Merge branch 4.x

2026-07-29 07:13:02 +04:00 · 2023-01-09 11:08:02 +00:00
parent 8a62b03761 2ab46d9553
commit 593a376566
880 changed files with 83958 additions and 9368 deletions
@@ -0,0 +1,146 @@
+#!/usr/bin/env python
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import os, tempfile, numpy as np
+
+import cv2 as cv
+
+from tests_common import NewOpenCVTests
+
+class aruco_objdetect_test(NewOpenCVTests):
+
+    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_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)
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()
@@ -43,10 +43,10 @@ class qrcode_detector_test(NewOpenCVTests):
        retval, decoded_data, points, straight_qrcode = detector.detectAndDecodeMulti(img)
        self.assertTrue(retval)
        self.assertEqual(len(decoded_data), 6)
-        self.assertEqual(decoded_data[0], "TWO STEPS FORWARD")
-        self.assertEqual(decoded_data[1], "EXTRA")
-        self.assertEqual(decoded_data[2], "SKIP")
-        self.assertEqual(decoded_data[3], "STEP FORWARD")
-        self.assertEqual(decoded_data[4], "STEP BACK")
-        self.assertEqual(decoded_data[5], "QUESTION")
+        self.assertTrue("TWO STEPS FORWARD" in decoded_data)
+        self.assertTrue("EXTRA" in decoded_data)
+        self.assertTrue("SKIP" in decoded_data)
+        self.assertTrue("STEP FORWARD" in decoded_data)
+        self.assertTrue("STEP BACK" in decoded_data)
+        self.assertTrue("QUESTION" in decoded_data)
        self.assertEqual(points.shape, (6, 4, 2))