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Added tests for adaptiveThreshold and sepFilter2D

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This commit is contained in:
Alexander Lyulkov 2024-04-08 13:04:50 +03:00
parent 2b1c8aa4db
commit 30889f4a90
2 changed files with 226 additions and 0 deletions
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172
modules/imgproc/test/test_filter.cpp
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@ -2380,4 +2380,176 @@ TEST(Imgproc, morphologyEx_small_input_22893)
ASSERT_EQ(0, cvtest::norm(result, gold, NORM_INF));
}
TEST(Imgproc_sepFilter2D, identity)
{
std::vector<uint8_t> kernelX{0, 0, 0, 1, 0, 0, 0};
std::vector<uint8_t> kernelY{0, 0, 1, 0, 0};
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::sepFilter2D(input, result, input.depth(), kernelX, kernelY);
EXPECT_EQ(0, cv::norm(result, input, NORM_INF));
}
TEST(Imgproc_sepFilter2D, shift)
{
std::vector<float> kernelX{1, 0, 0};
std::vector<float> kernelY{0, 0, 1};
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::sepFilter2D(input, result, input.depth(), kernelX, kernelY);
int W = input.cols;
int H = input.rows;
Mat inputCrop = input(Range(1, H), Range(0, W - 1));
Mat resultCrop = result(Range(0, H - 1), Range(1, W));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
// Checking borders. Should be BORDER_REFLECT_101
inputCrop = input(Range(H - 2, H - 1), Range(0, W - 1));
resultCrop = result(Range(H - 1, H), Range(1, W));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
inputCrop = input(Range(1, H), Range(1, 2));
resultCrop = result(Range(0, H - 1), Range(0, 1));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
inputCrop = input(Range(H - 2, H - 1), Range(1, 2));
resultCrop = result(Range(H - 1, H), Range(0, 1));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
}
TEST(Imgproc_sepFilter2D, zeroPadding)
{
std::vector<int> kernelX{1, 0, 0};
std::vector<int> kernelY{0, 0, 1};
Point anchor(-1, -1);
double delta = 0;
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::sepFilter2D(input, result, input.depth(), kernelX, kernelY, anchor, delta, BORDER_CONSTANT);
int W = input.cols;
int H = input.rows;
Mat inputCrop = input(Range(1, H), Range(0, W - 1));
Mat resultCrop = result(Range(0, H - 1), Range(1, W));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
// Checking borders
resultCrop = result(Range(H - 1, H), Range(0, W));
EXPECT_EQ(0, cv::norm(resultCrop, NORM_INF));
resultCrop = result(Range(0, H), Range(0, 1));
EXPECT_EQ(0, cv::norm(resultCrop, NORM_INF));
}
TEST(Imgproc_sepFilter2D, anchor)
{
std::vector<float> kernelX{0, 1, 0};
std::vector<float> kernelY{0, 1, 0};
Point anchor(2, 0);
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::sepFilter2D(input, result, input.depth(), kernelX, kernelY, anchor);
int W = input.cols;
int H = input.rows;
Mat inputCrop = input(Range(1, H), Range(0, W - 1));
Mat resultCrop = result(Range(0, H - 1), Range(1, W));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
// Checking borders. Should be BORDER_REFLECT_101
inputCrop = input(Range(H - 2, H - 1), Range(0, W - 1));
resultCrop = result(Range(H - 1, H), Range(1, W));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
inputCrop = input(Range(1, H), Range(1, 2));
resultCrop = result(Range(0, H - 1), Range(0, 1));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
inputCrop = input(Range(H - 2, H - 1), Range(1, 2));
resultCrop = result(Range(H - 1, H), Range(0, 1));
EXPECT_EQ(0, cv::norm(resultCrop, inputCrop, NORM_INF));
}
TEST(Imgproc_sepFilter2D, delta)
{
std::vector<float> kernelX{0, 0.5, 0};
std::vector<float> kernelY{0, 1, 0};
Point anchor(1, 1);
double delta = 5;
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::sepFilter2D(input, result, input.depth(), kernelX, kernelY, anchor, delta);
Mat gt = input / 2 + delta;
EXPECT_EQ(0, cv::norm(result, gt, NORM_INF));
}
typedef testing::TestWithParam<int> Imgproc_sepFilter2D_outTypes;
TEST_P(Imgproc_sepFilter2D_outTypes, simple)
{
int outputType = GetParam();
std::vector<float> kernelX{0, 0.5, 0};
std::vector<float> kernelY{0, 0.5, 0};
Point anchor(1, 1);
double delta = 5;
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::sepFilter2D(input, result, outputType, kernelX, kernelY, anchor, delta);
input.convertTo(input, outputType);
Mat gt = input / 4 + delta;
EXPECT_EQ(0, cv::norm(result, gt, NORM_INF));
}
INSTANTIATE_TEST_CASE_P(/**/, Imgproc_sepFilter2D_outTypes,
testing::Values(CV_16S, CV_32F, CV_64F),
);
typedef testing::TestWithParam<int> Imgproc_sepFilter2D_types;
TEST_P(Imgproc_sepFilter2D_types, simple)
{
int outputType = GetParam();
std::vector<float> kernelX{0, 0.5, 0};
std::vector<float> kernelY{0, 0.5, 0};
Point anchor(1, 1);
double delta = 5;
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
input.convertTo(input, outputType);
Mat result;
cv::sepFilter2D(input, result, outputType, kernelX, kernelY, anchor, delta);
Mat gt = input / 4 + delta;
EXPECT_EQ(0, cv::norm(result, gt, NORM_INF));
}
INSTANTIATE_TEST_CASE_P(/**/, Imgproc_sepFilter2D_types,
testing::Values(CV_16S, CV_32F, CV_64F),
);
}} // namespace

54
modules/imgproc/test/test_thresh.cpp
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@ -541,4 +541,58 @@ TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_21258_Max)
EXPECT_EQ(0, cv::norm(result, NORM_INF));
}
TEST(Imgproc_AdaptiveThreshold, mean)
{
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::adaptiveThreshold(input, result, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY, 15, 8);
const string gt_path = cvtest::findDataFile("../cv/imgproc/adaptive_threshold1.png");
Mat gt = imread(gt_path, IMREAD_GRAYSCALE);
EXPECT_EQ(0, cv::norm(result, gt, NORM_INF));
}
TEST(Imgproc_AdaptiveThreshold, mean_inv)
{
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::adaptiveThreshold(input, result, 255, ADAPTIVE_THRESH_MEAN_C, THRESH_BINARY_INV, 15, 8);
const string gt_path = cvtest::findDataFile("../cv/imgproc/adaptive_threshold1.png");
Mat gt = imread(gt_path, IMREAD_GRAYSCALE);
gt = Mat(gt.rows, gt.cols, CV_8UC1, cv::Scalar(255)) - gt;
EXPECT_EQ(0, cv::norm(result, gt, NORM_INF));
}
TEST(Imgproc_AdaptiveThreshold, gauss)
{
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::adaptiveThreshold(input, result, 200, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY, 21, -5);
const string gt_path = cvtest::findDataFile("../cv/imgproc/adaptive_threshold2.png");
Mat gt = imread(gt_path, IMREAD_GRAYSCALE);
EXPECT_EQ(0, cv::norm(result, gt, NORM_INF));
}
TEST(Imgproc_AdaptiveThreshold, gauss_inv)
{
const string input_path = cvtest::findDataFile("../cv/shared/baboon.png");
Mat input = imread(input_path, IMREAD_GRAYSCALE);
Mat result;
cv::adaptiveThreshold(input, result, 200, ADAPTIVE_THRESH_GAUSSIAN_C, THRESH_BINARY_INV, 21, -5);
const string gt_path = cvtest::findDataFile("../cv/imgproc/adaptive_threshold2.png");
Mat gt = imread(gt_path, IMREAD_GRAYSCALE);
gt = Mat(gt.rows, gt.cols, CV_8UC1, cv::Scalar(200)) - gt;
EXPECT_EQ(0, cv::norm(result, gt, NORM_INF));
}
}} // namespace