vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

2026-08-22 00:11:13 +08:00
commit 12022378a3
3872 changed files with 2513409 additions and 0 deletions
@@ -0,0 +1,3 @@
+#ifdef HAVE_OPENCV_XIMGPROC
+typedef cv::ximgproc::EdgeDrawing::Params EdgeDrawing_Params;
+#endif
@@ -0,0 +1,24 @@
+#!/usr/bin/env python
+import cv2 as cv
+import numpy as np
+
+from tests_common import NewOpenCVTests
+
+class disparity_test(NewOpenCVTests):
+    def test_disp(self):
+        # readGT
+        ret,GT = cv.ximgproc.readGT(self.find_file("cv/disparityfilter/GT.png"))
+        self.assertEqual(ret, 0) # returns 0 on success!
+        self.assertFalse(np.shape(GT) == ())
+
+        # computeMSE
+        left = cv.imread(self.find_file("cv/disparityfilter/disparity_left_raw.png"), cv.IMREAD_UNCHANGED)
+        self.assertFalse(np.shape(left) == ())
+        left = np.asarray(left, dtype=np.int16)
+        mse = cv.ximgproc.computeMSE(GT, left, (0, 0, GT.shape[1], GT.shape[0]))
+
+        # computeBadPixelPercent
+        bad = cv.ximgproc.computeBadPixelPercent(GT, left, (0, 0, GT.shape[1], GT.shape[0]), 24)
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()
@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+import numpy as np
+import cv2 as cv
+
+from tests_common import NewOpenCVTests
+
+class Interpolator_test(NewOpenCVTests):
+    def test_edgeaware_interpolator(self):
+        # readGT
+        MAX_DIF = 1.0
+        MAX_MEAN_DIF = 1.0 / 256.0
+
+        src = cv.imread(self.find_file("cv/optflow/RubberWhale1.png"), cv.IMREAD_COLOR)
+        self.assertFalse(src is None)
+
+        ref_flow = cv.readOpticalFlow(self.find_file("cv/sparse_match_interpolator/RubberWhale_reference_result.flo"))
+        self.assertFalse(ref_flow is None)
+
+        matches = np.genfromtxt(self.find_file("cv/sparse_match_interpolator/RubberWhale_sparse_matches.txt")).astype(np.float32)
+        from_points = matches[:,0:2]
+        to_points = matches[:,2:4]
+        interpolator = cv.ximgproc.createEdgeAwareInterpolator()
+        interpolator.setK(128)
+        interpolator.setSigma(0.05)
+        interpolator.setUsePostProcessing(True)
+        interpolator.setFGSLambda(500.0)
+        interpolator.setFGSSigma(1.5)
+
+        dense_flow = interpolator.interpolate(src, from_points, src, to_points)
+
+        self.assertTrue(cv.norm(dense_flow, ref_flow, cv.NORM_INF) <= MAX_DIF)
+        self.assertTrue(cv.norm(dense_flow, ref_flow, cv.NORM_L1) <= (MAX_MEAN_DIF * dense_flow.shape[0] * dense_flow.shape[1]))
+
+    def test_ric_interpolator(self):
+        # readGT
+        MAX_DIF = 6.0
+        MAX_MEAN_DIF = 60.0 / 256.0
+
+        src0 = cv.imread(self.find_file("cv/optflow/RubberWhale1.png"), cv.IMREAD_COLOR)
+        self.assertFalse(src0 is None)
+
+        src1 = cv.imread(self.find_file("cv/optflow/RubberWhale2.png"), cv.IMREAD_COLOR)
+        self.assertFalse(src1 is None)
+
+        ref_flow = cv.readOpticalFlow(self.find_file("cv/sparse_match_interpolator/RubberWhale_reference_result.flo"))
+        self.assertFalse(ref_flow is None)
+
+        matches = np.genfromtxt(self.find_file("cv/sparse_match_interpolator/RubberWhale_sparse_matches.txt")).astype(np.float32)
+        from_points = matches[:,0:2]
+        to_points = matches[:,2:4]
+
+        interpolator = cv.ximgproc.createRICInterpolator()
+        interpolator.setK(32)
+        interpolator.setSuperpixelSize(15)
+        interpolator.setSuperpixelNNCnt(150)
+        interpolator.setSuperpixelRuler(15.0)
+        interpolator.setSuperpixelMode(cv.ximgproc.SLIC)
+        interpolator.setAlpha(0.7)
+        interpolator.setModelIter(4)
+        interpolator.setRefineModels(True)
+        interpolator.setMaxFlow(250)
+        interpolator.setUseVariationalRefinement(True)
+        interpolator.setUseGlobalSmootherFilter(True)
+        interpolator.setFGSLambda(500.0)
+        interpolator.setFGSSigma(1.5)
+        dense_flow = interpolator.interpolate(src0, from_points, src1, to_points)
+        self.assertTrue(cv.norm(dense_flow, ref_flow, cv.NORM_INF) <= MAX_DIF)
+        self.assertTrue(cv.norm(dense_flow, ref_flow, cv.NORM_L1) <= (MAX_MEAN_DIF * dense_flow.shape[0] * dense_flow.shape[1]))
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()