vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

2026-08-22 00:11:13 +08:00
commit 12022378a3
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+/*
+ * Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+*/
+
+#include "test_precomp.hpp"
+
+namespace opencv_test { namespace {
+
+typedef tuple<cv::Size /*imgSize*/, int /*nPts*/, int /*channels*/> FillConvexTestParams;
+class FillConvexTest : public ::testing::TestWithParam<FillConvexTestParams> {};
+
+TEST_P(FillConvexTest, randomDraw)
+{
+    auto p = GetParam();
+
+    Size imgSize = std::get<0>(p);
+    int nPts     = std::get<1>(p);
+    int channels = std::get<2>(p);
+
+    cv::RNG rng = cv::theRNG();
+
+    std::vector<Point> allPts, contour;
+    for (int i = 0; i < nPts; i++)
+    {
+        allPts.push_back(Point(rng() % imgSize.width, rng() % imgSize.height));
+    }
+    cv::convexHull(allPts, contour);
+
+    Scalar color(rng() % 256, rng() % 256, rng() % 256);
+
+    Mat imgRef(imgSize, CV_MAKE_TYPE(CV_8U, channels), Scalar(0));
+    Mat imgFast = imgRef.clone();
+
+    cv::fillConvexPoly(imgRef, contour, color);
+    cv::fastcv::fillConvexPoly(imgFast, contour, color);
+
+    double normInf = cvtest::norm(imgRef, imgFast, cv::NORM_INF);
+    double normL2  = cvtest::norm(imgRef, imgFast, cv::NORM_L2);
+
+    EXPECT_EQ(normInf, 0);
+    EXPECT_EQ(normL2, 0);
+}
+
+TEST_P(FillConvexTest, circle)
+{
+    auto p = GetParam();
+
+    Size imgSize = std::get<0>(p);
+    int nPts     = std::get<1>(p);
+    int channels = std::get<2>(p);
+
+    cv::RNG rng = cv::theRNG();
+
+    float r = std::min(imgSize.width, imgSize.height) / 2 * 0.9f;
+    float angle = CV_PI * 2.0f / (float)nPts;
+    std::vector<Point> contour;
+    for (int i = 0; i < nPts; i++)
+    {
+        Point2f pt(r * cos((float)i * angle),
+                   r * sin((float)i * angle));
+        contour.push_back({ imgSize.width  / 2 + int(pt.x),
+                            imgSize.height / 2 + int(pt.y)});
+    }
+    Scalar color(rng() % 256, rng() % 256, rng() % 256);
+
+    Mat imgRef(imgSize, CV_MAKE_TYPE(CV_8U, channels), Scalar(0));
+    Mat imgFast = imgRef.clone();
+
+    cv::fillConvexPoly(imgRef, contour, color);
+    cv::fastcv::fillConvexPoly(imgFast, contour, color);
+
+    double normInf = cvtest::norm(imgRef, imgFast, cv::NORM_INF);
+    double normL2  = cvtest::norm(imgRef, imgFast, cv::NORM_L2);
+
+    EXPECT_EQ(normInf, 0);
+    EXPECT_EQ(normL2, 0);
+}
+
+INSTANTIATE_TEST_CASE_P(FastCV_Extension, FillConvexTest,
+                        ::testing::Combine(testing::Values(Size(640, 480), Size(512, 512), Size(1920, 1080)), // imgSize
+                                           testing::Values(4, 64, 1024), // nPts
+                                           testing::Values(1, 2, 3, 4))); // channels
+
+}} // namespaces opencv_test, ::