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Merge pull request #29175 from asmorkalov:as/geometry2
Geometry module #29175 OpenCV Contrib: https://github.com/opencv/opencv_contrib/pull/4129 CI changes: https://github.com/opencv/ci-gha-workflow/pull/313 Continues - https://github.com/opencv/opencv/pull/28804 - https://github.com/opencv/opencv/pull/29101 - https://github.com/opencv/opencv/pull/29108 - https://github.com/opencv/opencv/pull/28810 Todo for followup PRs: - [x] Rename doxygen groups - [x] Fix JS modules layout and whitelists - [ ] Sort tutorials code/snippets ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Alexander Smorkalov
committed by
GitHub
GitHub
parent
14a475aa0b
commit
59218f9edd
@@ -0,0 +1,46 @@
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#!/usr/bin/env python
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# Python 2/3 compatibility
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from __future__ import print_function
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import os, numpy
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import math
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import unittest
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import cv2 as cv
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from tests_common import NewOpenCVTests
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class raster_test(NewOpenCVTests):
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def test_loadCloud(self):
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fin = self.find_file("pointcloudio/orig.obj")
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points, normals, colors = cv.loadPointCloud(fin)
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if points.shape != (8, 1, 3):
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self.fail('point array should be 8x1x3')
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if normals.shape != (6, 1, 3):
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self.fail('normals array should be 6x1x3')
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if colors.shape != (8, 1, 3):
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self.fail('colors array should be 8x1x3')
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def test_loadMesh(self):
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fin = self.find_file("pointcloudio/orig.obj")
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points, indices, normals, colors, texCoords = cv.loadMesh(fin)
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goodShapes = [(1, 18, 3), (18, 1, 3)]
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errorMsg = "%s array should be 18x1x3 or 1x18x3"
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for a, s in [(points, 'points'), (normals, 'normals'), (colors, 'colors')]:
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if a.shape not in goodShapes:
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self.fail(errorMsg % s)
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if texCoords.shape not in [(1, 18, 2), (18, 1, 2), (18, 2)]:
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self.fail('texture coordinates array should be 1x18x2 or 18x1x2')
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if isinstance(indices, numpy.ndarray):
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if indices.shape not in [(1, 6, 3), (6, 1, 3)]:
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self.fail('indices array should be 1x6x3 or 6x1x3')
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elif isinstance(indices, list) or isinstance(indices, tuple):
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for i in indices:
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if len(indices) != 6 or i.shape != (1, 3):
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self.fail('indices array should be 1x6x3 or 6x1x3')
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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@@ -0,0 +1,31 @@
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#!/usr/bin/env python
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import os
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import numpy as np
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import math
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import unittest
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import cv2 as cv
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from tests_common import NewOpenCVTests
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class octree_test(NewOpenCVTests):
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def test_octree_basic_test(self):
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pointCloudSize = 1000
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resolution = 0.0001
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scale = 1 << 20
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pointCloud = np.random.randint(-scale, scale, size=(pointCloudSize, 3)) * (10.0 / scale)
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pointCloud = pointCloud.astype(np.float32)
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octree = cv.Octree_createWithResolution(resolution, pointCloud)
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restPoint = np.random.randint(-scale, scale, size=(1, 3)) * (10.0 / scale)
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restPoint = [restPoint[0, 0], restPoint[0, 1], restPoint[0, 2]]
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self.assertTrue(octree.isPointInBound(restPoint))
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self.assertFalse(octree.deletePoint(restPoint))
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self.assertTrue(octree.insertPoint(restPoint))
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self.assertTrue(octree.deletePoint(restPoint))
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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@@ -0,0 +1,88 @@
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#!/usr/bin/env python
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import numpy as np
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import cv2 as cv
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from tests_common import NewOpenCVTests
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class odometry_test(NewOpenCVTests):
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def commonOdometryTest(self, needRgb, otype, algoType, useFrame):
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depth = self.get_sample('cv/rgbd/depth.png', cv.IMREAD_ANYDEPTH).astype(np.float32)
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if needRgb:
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rgb = self.get_sample('cv/rgbd/rgb.png', cv.IMREAD_ANYCOLOR)
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radian = np.radians(1)
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Rt_warp = np.array(
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[[np.cos(radian), -np.sin(radian), 0],
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[np.sin(radian), np.cos(radian), 0],
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[0, 0, 1]], dtype=np.float32
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)
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Rt_curr = np.array(
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[[np.cos(radian), -np.sin(radian), 0, 0],
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[np.sin(radian), np.cos(radian), 0, 0],
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[0, 0, 1, 0],
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[0, 0, 0, 1]], dtype=np.float32
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)
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Rt_res = np.zeros((4, 4))
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if otype is not None:
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settings = cv.OdometrySettings()
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odometry = cv.Odometry(otype, settings, algoType)
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else:
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odometry = cv.Odometry()
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warped_depth = cv.warpPerspective(depth, Rt_warp, (640, 480))
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if needRgb:
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warped_rgb = cv.warpPerspective(rgb, Rt_warp, (640, 480))
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if useFrame:
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if needRgb:
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srcFrame = cv.OdometryFrame(depth, rgb)
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dstFrame = cv.OdometryFrame(warped_depth, warped_rgb)
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else:
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srcFrame = cv.OdometryFrame(depth)
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dstFrame = cv.OdometryFrame(warped_depth)
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odometry.prepareFrames(srcFrame, dstFrame)
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isCorrect = odometry.compute(srcFrame, dstFrame, Rt_res)
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else:
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if needRgb:
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isCorrect = odometry.compute(depth, rgb, warped_depth, warped_rgb, Rt_res)
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else:
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isCorrect = odometry.compute(depth, warped_depth, Rt_res)
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res = np.absolute(Rt_curr - Rt_res).sum()
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eps = 0.15
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self.assertLessEqual(res, eps)
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self.assertTrue(isCorrect)
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def test_OdometryDefault(self):
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self.commonOdometryTest(False, None, None, False)
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def test_OdometryDefaultFrame(self):
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self.commonOdometryTest(False, None, None, True)
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def test_OdometryDepth(self):
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self.commonOdometryTest(False, cv.OdometryType_DEPTH, cv.OdometryAlgoType_COMMON, False)
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def test_OdometryDepthFast(self):
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self.commonOdometryTest(False, cv.OdometryType_DEPTH, cv.OdometryAlgoType_FAST, False)
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def test_OdometryDepthFrame(self):
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self.commonOdometryTest(False, cv.OdometryType_DEPTH, cv.OdometryAlgoType_COMMON, True)
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def test_OdometryDepthFastFrame(self):
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self.commonOdometryTest(False, cv.OdometryType_DEPTH, cv.OdometryAlgoType_FAST, True)
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def test_OdometryRGB(self):
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self.commonOdometryTest(True, cv.OdometryType_RGB, cv.OdometryAlgoType_COMMON, False)
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def test_OdometryRGBFrame(self):
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self.commonOdometryTest(True, cv.OdometryType_RGB, cv.OdometryAlgoType_COMMON, True)
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def test_OdometryRGB_Depth(self):
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self.commonOdometryTest(True, cv.OdometryType_RGB_DEPTH, cv.OdometryAlgoType_COMMON, False)
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def test_OdometryRGB_DepthFrame(self):
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self.commonOdometryTest(True, cv.OdometryType_RGB_DEPTH, cv.OdometryAlgoType_COMMON, True)
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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@@ -0,0 +1,113 @@
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#!/usr/bin/env python
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# Python 2/3 compatibility
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from __future__ import print_function
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import os, numpy
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import math
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import unittest
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import cv2 as cv
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from tests_common import NewOpenCVTests
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def lookAtMatrixCal(position, lookat, upVector):
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tmp = position - lookat
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norm = numpy.linalg.norm(tmp)
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w = tmp / norm
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tmp = numpy.cross(upVector, w)
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norm = numpy.linalg.norm(tmp)
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u = tmp / norm
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v = numpy.cross(w, u)
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res = numpy.array([
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[u[0], u[1], u[2], 0],
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[v[0], v[1], v[2], 0],
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[w[0], w[1], w[2], 0],
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[0, 0, 0, 1.0]
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], dtype=numpy.float32)
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translate = numpy.array([
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[1.0, 0, 0, -position[0]],
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[0, 1.0, 0, -position[1]],
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[0, 0, 1.0, -position[2]],
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[0, 0, 0, 1.0]
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], dtype=numpy.float32)
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res = numpy.matmul(res, translate)
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return res
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class raster_test(NewOpenCVTests):
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def prepareData(self):
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self.vertices = numpy.array([
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[ 2.0, 0.0, -2.0],
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[ 0.0, -6.0, -2.0],
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[-2.0, 0.0, -2.0],
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[ 3.5, -1.0, -5.0],
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[ 2.5, -2.5, -5.0],
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[-1.0, 1.0, -5.0],
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[-6.5, -1.0, -3.0],
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[-2.5, -2.0, -3.0],
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[ 1.0, 1.0, -5.0],
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], dtype=numpy.float32)
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self.indices = numpy.array([ [0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=int)
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col1 = [ 185.0, 238.0, 217.0 ]
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col2 = [ 238.0, 217.0, 185.0 ]
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col3 = [ 238.0, 10.0, 150.0 ]
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self.colors = numpy.array([
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col1, col2, col3,
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col2, col3, col1,
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col3, col1, col2,
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], dtype=numpy.float32)
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self.colors = self.colors / 255.0
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self.zNear = 0.1
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self.zFar = 50.0
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self.fovy = 45.0 * math.pi / 180.0
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position = numpy.array([0.0, 0.0, 5.0], dtype=numpy.float32)
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lookat = numpy.array([0.0, 0.0, 0.0], dtype=numpy.float32)
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upVector = numpy.array([0.0, 1.0, 0.0], dtype=numpy.float32)
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self.cameraPose = lookAtMatrixCal(position, lookat, upVector)
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self.depth_buf = numpy.ones((240, 320), dtype=numpy.float32) * self.zFar
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self.color_buf = numpy.zeros((240, 320, 3), dtype=numpy.float32)
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self.settings = cv.TriangleRasterizeSettings().setShadingType(cv.RASTERIZE_SHADING_SHADED)
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self.settings = self.settings.setCullingMode(cv.RASTERIZE_CULLING_NONE)
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def compareResults(self, needRgb, needDepth):
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if needDepth:
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depth = self.get_sample('rendering/depth_image_Clipping_320x240_CullNone.png', cv.IMREAD_ANYDEPTH).astype(numpy.float32)
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depthFactor = 1000.0
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diff = depth/depthFactor - self.depth_buf
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norm = numpy.linalg.norm(diff)
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self.assertLessEqual(norm, 356.0)
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if needRgb:
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rgb = self.get_sample('rendering/example_image_Clipping_320x240_CullNone_Shaded.png', cv.IMREAD_ANYCOLOR)
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diff = rgb/255.0 - self.color_buf
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norm = numpy.linalg.norm(diff)
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self.assertLessEqual(norm, 11.62)
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def test_rasterizeBoth(self):
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self.prepareData()
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self.color_buf, self.depth_buf = cv.triangleRasterize(self.vertices, self.indices, self.colors, self.color_buf, self.depth_buf,
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self.cameraPose, self.fovy, self.zNear, self.zFar, self.settings)
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self.compareResults(needRgb=True, needDepth=True)
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def test_rasterizeDepth(self):
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self.prepareData()
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self.depth_buf = cv.triangleRasterizeDepth(self.vertices, self.indices, self.depth_buf,
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self.cameraPose, self.fovy, self.zNear, self.zFar, self.settings)
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self.compareResults(needRgb=False, needDepth=True)
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def test_rasterizeColor(self):
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self.prepareData()
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self.color_buf = cv.triangleRasterizeColor(self.vertices, self.indices, self.colors, self.color_buf,
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self.cameraPose, self.fovy, self.zNear, self.zFar, self.settings)
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self.compareResults(needRgb=True, needDepth=False)
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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@@ -0,0 +1,43 @@
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#!/usr/bin/env python
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# Python 2/3 compatibility
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from __future__ import print_function
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import os, numpy
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import unittest
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import cv2 as cv
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from tests_common import NewOpenCVTests
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class rgbd_test(NewOpenCVTests):
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def test_computeRgbdPlane(self):
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depth_image = self.get_sample('cv/rgbd/depth.png', cv.IMREAD_ANYDEPTH)
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if depth_image is None:
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raise unittest.SkipTest("Missing files with test data")
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K = numpy.array([[525, 0, 320.5], [0, 525, 240.5], [0, 0, 1]])
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points3d = cv.depthTo3d(depth_image, K)
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normals = cv.RgbdNormals_create(480, 640, cv.CV_32F, K).apply(points3d)
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_, planes_coeff = cv.findPlanes(points3d, normals, numpy.array([]), numpy.array([]), 40, 1600, 0.01, 0, 0, 0, cv.RGBD_PLANE_METHOD_DEFAULT)
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planes_coeff_expected = \
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numpy.asarray([[[-0.02447728, -0.8678335 , -0.49625182, 4.02800846]],
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[[-0.05055107, -0.86144137, -0.50533485, 3.95456314]],
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[[-0.03294908, -0.86964548, -0.49257591, 3.97052431]],
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[[-0.02886586, -0.87153459, -0.48948362, 7.77550507]],
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[[-0.04455929, -0.87659335, -0.47916424, 3.93200684]],
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[[-0.21514639, 0.18835169, -0.95824611, 7.59479475]],
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[[-0.01006953, -0.86679155, -0.49856904, 4.01355648]],
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[[-0.00876531, -0.87571168, -0.48275498, 3.96768975]],
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[[-0.06395926, -0.86951321, -0.48975089, 4.08618736]],
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[[-0.01403128, -0.87593341, -0.48222789, 7.74559402]],
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[[-0.01143177, -0.87495202, -0.4840748 , 7.75355816]]],
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dtype=numpy.float32)
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eps = 0.05
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self.assertLessEqual(cv.norm(planes_coeff, planes_coeff_expected, cv.NORM_L2), eps)
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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+64
@@ -0,0 +1,64 @@
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#!/usr/bin/env python
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# Python 2/3 compatibility
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from __future__ import print_function
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import numpy as np
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import cv2 as cv
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from tests_common import NewOpenCVTests
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class solvepnp_test(NewOpenCVTests):
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def test_regression_16040(self):
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obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
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img_points = np.array(
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[[700, 400], [700, 600], [900, 600], [900, 400]], dtype=np.float32
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)
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cameraMatrix = np.array(
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[[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
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)
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distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
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r = np.array([], dtype=np.float32)
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x, r, t, e = cv.solvePnPGeneric(
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obj_points, img_points, cameraMatrix, distCoeffs, reprojectionError=r
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)
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def test_regression_16040_2(self):
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obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
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img_points = np.array(
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[[[700, 400], [700, 600], [900, 600], [900, 400]]], dtype=np.float32
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)
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cameraMatrix = np.array(
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[[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
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)
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distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
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r = np.array([], dtype=np.float32)
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x, r, t, e = cv.solvePnPGeneric(
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obj_points, img_points, cameraMatrix, distCoeffs, reprojectionError=r
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)
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def test_regression_16049(self):
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obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
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img_points = np.array(
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[[[700, 400], [700, 600], [900, 600], [900, 400]]], dtype=np.float32
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)
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|
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cameraMatrix = np.array(
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[[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
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)
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distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
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x, r, t, e = cv.solvePnPGeneric(
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obj_points, img_points, cameraMatrix, distCoeffs
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)
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if e is None:
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# noArray() is supported, see https://github.com/opencv/opencv/issues/16049
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pass
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else:
|
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eDump = cv.utils.dumpInputArray(e)
|
||||
self.assertEqual(eDump, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=1 dims(-1)=2 size(-1)=1x1 type(-1)=CV_32FC1")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
NewOpenCVTests.bootstrap()
|
||||
@@ -0,0 +1,123 @@
|
||||
import numpy as np
|
||||
import cv2 as cv
|
||||
|
||||
from tests_common import NewOpenCVTests
|
||||
|
||||
class volume_test(NewOpenCVTests):
|
||||
def test_VolumeDefault(self):
|
||||
depthPath = 'cv/rgbd/depth.png'
|
||||
depth = self.get_sample(depthPath, cv.IMREAD_ANYDEPTH).astype(np.float32)
|
||||
if depth.size <= 0:
|
||||
raise Exception('Failed to load depth file: %s' % depthPath)
|
||||
|
||||
Rt = np.eye(4)
|
||||
volume = cv.Volume()
|
||||
volume.integrate(depth, Rt)
|
||||
|
||||
size = (480, 640, 4)
|
||||
points = np.zeros(size, np.float32)
|
||||
normals = np.zeros(size, np.float32)
|
||||
|
||||
Kraycast = np.array([[525. , 0. , 319.5],
|
||||
[ 0. , 525. , 239.5],
|
||||
[ 0. , 0. , 1. ]])
|
||||
|
||||
volume.raycastEx(Rt, size[0], size[1], Kraycast, points, normals)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
|
||||
volume.raycast(Rt, points, normals)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
|
||||
def test_VolumeTSDF(self):
|
||||
depthPath = 'cv/rgbd/depth.png'
|
||||
depth = self.get_sample(depthPath, cv.IMREAD_ANYDEPTH).astype(np.float32)
|
||||
if depth.size <= 0:
|
||||
raise Exception('Failed to load depth file: %s' % depthPath)
|
||||
|
||||
Rt = np.eye(4)
|
||||
|
||||
settings = cv.VolumeSettings(cv.VolumeType_TSDF)
|
||||
volume = cv.Volume(cv.VolumeType_TSDF, settings)
|
||||
volume.integrate(depth, Rt)
|
||||
|
||||
size = (480, 640, 4)
|
||||
points = np.zeros(size, np.float32)
|
||||
normals = np.zeros(size, np.float32)
|
||||
|
||||
Kraycast = settings.getCameraRaycastIntrinsics()
|
||||
volume.raycastEx(Rt, size[0], size[1], Kraycast, points, normals)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
|
||||
volume.raycast(Rt, points, normals)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
|
||||
def test_VolumeHashTSDF(self):
|
||||
depthPath = 'cv/rgbd/depth.png'
|
||||
depth = self.get_sample(depthPath, cv.IMREAD_ANYDEPTH).astype(np.float32)
|
||||
if depth.size <= 0:
|
||||
raise Exception('Failed to load depth file: %s' % depthPath)
|
||||
|
||||
Rt = np.eye(4)
|
||||
settings = cv.VolumeSettings(cv.VolumeType_HashTSDF)
|
||||
volume = cv.Volume(cv.VolumeType_HashTSDF, settings)
|
||||
volume.integrate(depth, Rt)
|
||||
|
||||
size = (480, 640, 4)
|
||||
points = np.zeros(size, np.float32)
|
||||
normals = np.zeros(size, np.float32)
|
||||
|
||||
Kraycast = settings.getCameraRaycastIntrinsics()
|
||||
volume.raycastEx(Rt, size[0], size[1], Kraycast, points, normals)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
|
||||
volume.raycast(Rt, points, normals)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
|
||||
def test_VolumeColorTSDF(self):
|
||||
depthPath = 'cv/rgbd/depth.png'
|
||||
rgbPath = 'cv/rgbd/rgb.png'
|
||||
depth = self.get_sample(depthPath, cv.IMREAD_ANYDEPTH).astype(np.float32)
|
||||
rgb = self.get_sample(rgbPath, cv.IMREAD_ANYCOLOR).astype(np.float32)
|
||||
|
||||
if depth.size <= 0:
|
||||
raise Exception('Failed to load depth file: %s' % depthPath)
|
||||
if rgb.size <= 0:
|
||||
raise Exception('Failed to load RGB file: %s' % rgbPath)
|
||||
|
||||
Rt = np.eye(4)
|
||||
settings = cv.VolumeSettings(cv.VolumeType_ColorTSDF)
|
||||
volume = cv.Volume(cv.VolumeType_ColorTSDF, settings)
|
||||
volume.integrateColor(depth, rgb, Rt)
|
||||
|
||||
size = (480, 640, 4)
|
||||
points = np.zeros(size, np.float32)
|
||||
normals = np.zeros(size, np.float32)
|
||||
colors = np.zeros(size, np.float32)
|
||||
|
||||
Kraycast = settings.getCameraRaycastIntrinsics()
|
||||
volume.raycastExColor(Rt, size[0], size[1], Kraycast, points, normals, colors)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
|
||||
volume.raycastColor(Rt, points, normals, colors)
|
||||
|
||||
self.assertEqual(points.shape, size)
|
||||
self.assertEqual(points.shape, normals.shape)
|
||||
self.assertEqual(points.shape, colors.shape)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
NewOpenCVTests.bootstrap()
|
||||
Reference in New Issue
Block a user