Merge pull request #26836 from chacha21:thresholding_compute_threshold_only

Add cv::THRESH_DRYRUN flag to get adaptive threshold values without thresholding #26836

A first proposal for #26777

Adds a `cv::THRESH_DRYRUN` flag to let cv::threshold() compute the threshold (useful for OTSU/TRIANGLE), but without actually running the thresholding. This flags is a proposal instead of a new function cv::computeThreshold()

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [X] The PR is proposed to the proper branch
- [X] There is a reference to the original bug report and related work
- [X] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

modules/imgproc/test/ocl/test_imgproc.cpp

@@ -386,6 +386,40 @@ OCL_TEST_P(Threshold, Mat)
     }
 }
 
+struct Threshold_Dryrun :
+        public ImgprocTestBase
+{
+    int thresholdType;
+
+    virtual void SetUp()
+    {
+        type = GET_PARAM(0);
+        thresholdType = GET_PARAM(2);
+        useRoi = GET_PARAM(3);
+    }
+};
+
+OCL_TEST_P(Threshold_Dryrun, Mat)
+{
+    for (int j = 0; j < test_loop_times; j++)
+    {
+        random_roi();
+
+        double maxVal = randomDouble(20.0, 127.0);
+        double thresh = randomDouble(0.0, maxVal);
+
+        const int _thresholdType = thresholdType | THRESH_DRYRUN;
+
+        src_roi.copyTo(dst_roi);
+        usrc_roi.copyTo(udst_roi);
+
+        OCL_OFF(cv::threshold(src_roi, dst_roi, thresh, maxVal, _thresholdType));
+        OCL_ON(cv::threshold(usrc_roi, udst_roi, thresh, maxVal, _thresholdType));
+
+        OCL_EXPECT_MATS_NEAR(dst, 0);
+    }
+}
+
 /////////////////////////////////////////// CLAHE //////////////////////////////////////////////////
 
 PARAM_TEST_CASE(CLAHETest, Size, double, bool)
@@ -483,6 +517,16 @@ OCL_INSTANTIATE_TEST_CASE_P(Imgproc, Threshold, Combine(
                                    ThreshOp(THRESH_TOZERO), ThreshOp(THRESH_TOZERO_INV)),
                             Bool()));
 
+OCL_INSTANTIATE_TEST_CASE_P(Imgproc, Threshold_Dryrun, Combine(
+                            Values(CV_8UC1, CV_8UC2, CV_8UC3, CV_8UC4,
+                                   CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
+                                   CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
+                            Values(0),
+                            Values(ThreshOp(THRESH_BINARY),
+                                   ThreshOp(THRESH_BINARY_INV), ThreshOp(THRESH_TRUNC),
+                                   ThreshOp(THRESH_TOZERO), ThreshOp(THRESH_TOZERO_INV)),
+                            Bool()));
+
 OCL_INSTANTIATE_TEST_CASE_P(Imgproc, CLAHETest, Combine(
                             Values(Size(4, 4), Size(32, 8), Size(8, 64)),
                             Values(0.0, 10.0, 62.0, 300.0),

modules/imgproc/test/test_thresh.cpp

@@ -502,6 +502,25 @@ BIGDATA_TEST(Imgproc_Threshold, huge)
     ASSERT_EQ((uint64)nz, n / 2);
 }
 
+TEST(Imgproc_Threshold, threshold_dryrun)
+{
+    Size sz(16, 16);
+    Mat input_original(sz, CV_8U, Scalar::all(2));
+    Mat input = input_original.clone();
+    std::vector<int> threshTypes = {THRESH_BINARY, THRESH_BINARY_INV, THRESH_TRUNC, THRESH_TOZERO, THRESH_TOZERO_INV};
+    std::vector<int> threshFlags = {0, THRESH_OTSU, THRESH_TRIANGLE};
+    for(int threshType : threshTypes)
+    {
+        for(int threshFlag : threshFlags)
+        {
+            const int _threshType = threshType | threshFlag | THRESH_DRYRUN;
+            cv::threshold(input, input, 2.0, 0.0, _threshType);
+            EXPECT_MAT_NEAR(input, input_original, 0);
+        }
+    }
+}
+
+
 TEST(Imgproc_Threshold, regression_THRESH_TOZERO_IPP_16085)
 {
     Size sz(16, 16);