deepin-ocr/3rdparty/opencv-4.5.4/modules/imgproc/test/test_intelligent_scissors.cpp
wangzhengyang 718c41634f feat: 切换后端至PaddleOCR-NCNN,切换工程为CMake
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
2022-05-10 10:22:11 +08:00

468 lines
11 KiB
C++

// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#include "test_precomp.hpp"
//#include "opencv2/imgproc/segmentation.hpp"
namespace opencv_test { namespace {
Mat getTestImageGray()
{
static Mat m;
if (m.empty())
{
m = imread(findDataFile("shared/lena.png"), IMREAD_GRAYSCALE);
}
return m.clone();
}
Mat getTestImageColor()
{
static Mat m;
if (m.empty())
{
m = imread(findDataFile("shared/lena.png"), IMREAD_COLOR);
}
return m.clone();
}
Mat getTestImage1()
{
static Mat m;
if (m.empty())
{
m.create(Size(200, 100), CV_8UC1);
m.setTo(Scalar::all(128));
Rect roi(50, 30, 100, 40);
m(roi).setTo(Scalar::all(0));
#if 0
imshow("image", m);
waitKey();
#endif
}
return m.clone();
}
Mat getTestImage2()
{
static Mat m;
if (m.empty())
{
m.create(Size(200, 100), CV_8UC1);
m.setTo(Scalar::all(128));
Rect roi(40, 30, 100, 40);
m(roi).setTo(Scalar::all(255));
#if 0
imshow("image", m);
waitKey();
#endif
}
return m.clone();
}
Mat getTestImage3()
{
static Mat m;
if (m.empty())
{
m.create(Size(200, 100), CV_8UC1);
m.setTo(Scalar::all(128));
Scalar color(0,0,0,0);
line(m, Point(30, 50), Point(50, 50), color, 1);
line(m, Point(50, 50), Point(80, 30), color, 1);
line(m, Point(150, 50), Point(80, 30), color, 1);
line(m, Point(150, 50), Point(180, 50), color, 1);
line(m, Point(80, 10), Point(80, 90), Scalar::all(200), 1);
line(m, Point(100, 10), Point(100, 90), Scalar::all(200), 1);
line(m, Point(120, 10), Point(120, 90), Scalar::all(200), 1);
#if 0
imshow("image", m);
waitKey();
#endif
}
return m.clone();
}
Mat getTestImage4()
{
static Mat m;
if (m.empty())
{
m.create(Size(200, 100), CV_8UC1);
for (int y = 0; y < m.rows; y++)
{
for (int x = 0; x < m.cols; x++)
{
float dx = (float)(x - 100);
float dy = (float)(y - 100);
float d = sqrtf(dx * dx + dy * dy);
m.at<uchar>(y, x) = saturate_cast<uchar>(100 + 100 * sin(d / 10 * CV_PI));
}
}
#if 0
imshow("image", m);
waitKey();
#endif
}
return m.clone();
}
Mat getTestImage5()
{
static Mat m;
if (m.empty())
{
m.create(Size(200, 100), CV_8UC1);
for (int y = 0; y < m.rows; y++)
{
for (int x = 0; x < m.cols; x++)
{
float dx = (float)(x - 100);
float dy = (float)(y - 100);
float d = sqrtf(dx * dx + dy * dy);
m.at<uchar>(y, x) = saturate_cast<uchar>(x / 2 + 100 * sin(d / 10 * CV_PI));
}
}
#if 0
imshow("image", m);
waitKey();
#endif
}
return m.clone();
}
void show(const Mat& img, const std::vector<Point> pts)
{
if (cvtest::debugLevel >= 10)
{
Mat dst = img.clone();
std::vector< std::vector<Point> > contours;
contours.push_back(pts);
polylines(dst, contours, false, Scalar::all(255));
imshow("dst", dst);
waitKey();
}
}
TEST(Imgproc_IntelligentScissorsMB, rect)
{
segmentation::IntelligentScissorsMB tool;
tool.applyImage(getTestImage1());
Point source_point(50, 30);
tool.buildMap(source_point);
Point target_point(100, 30);
std::vector<Point> pts;
tool.getContour(target_point, pts);
tool.applyImage(getTestImage2());
tool.buildMap(source_point);
std::vector<Point> pts2;
tool.getContour(target_point, pts2, true/*backward*/);
EXPECT_EQ(pts.size(), pts2.size());
}
TEST(Imgproc_IntelligentScissorsMB, lines)
{
segmentation::IntelligentScissorsMB tool;
Mat image = getTestImage3();
tool.applyImage(image);
Point source_point(30, 50);
tool.buildMap(source_point);
Point target_point(150, 50);
std::vector<Point> pts;
tool.getContour(target_point, pts);
EXPECT_EQ((size_t)121, pts.size());
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, circles)
{
segmentation::IntelligentScissorsMB tool;
tool.setGradientMagnitudeMaxLimit(10);
Mat image = getTestImage4();
tool.applyImage(image);
Point source_point(50, 50);
tool.buildMap(source_point);
Point target_point(150, 50);
std::vector<Point> pts;
tool.getContour(target_point, pts);
EXPECT_EQ((size_t)101, pts.size());
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, circles_gradient)
{
segmentation::IntelligentScissorsMB tool;
Mat image = getTestImage5();
tool.applyImage(image);
Point source_point(50, 50);
tool.buildMap(source_point);
Point target_point(150, 50);
std::vector<Point> pts;
tool.getContour(target_point, pts);
EXPECT_EQ((size_t)101, pts.size());
show(image, pts);
}
#define PTS_SIZE_EPS 2
TEST(Imgproc_IntelligentScissorsMB, grayscale)
{
segmentation::IntelligentScissorsMB tool;
Mat image = getTestImageGray();
tool.applyImage(image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 206;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, check_features_grayscale_1_0_0_zerro_crossing_with_limit)
{
segmentation::IntelligentScissorsMB tool;
tool.setEdgeFeatureZeroCrossingParameters(64);
tool.setWeights(1.0f, 0.0f, 0.0f);
Mat image = getTestImageGray();
tool.applyImage(image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 207;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, check_features_grayscale_1_0_0_canny)
{
segmentation::IntelligentScissorsMB tool;
tool.setEdgeFeatureCannyParameters(50, 100);
tool.setWeights(1.0f, 0.0f, 0.0f);
Mat image = getTestImageGray();
tool.applyImage(image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 201;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, check_features_grayscale_0_1_0)
{
segmentation::IntelligentScissorsMB tool;
tool.setWeights(0.0f, 1.0f, 0.0f);
Mat image = getTestImageGray();
tool.applyImage(image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 166;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, check_features_grayscale_0_0_1)
{
segmentation::IntelligentScissorsMB tool;
tool.setWeights(0.0f, 0.0f, 1.0f);
Mat image = getTestImageGray();
tool.applyImage(image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 197;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, color)
{
segmentation::IntelligentScissorsMB tool;
Mat image = getTestImageColor();
tool.applyImage(image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 205;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, color_canny)
{
segmentation::IntelligentScissorsMB tool;
tool.setEdgeFeatureCannyParameters(32, 100);
Mat image = getTestImageColor();
tool.applyImage(image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 200;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, color_custom_features_invalid)
{
segmentation::IntelligentScissorsMB tool;
ASSERT_ANY_THROW(tool.applyImageFeatures(noArray(), noArray(), noArray()));
}
TEST(Imgproc_IntelligentScissorsMB, color_custom_features_edge)
{
segmentation::IntelligentScissorsMB tool;
Mat image = getTestImageColor();
Mat canny_edges;
Canny(image, canny_edges, 32, 100, 5);
Mat binary_edge_feature;
cv::threshold(canny_edges, binary_edge_feature, 254, 1, THRESH_BINARY_INV);
tool.applyImageFeatures(binary_edge_feature, noArray(), noArray(), image);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 201;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, color_custom_features_all)
{
segmentation::IntelligentScissorsMB tool;
tool.setWeights(0.9f, 0.0f, 0.1f);
Mat image = getTestImageColor();
Mat canny_edges;
Canny(image, canny_edges, 50, 100, 5);
Mat binary_edge_feature; // 0, 1 values
cv::threshold(canny_edges, binary_edge_feature, 254, 1, THRESH_BINARY_INV);
Mat_<Point2f> gradient_direction(image.size(), Point2f(0, 0)); // normalized
Mat_<float> gradient_magnitude(image.size(), 0); // cost function
tool.applyImageFeatures(binary_edge_feature, gradient_direction, gradient_magnitude);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 201;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
TEST(Imgproc_IntelligentScissorsMB, color_custom_features_edge_magnitude)
{
segmentation::IntelligentScissorsMB tool;
tool.setWeights(0.9f, 0.0f, 0.1f);
Mat image = getTestImageColor();
Mat canny_edges;
Canny(image, canny_edges, 50, 100, 5);
Mat binary_edge_feature; // 0, 1 values
cv::threshold(canny_edges, binary_edge_feature, 254, 1, THRESH_BINARY_INV);
Mat_<float> gradient_magnitude(image.size(), 0); // cost function
tool.applyImageFeatures(binary_edge_feature, noArray(), gradient_magnitude);
Point source_point(275, 63);
tool.buildMap(source_point);
Point target_point(413, 155);
std::vector<Point> pts;
tool.getContour(target_point, pts);
size_t gold = 201;
EXPECT_GE(pts.size(), gold - PTS_SIZE_EPS);
EXPECT_LE(pts.size(), gold + PTS_SIZE_EPS);
show(image, pts);
}
}} // namespace