Added python tests

corelib/test/test_pydetector.cpp

@@ -0,0 +1,182 @@
+// Tests for PyDetector: rtabmap's bridge to Python-backed local-feature
+// detectors (SuperPoint, custom networks, etc.).
+//
+// We stand in a tiny numpy-only stub script for whatever the user would
+// normally point PyDetector at, so the test exercises the full pipeline
+// (script load -> init() -> detect() -> keypoint/descriptor parsing) without
+// pulling in heavy ML model weights. The whole file is a no-op when rtabmap
+// is built without Python -- the CMakeLists.txt only registers it when
+// WITH_PYTHON AND Python3_FOUND, and a defensive #ifdef matches that.
+
+#include <gtest/gtest.h>
+#include <rtabmap/core/Version.h>
+
+#ifdef RTABMAP_PYTHON
+
+#include <rtabmap/core/Features2d.h>
+#include <rtabmap/core/Parameters.h>
+#include <rtabmap/utilite/UConversion.h>
+#include <rtabmap/utilite/UFile.h>
+
+#include <opencv2/core.hpp>
+
+#include <fstream>
+#include <memory>
+#include <string>
+#include <unistd.h>
+
+using namespace rtabmap;
+
+namespace {
+
+// Drops a minimal detector script implementing the contract PyDetector.cpp
+// expects:
+//   init(cuda)            -- called once
+//   detect(imageBuffer)   -- returns (Nx3 float32 [x, y, response], NxDIM float32)
+// Three hard-coded keypoints at (w/4, h/4), (w/2, h/2), (3w/4, 3h/4) with
+// descending responses; descriptor rows filled with (row_index + 1) so the
+// test can identify them. Numpy-only, no heavy deps.
+//
+// Each test uses a unique filename via `tag` so the Python module cache
+// reloads fresh content on each TEST().
+std::string writeStubScript(int tag)
+{
+	const std::string path = uFormat(
+			"/tmp/rtabmap_test_pydetector_%d_%d.py", getpid(), tag);
+	std::ofstream out(path);
+	out <<
+		"import numpy as np\n"
+		"\n"
+		"INITIALIZED = False\n"
+		"CUDA_ARG = None\n"
+		"DESCRIPTOR_DIM = 8\n"
+		"\n"
+		"def init(cuda):\n"
+		"    global INITIALIZED, CUDA_ARG\n"
+		"    INITIALIZED = True\n"
+		"    CUDA_ARG = int(cuda)\n"
+		"\n"
+		"def detect(image):\n"
+		"    h, w = image.shape\n"
+		"    pts = np.array([\n"
+		"        [w * 0.25, h * 0.25, 0.9],\n"
+		"        [w * 0.50, h * 0.50, 0.8],\n"
+		"        [w * 0.75, h * 0.75, 0.7],\n"
+		"    ], dtype=np.float32)\n"
+		"    desc = np.zeros((3, DESCRIPTOR_DIM), dtype=np.float32)\n"
+		"    for i in range(3):\n"
+		"        desc[i, :] = float(i + 1)\n"
+		"    return pts, desc\n";
+	return path;
+}
+
+ParametersMap baseParams(const std::string & scriptPath)
+{
+	ParametersMap p;
+	p.insert(ParametersPair(Parameters::kPyDetectorPath(), scriptPath));
+	p.insert(ParametersPair(Parameters::kPyDetectorCuda(), "false"));
+	p.insert(ParametersPair(Parameters::kKpMaxFeatures(), "100"));
+	p.insert(ParametersPair(Parameters::kKpSSC(), "false"));
+	return p;
+}
+
+cv::Mat makeImage(int rows = 64, int cols = 64)
+{
+	// PyDetector requires CV_8UC1; uniform content is fine for the stub
+	// which ignores pixel values.
+	return cv::Mat(rows, cols, CV_8UC1, cv::Scalar(0));
+}
+
+}  // namespace
+
+// Full happy path: the script loads, returns 3 keypoints + descriptors, and
+// the keypoint positions, responses, and descriptor rows survive end to end.
+TEST(PyDetector, BasicDetection)
+{
+	const std::string scriptPath = writeStubScript(1);
+	std::unique_ptr<Feature2D> detector(Feature2D::create(
+			Feature2D::kFeaturePyDetector, baseParams(scriptPath)));
+	ASSERT_NE(detector.get(), nullptr);
+	EXPECT_EQ(Feature2D::kFeaturePyDetector, detector->getType());
+
+	cv::Mat image = makeImage(64, 64);
+	std::vector<cv::KeyPoint> kpts = detector->generateKeypoints(image);
+	ASSERT_EQ(3u, kpts.size());
+
+	// Stub points: (w/4, h/4), (w/2, h/2), (3w/4, 3h/4) with responses
+	// 0.9, 0.8, 0.7.
+	EXPECT_NEAR(16.0f, kpts[0].pt.x, 1e-3f);
+	EXPECT_NEAR(16.0f, kpts[0].pt.y, 1e-3f);
+	EXPECT_NEAR(32.0f, kpts[1].pt.x, 1e-3f);
+	EXPECT_NEAR(48.0f, kpts[2].pt.x, 1e-3f);
+	EXPECT_NEAR(0.9f, kpts[0].response, 1e-5f);
+	EXPECT_NEAR(0.8f, kpts[1].response, 1e-5f);
+	EXPECT_NEAR(0.7f, kpts[2].response, 1e-5f);
+
+	cv::Mat descriptors = detector->generateDescriptors(image, kpts);
+	EXPECT_EQ(3, descriptors.rows);
+	EXPECT_EQ(8, descriptors.cols);
+	EXPECT_EQ(CV_32FC1, descriptors.type());
+	for(int r = 0; r < descriptors.rows; ++r)
+	{
+		EXPECT_NEAR(float(r + 1), descriptors.at<float>(r, 0), 1e-5f);
+	}
+
+	UFile::erase(scriptPath);
+}
+
+// PyDetector logs an error and silently returns no keypoints when the
+// script path doesn't exist -- the constructor doesn't throw. Pin that
+// contract so callers can safely construct without pre-checking the path.
+TEST(PyDetector, MissingPathReturnsEmpty)
+{
+	const std::string scriptPath = uFormat(
+			"/tmp/rtabmap_test_pydetector_does_not_exist_%d.py", getpid());
+	std::unique_ptr<Feature2D> detector(Feature2D::create(
+			Feature2D::kFeaturePyDetector, baseParams(scriptPath)));
+	ASSERT_NE(detector.get(), nullptr);
+
+	cv::Mat image = makeImage(32, 32);
+	std::vector<cv::KeyPoint> kpts = detector->generateKeypoints(image);
+	EXPECT_TRUE(kpts.empty());
+}
+
+// A non-empty mask removes keypoints whose (x, y) falls on a 0 pixel. The
+// stub returns one keypoint at (48, 48); we mask everything from row/col 33
+// onward so it gets dropped while the two earlier points survive.
+TEST(PyDetector, MaskFiltersKeypoints)
+{
+	const std::string scriptPath = writeStubScript(2);
+	std::unique_ptr<Feature2D> detector(Feature2D::create(
+			Feature2D::kFeaturePyDetector, baseParams(scriptPath)));
+	ASSERT_NE(detector.get(), nullptr);
+
+	cv::Mat image = makeImage(64, 64);
+	cv::Mat mask(image.size(), CV_8UC1, cv::Scalar(255));
+	mask(cv::Rect(33, 33, mask.cols - 33, mask.rows - 33)).setTo(0);
+	std::vector<cv::KeyPoint> kpts = detector->generateKeypoints(image, mask);
+	EXPECT_EQ(2u, kpts.size());
+
+	UFile::erase(scriptPath);
+}
+
+// Kp/MaxFeatures caps the returned keypoint list inside generateKeypointsImpl
+// (PyDetector calls limitKeypoints with its own descriptor matrix at the end).
+// The stub returns 3 keypoints; cap at 2 and verify the rest are dropped.
+TEST(PyDetector, MaxFeaturesCap)
+{
+	const std::string scriptPath = writeStubScript(3);
+	ParametersMap p = baseParams(scriptPath);
+	p[Parameters::kKpMaxFeatures()] = "2";
+	std::unique_ptr<Feature2D> detector(
+			Feature2D::create(Feature2D::kFeaturePyDetector, p));
+	ASSERT_NE(detector.get(), nullptr);
+
+	cv::Mat image = makeImage(64, 64);
+	std::vector<cv::KeyPoint> kpts = detector->generateKeypoints(image);
+	EXPECT_EQ(2u, kpts.size());
+
+	UFile::erase(scriptPath);
+}
+
+#endif  // RTABMAP_PYTHON