xcoeff1, ycoeff0, ycoeff1, c, src_pt00, src_pt01, src_pt10, src_pt11, dst_pt); |
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else |
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CV_Assert(0); |
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} |
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} |
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} |
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cv::resize(src, dst, Size(dcols, drows), 0, 0, cv::INTER_LINEAR_EXACT); |
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EXPECT_GE(0, cvtest::norm(refdst, dst, cv::NORM_L1)) |
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<< "Resize " << cn << "-chan mat from " << cols << "x" << rows << " to " << dcols << "x" << drows << " failed with max diff " << cvtest::norm(refdst, dst, cv::NORM_INF); |
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} |
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} |
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PARAM_TEST_CASE(Resize_Bitexact, int) |
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{ |
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public: |
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int depth; |
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virtual void SetUp() |
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{ |
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depth = GET_PARAM(0); |
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} |
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double CountDiff(const Mat& src) |
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{ |
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Mat dstExact; cv::resize(src, dstExact, Size(), 2, 1, INTER_NEAREST_EXACT); |
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Mat dstNonExact; cv::resize(src, dstNonExact, Size(), 2, 1, INTER_NEAREST); |
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return cv::norm(dstExact, dstNonExact, NORM_INF); |
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} |
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}; |
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TEST_P(Resize_Bitexact, Nearest8U_vsNonExact) |
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{ |
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Mat mat_color, mat_gray; |
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Mat src_color = imread(cvtest::findDataFile("shared/lena.png")); |
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Mat src_gray; cv::cvtColor(src_color, src_gray, COLOR_BGR2GRAY); |
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src_color.convertTo(mat_color, depth); |
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src_gray.convertTo(mat_gray, depth); |
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EXPECT_EQ(CountDiff(mat_color), 0) << "color, type: " << depth; |
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EXPECT_EQ(CountDiff(mat_gray), 0) << "gray, type: " << depth; |
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} |
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// Now INTER_NEAREST's convention and INTER_NEAREST_EXACT's one are different. |
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INSTANTIATE_TEST_CASE_P(DISABLED_Imgproc, Resize_Bitexact, |
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testing::Values(CV_8U, CV_16U, CV_32F, CV_64F) |
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); |
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TEST(Resize_Bitexact, Nearest8U) |
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{ |
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Mat src[6], dst[6]; |
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// 2x decimation |
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src[0] = (Mat_<uint8_t>(1, 6) << 0, 1, 2, 3, 4, 5); |
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dst[0] = (Mat_<uint8_t>(1, 3) << 1, 3, 5); |
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// decimation odd to 1 |
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src[1] = (Mat_<uint8_t>(1, 5) << 0, 1, 2, 3, 4); |
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dst[1] = (Mat_<uint8_t>(1, 1) << 2); |
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// decimation n*2-1 to n |
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src[2] = (Mat_<uint8_t>(1, 5) << 0, 1, 2, 3, 4); |
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dst[2] = (Mat_<uint8_t>(1, 3) << 0, 2, 4); |
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// decimation n*2+1 to n |
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src[3] = (Mat_<uint8_t>(1, 5) << 0, 1, 2, 3, 4); |
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dst[3] = (Mat_<uint8_t>(1, 2) << 1, 3); |
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// zoom |
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src[4] = (Mat_<uint8_t>(3, 5) << |
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0, 1, 2, 3, 4, |
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5, 6, 7, 8, 9, |
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10, 11, 12, 13, 14); |
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dst[4] = (Mat_<uint8_t>(5, 7) << |
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0, 1, 1, 2, 3, 3, 4, |
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0, 1, 1, 2, 3, 3, 4, |
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5, 6, 6, 7, 8, 8, 9, |
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10, 11, 11, 12, 13, 13, 14, |
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10, 11, 11, 12, 13, 13, 14); |
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src[5] = (Mat_<uint8_t>(2, 3) << |
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0, 1, 2, |
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3, 4, 5); |
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dst[5] = (Mat_<uint8_t>(4, 6) << |
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0, 0, 1, 1, 2, 2, |
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0, 0, 1, 1, 2, 2, |
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3, 3, 4, 4, 5, 5, |
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3, 3, 4, 4, 5, 5); |
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for (int i = 0; i < 6; i++) |
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{ |
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Mat calc; |
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resize(src[i], calc, dst[i].size(), 0, 0, INTER_NEAREST_EXACT); |
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EXPECT_EQ(cvtest::norm(calc, dst[i], cv::NORM_L1), 0); |
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resize(src[i].t(), calc, dst[i].t().size(), 0, 0, INTER_NEAREST_EXACT); |
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EXPECT_EQ(cvtest::norm(calc, dst[i].t(), cv::NORM_L1), 0); |
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} |
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} |
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}} // namespace
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