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modules/objdetect/misc/python/test/test_objdetect_aruco.py
462 строки
20 KB
Alex
fix drawDetectedCornersCharuco, drawDetectedMarkers, drawDetectedDiamonds added tests
12 сен 2023, 12:17
12 сен 2023, 12:17
ae1d1b6
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#!/usr/bin/env python # Python 2/3 compatibility from __future__ import print_function import os, tempfile, numpy as np from math import pi import cv2 as cv from tests_common import NewOpenCVTests def getSyntheticRT(yaw, pitch, distance): rvec = np.zeros((3, 1), np.float64) tvec = np.zeros((3, 1), np.float64) rotPitch = np.array([[-pitch], [0], [0]]) rotYaw = np.array([[0], [yaw], [0]]) rvec, tvec = cv.composeRT(rotPitch, np.zeros((3, 1), np.float64), rotYaw, np.zeros((3, 1), np.float64))[:2] tvec = np.array([[0], [0], [distance]]) return rvec, tvec # see test_aruco_utils.cpp def projectMarker(img, board, markerIndex, cameraMatrix, rvec, tvec, markerBorder): markerSizePixels = 100 markerImg = cv.aruco.generateImageMarker(board.getDictionary(), board.getIds()[markerIndex], markerSizePixels, borderBits=markerBorder) distCoeffs = np.zeros((5, 1), np.float64) maxCoord = board.getRightBottomCorner() objPoints = board.getObjPoints()[markerIndex] for i in range(len(objPoints)): objPoints[i][0] -= maxCoord[0] / 2 objPoints[i][1] -= maxCoord[1] / 2 objPoints[i][2] -= maxCoord[2] / 2 corners, _ = cv.projectPoints(objPoints, rvec, tvec, cameraMatrix, distCoeffs) originalCorners = np.array([ [0, 0], [markerSizePixels, 0], [markerSizePixels, markerSizePixels], [0, markerSizePixels], ], np.float32) transformation = cv.getPerspectiveTransform(originalCorners, corners) borderValue = 127 aux = cv.warpPerspective(markerImg, transformation, img.shape, None, cv.INTER_NEAREST, cv.BORDER_CONSTANT, borderValue) assert(img.shape == aux.shape) mask = (aux == borderValue).astype(np.uint8) img = img * mask + aux * (1 - mask) return img def projectChessboard(squaresX, squaresY, squareSize, imageSize, cameraMatrix, rvec, tvec): img = np.ones(imageSize, np.uint8) * 255 distCoeffs = np.zeros((5, 1), np.float64) for y in range(squaresY): startY = y * squareSize for x in range(squaresX): if (y % 2 != x % 2): continue startX = x * squareSize squareCorners = np.array([[startX - squaresX*squareSize/2, startY - squaresY*squareSize/2, 0]], np.float32) squareCorners = np.stack((squareCorners[0], squareCorners[0] + [squareSize, 0, 0], squareCorners[0] + [squareSize, squareSize, 0], squareCorners[0] + [0, squareSize, 0])) projectedCorners, _ = cv.projectPoints(squareCorners, rvec, tvec, cameraMatrix, distCoeffs) projectedCorners = projectedCorners.astype(np.int64) projectedCorners = projectedCorners.reshape(1, 4, 2) img = cv.fillPoly(img, [projectedCorners], 0) return img def projectCharucoBoard(board, cameraMatrix, yaw, pitch, distance, imageSize, markerBorder): rvec, tvec = getSyntheticRT(yaw, pitch, distance) img = np.ones(imageSize, np.uint8) * 255 for indexMarker in range(len(board.getIds())): img = projectMarker(img, board, indexMarker, cameraMatrix, rvec, tvec, markerBorder) chessboard = projectChessboard(board.getChessboardSize()[0], board.getChessboardSize()[1], board.getSquareLength(), imageSize, cameraMatrix, rvec, tvec) chessboard = (chessboard != 0).astype(np.uint8) img = img * chessboard return img, rvec, tvec class aruco_objdetect_test(NewOpenCVTests): def test_board(self): p1 = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32) p2 = np.array([[1, 0, 0], [1, 1, 0], [2, 1, 0], [2, 0, 0]], dtype=np.float32) objPoints = np.array([p1, p2]) dictionary = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_50) ids = np.array([0, 1]) board = cv.aruco.Board(objPoints, dictionary, ids) np.testing.assert_array_equal(board.getIds().squeeze(), ids) np.testing.assert_array_equal(np.ravel(np.array(board.getObjPoints())), np.ravel(np.concatenate([p1, p2]))) def test_idsAccessibility(self): ids = np.arange(17) rev_ids = ids[::-1] aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_5X5_250) board = cv.aruco.CharucoBoard((7, 5), 1, 0.5, aruco_dict) np.testing.assert_array_equal(board.getIds().squeeze(), ids) board = cv.aruco.CharucoBoard((7, 5), 1, 0.5, aruco_dict, rev_ids) np.testing.assert_array_equal(board.getIds().squeeze(), rev_ids) board = cv.aruco.CharucoBoard((7, 5), 1, 0.5, aruco_dict, ids) np.testing.assert_array_equal(board.getIds().squeeze(), ids) def test_identify(self): aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_50) expected_idx = 9 expected_rotation = 2 bit_marker = np.array([[0, 1, 1, 0], [1, 0, 1, 0], [1, 1, 1, 1], [0, 0, 1, 1]], dtype=np.uint8) check, idx, rotation = aruco_dict.identify(bit_marker, 0) self.assertTrue(check, True) self.assertEqual(idx, expected_idx) self.assertEqual(rotation, expected_rotation) def test_getDistanceToId(self): aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_50) idx = 7 rotation = 3 bit_marker = np.array([[0, 1, 0, 1], [0, 1, 1, 1], [1, 1, 0, 0], [0, 1, 0, 0]], dtype=np.uint8) dist = aruco_dict.getDistanceToId(bit_marker, idx) self.assertEqual(dist, 0) def test_aruco_detector(self): aruco_params = cv.aruco.DetectorParameters() aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_250) aruco_detector = cv.aruco.ArucoDetector(aruco_dict, aruco_params) id = 2 marker_size = 100 offset = 10 img_marker = cv.aruco.generateImageMarker(aruco_dict, id, marker_size, aruco_params.markerBorderBits) img_marker = np.pad(img_marker, pad_width=offset, mode='constant', constant_values=255) gold_corners = np.array([[offset, offset],[marker_size+offset-1.0,offset], [marker_size+offset-1.0,marker_size+offset-1.0], [offset, marker_size+offset-1.0]], dtype=np.float32) corners, ids, rejected = aruco_detector.detectMarkers(img_marker) self.assertEqual(1, len(ids)) self.assertEqual(id, ids[0]) for i in range(0, len(corners)): np.testing.assert_array_equal(gold_corners, corners[i].reshape(4, 2)) def test_aruco_detector_refine(self): aruco_params = cv.aruco.DetectorParameters() aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_250) aruco_detector = cv.aruco.ArucoDetector(aruco_dict, aruco_params) board_size = (3, 4) board = cv.aruco.GridBoard(board_size, 5.0, 1.0, aruco_dict) board_image = board.generateImage((board_size[0]*50, board_size[1]*50), marginSize=10) corners, ids, rejected = aruco_detector.detectMarkers(board_image) self.assertEqual(board_size[0]*board_size[1], len(ids)) part_corners, part_ids, part_rejected = corners[:-1], ids[:-1], list(rejected) part_rejected.append(corners[-1]) refine_corners, refine_ids, refine_rejected, recovered_ids = aruco_detector.refineDetectedMarkers(board_image, board, part_corners, part_ids, part_rejected) self.assertEqual(board_size[0] * board_size[1], len(refine_ids)) self.assertEqual(1, len(recovered_ids)) self.assertEqual(ids[-1], refine_ids[-1]) self.assertEqual((1, 4, 2), refine_corners[0].shape) np.testing.assert_array_equal(corners, refine_corners) def test_charuco_refine(self): aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_6X6_50) board_size = (3, 4) board = cv.aruco.CharucoBoard(board_size, 1., .7, aruco_dict) aruco_detector = cv.aruco.ArucoDetector(aruco_dict) charuco_detector = cv.aruco.CharucoDetector(board) cell_size = 100 image = board.generateImage((cell_size*board_size[0], cell_size*board_size[1])) camera = np.array([[1, 0, 0.5], [0, 1, 0.5], [0, 0, 1]]) dist = np.array([0, 0, 0, 0, 0], dtype=np.float32).reshape(1, -1) # generate gold corners of the ArUco markers for the test gold_corners = np.array(board.getObjPoints())[:, :, 0:2]*cell_size # detect corners markerCorners, markerIds, _ = aruco_detector.detectMarkers(image) # test refine rejected = [markerCorners[-1]] markerCorners, markerIds = markerCorners[:-1], markerIds[:-1] markerCorners, markerIds, _, _ = aruco_detector.refineDetectedMarkers(image, board, markerCorners, markerIds, rejected, cameraMatrix=camera, distCoeffs=dist) charucoCorners, charucoIds, _, _ = charuco_detector.detectBoard(image, markerCorners=markerCorners, markerIds=markerIds) self.assertEqual(len(charucoIds), 6) self.assertEqual(len(markerIds), 6) for i, id in enumerate(markerIds.reshape(-1)): np.testing.assert_allclose(gold_corners[id], markerCorners[i].reshape(4, 2), 0.01, 1.) def test_write_read_dictionary(self): try: aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_5X5_50) markers_gold = aruco_dict.bytesList # write aruco_dict fd, filename = tempfile.mkstemp(prefix="opencv_python_aruco_dict_", suffix=".yml") os.close(fd) fs_write = cv.FileStorage(filename, cv.FileStorage_WRITE) aruco_dict.writeDictionary(fs_write) fs_write.release() # reset aruco_dict aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_6X6_250) # read aruco_dict fs_read = cv.FileStorage(filename, cv.FileStorage_READ) aruco_dict.readDictionary(fs_read.root()) fs_read.release() # check equal self.assertEqual(aruco_dict.markerSize, 5) self.assertEqual(aruco_dict.maxCorrectionBits, 3) np.testing.assert_array_equal(aruco_dict.bytesList, markers_gold) finally: if os.path.exists(filename): os.remove(filename) def test_charuco_detector(self): aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_250) board_size = (3, 3) board = cv.aruco.CharucoBoard(board_size, 1.0, .8, aruco_dict) charuco_detector = cv.aruco.CharucoDetector(board) cell_size = 100 image = board.generateImage((cell_size*board_size[0], cell_size*board_size[1])) list_gold_corners = [] for i in range(1, board_size[0]): for j in range(1, board_size[1]): list_gold_corners.append((j*cell_size, i*cell_size)) gold_corners = np.array(list_gold_corners, dtype=np.float32) charucoCorners, charucoIds, markerCorners, markerIds = charuco_detector.detectBoard(image) self.assertEqual(len(charucoIds), 4) for i in range(0, 4): self.assertEqual(charucoIds[i], i) np.testing.assert_allclose(gold_corners, charucoCorners.reshape(-1, 2), 0.01, 0.1) def test_detect_diamonds(self): aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_6X6_250) board_size = (3, 3) board = cv.aruco.CharucoBoard(board_size, 1.0, .8, aruco_dict) charuco_detector = cv.aruco.CharucoDetector(board) cell_size = 120 image = board.generateImage((cell_size*board_size[0], cell_size*board_size[1])) list_gold_corners = [(cell_size, cell_size), (2*cell_size, cell_size), (2*cell_size, 2*cell_size), (cell_size, 2*cell_size)] gold_corners = np.array(list_gold_corners, dtype=np.float32) diamond_corners, diamond_ids, marker_corners, marker_ids = charuco_detector.detectDiamonds(image) self.assertEqual(diamond_ids.size, 4) self.assertEqual(marker_ids.size, 4) for i in range(0, 4): self.assertEqual(diamond_ids[0][0][i], i) np.testing.assert_allclose(gold_corners, np.array(diamond_corners, dtype=np.float32).reshape(-1, 2), 0.01, 0.1) # check no segfault when cameraMatrix or distCoeffs are not initialized def test_charuco_no_segfault_params(self): dictionary = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_1000) board = cv.aruco.CharucoBoard((10, 10), 0.019, 0.015, dictionary) charuco_parameters = cv.aruco.CharucoParameters() detector = cv.aruco.CharucoDetector(board) detector.setCharucoParameters(charuco_parameters) self.assertIsNone(detector.getCharucoParameters().cameraMatrix) self.assertIsNone(detector.getCharucoParameters().distCoeffs) def test_charuco_no_segfault_params_constructor(self): dictionary = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_1000) board = cv.aruco.CharucoBoard((10, 10), 0.019, 0.015, dictionary) charuco_parameters = cv.aruco.CharucoParameters() detector = cv.aruco.CharucoDetector(board, charucoParams=charuco_parameters) self.assertIsNone(detector.getCharucoParameters().cameraMatrix) self.assertIsNone(detector.getCharucoParameters().distCoeffs) # similar to C++ test CV_CharucoDetection.accuracy def test_charuco_detector_accuracy(self): iteration = 0 cameraMatrix = np.eye(3, 3, dtype=np.float64) imgSize = (500, 500) params = cv.aruco.DetectorParameters() params.minDistanceToBorder = 3 board = cv.aruco.CharucoBoard((4, 4), 0.03, 0.015, cv.aruco.getPredefinedDictionary(cv.aruco.DICT_6X6_250)) detector = cv.aruco.CharucoDetector(board, detectorParams=params) cameraMatrix[0, 0] = cameraMatrix[1, 1] = 600 cameraMatrix[0, 2] = imgSize[0] / 2 cameraMatrix[1, 2] = imgSize[1] / 2 # for different perspectives distCoeffs = np.zeros((5, 1), dtype=np.float64) for distance in [0.2, 0.4]: for yaw in range(-55, 51, 25): for pitch in range(-55, 51, 25): markerBorder = iteration % 2 + 1 iteration += 1 # create synthetic image img, rvec, tvec = projectCharucoBoard(board, cameraMatrix, yaw * pi / 180, pitch * pi / 180, distance, imgSize, markerBorder) params.markerBorderBits = markerBorder detector.setDetectorParameters(params) if (iteration % 2 != 0): charucoParameters = cv.aruco.CharucoParameters() charucoParameters.cameraMatrix = cameraMatrix charucoParameters.distCoeffs = distCoeffs detector.setCharucoParameters(charucoParameters) charucoCorners, charucoIds, corners, ids = detector.detectBoard(img) self.assertGreater(len(ids), 0) copyChessboardCorners = board.getChessboardCorners() copyChessboardCorners -= np.array(board.getRightBottomCorner()) / 2 projectedCharucoCorners, _ = cv.projectPoints(copyChessboardCorners, rvec, tvec, cameraMatrix, distCoeffs) if charucoIds is None: self.assertEqual(iteration, 46) continue for i in range(len(charucoIds)): currentId = charucoIds[i] self.assertLess(currentId, len(board.getChessboardCorners())) reprErr = cv.norm(charucoCorners[i] - projectedCharucoCorners[currentId]) self.assertLessEqual(reprErr, 5) def test_aruco_match_image_points(self): aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_50) board_size = (3, 4) board = cv.aruco.GridBoard(board_size, 5.0, 1.0, aruco_dict) aruco_corners = np.array(board.getObjPoints())[:, :, :2] aruco_ids = board.getIds() obj_points, img_points = board.matchImagePoints(aruco_corners, aruco_ids) aruco_corners = aruco_corners.reshape(-1, 2) self.assertEqual(aruco_corners.shape[0], obj_points.shape[0]) self.assertEqual(img_points.shape[0], obj_points.shape[0]) self.assertEqual(2, img_points.shape[2]) np.testing.assert_array_equal(aruco_corners, obj_points[:, :, :2].reshape(-1, 2)) def test_charuco_match_image_points(self): aruco_dict = cv.aruco.getPredefinedDictionary(cv.aruco.DICT_4X4_50) board_size = (3, 4) board = cv.aruco.CharucoBoard(board_size, 5.0, 1.0, aruco_dict) chessboard_corners = np.array(board.getChessboardCorners())[:, :2] chessboard_ids = board.getIds() obj_points, img_points = board.matchImagePoints(chessboard_corners, chessboard_ids) self.assertEqual(chessboard_corners.shape[0], obj_points.shape[0]) self.assertEqual(img_points.shape[0], obj_points.shape[0]) self.assertEqual(2, img_points.shape[2]) np.testing.assert_array_equal(chessboard_corners, obj_points[:, :, :2].reshape(-1, 2)) def test_draw_detected_markers(self): detected_points = [[[10, 10], [50, 10], [50, 50], [10, 50]]] img = np.zeros((60, 60), dtype=np.uint8) # add extra dimension in Python to create Nx4 Mat with 2 channels points1 = np.array(detected_points).reshape(-1, 4, 1, 2) img = cv.aruco.drawDetectedMarkers(img, points1, borderColor=255) # check that the marker borders are painted contours, _ = cv.findContours(img, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) self.assertEqual(len(contours), 1) self.assertEqual(img[10, 10], 255) self.assertEqual(img[50, 10], 255) self.assertEqual(img[50, 50], 255) self.assertEqual(img[10, 50], 255) # must throw Exception without extra dimension points2 = np.array(detected_points) with self.assertRaises(Exception): img = cv.aruco.drawDetectedMarkers(img, points2, borderColor=255) def test_draw_detected_charuco(self): detected_points = [[[10, 10], [50, 10], [50, 50], [10, 50]]] img = np.zeros((60, 60), dtype=np.uint8) # add extra dimension in Python to create Nx1 Mat with 2 channels points = np.array(detected_points).reshape(-1, 1, 2) img = cv.aruco.drawDetectedCornersCharuco(img, points, cornerColor=255) # check that the 4 charuco corners are painted contours, _ = cv.findContours(img, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) self.assertEqual(len(contours), 4) for contour in contours: center_x = round(np.average(contour[:, 0, 0])) center_y = round(np.average(contour[:, 0, 1])) center = [center_x, center_y] self.assertTrue(center in detected_points[0]) # must throw Exception without extra dimension points2 = np.array(detected_points) with self.assertRaises(Exception): img = cv.aruco.drawDetectedCornersCharuco(img, points2, borderColor=255) def test_draw_detected_diamonds(self): detected_points = [[[10, 10], [50, 10], [50, 50], [10, 50]]] img = np.zeros((60, 60), dtype=np.uint8) # add extra dimension in Python to create Nx4 Mat with 2 channels points = np.array(detected_points).reshape(-1, 4, 1, 2) img = cv.aruco.drawDetectedDiamonds(img, points, borderColor=255) # check that the diamonds borders are painted contours, _ = cv.findContours(img, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE) self.assertEqual(len(contours), 1) self.assertEqual(img[10, 10], 255) self.assertEqual(img[50, 10], 255) self.assertEqual(img[50, 50], 255) self.assertEqual(img[10, 50], 255) # must throw Exception without extra dimension points2 = np.array(detected_points) with self.assertRaises(Exception): img = cv.aruco.drawDetectedDiamonds(img, points2, borderColor=255) if __name__ == '__main__': NewOpenCVTests.bootstrap()