718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法,已通过基本的兼容性测试 2.工程改为使用CMake组织,后续为了更好地兼容第三方库,不再提供QMake工程 3.重整权利声明文件,重整代码工程,确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN,切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
161 lines
5.1 KiB
C++
161 lines
5.1 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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namespace opencv_test { namespace {
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class CV_InpaintTest : public cvtest::BaseTest
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{
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public:
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CV_InpaintTest();
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~CV_InpaintTest();
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protected:
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void run(int);
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};
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CV_InpaintTest::CV_InpaintTest()
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{
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}
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CV_InpaintTest::~CV_InpaintTest() {}
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void CV_InpaintTest::run( int )
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{
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string folder = string(ts->get_data_path()) + "inpaint/";
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Mat orig = imread(folder + "orig.png");
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Mat exp1 = imread(folder + "exp1.png");
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Mat exp2 = imread(folder + "exp2.png");
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Mat mask = imread(folder + "mask.png");
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if (orig.empty() || exp1.empty() || exp2.empty() || mask.empty())
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
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return;
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}
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Mat inv_mask;
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mask.convertTo(inv_mask, CV_8UC3, -1.0, 255.0);
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Mat mask1ch;
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cv::cvtColor(mask, mask1ch, COLOR_BGR2GRAY);
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Mat test = orig.clone();
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test.setTo(Scalar::all(255), mask1ch);
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Mat res1, res2;
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inpaint( test, mask1ch, res1, 5, INPAINT_NS );
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inpaint( test, mask1ch, res2, 5, INPAINT_TELEA );
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Mat diff1, diff2;
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absdiff( orig, res1, diff1 );
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absdiff( orig, res2, diff2 );
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double n1 = cvtest::norm(diff1.reshape(1), NORM_INF, inv_mask.reshape(1));
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double n2 = cvtest::norm(diff2.reshape(1), NORM_INF, inv_mask.reshape(1));
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if (n1 != 0 || n2 != 0)
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
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return;
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}
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absdiff( exp1, res1, diff1 );
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absdiff( exp2, res2, diff2 );
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n1 = cvtest::norm(diff1.reshape(1), NORM_INF, mask.reshape(1));
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n2 = cvtest::norm(diff2.reshape(1), NORM_INF, mask.reshape(1));
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const int jpeg_thres = 3;
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if (n1 > jpeg_thres || n2 > jpeg_thres)
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{
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ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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return;
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}
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ts->set_failed_test_info(cvtest::TS::OK);
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}
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TEST(Photo_Inpaint, regression) { CV_InpaintTest test; test.safe_run(); }
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typedef testing::TestWithParam<tuple<int> > formats;
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TEST_P(formats, 1c)
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{
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const int type = get<0>(GetParam());
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Mat src(100, 100, type);
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src.setTo(Scalar::all(128));
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Mat ref = src.clone();
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Mat dst, mask = Mat::zeros(src.size(), CV_8U);
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circle(src, Point(50, 50), 5, Scalar(200), 6);
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circle(mask, Point(50, 50), 5, Scalar(200), 6);
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inpaint(src, mask, dst, 10, INPAINT_NS);
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Mat dst2;
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inpaint(src, mask, dst2, 10, INPAINT_TELEA);
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ASSERT_LE(cv::norm(dst, ref, NORM_INF), 3.);
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ASSERT_LE(cv::norm(dst2, ref, NORM_INF), 3.);
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}
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INSTANTIATE_TEST_CASE_P(Photo_Inpaint, formats, testing::Values(CV_32F, CV_16U, CV_8U));
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TEST(Photo_InpaintBorders, regression)
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{
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Mat img(64, 64, CV_8U);
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img = 128;
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img(Rect(0, 0, 16, 64)) = 0;
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Mat mask(64, 64, CV_8U);
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mask = 0;
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mask(Rect(0, 0, 16, 64)) = 255;
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Mat inpainted;
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inpaint(img, mask, inpainted, 1, INPAINT_TELEA);
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Mat diff;
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cv::absdiff(inpainted, 128*Mat::ones(inpainted.size(), inpainted.type()), diff);
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ASSERT_TRUE(countNonZero(diff) == 0);
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}
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}} // namespace
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