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67a3d35b4e
Add multiview calibration [GSOC 2022]
### Pull Request Readiness Checklist
- [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
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
The usage tutorial is on Google Docs following this link: https://docs.google.com/document/d/1k6YpD0tpSVqnVnvU2nzE34K3cp_Po6mLWqXV06CUHwQ/edit?usp=sharing
72 lines
3.0 KiB
Python
72 lines
3.0 KiB
Python
# This file is part of OpenCV project.
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# It is subject to the license terms in the LICENSE file found in the top-level directory
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# of this distribution and at http://opencv.org/license.html.
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import numpy as np
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import math
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import cv2 as cv
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import json
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class RandGen:
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def __init__(self, seed = 0):
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self.rand_gen = np.random.RandomState(seed)
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def randRange(self, min_v, max_v):
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return self.rand_gen.rand(1).item() * (max_v - min_v) + min_v
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def project(K, R, t, dist, pts_3d, is_fisheye):
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if is_fisheye:
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pts_2d = cv.fisheye.projectPoints(pts_3d.T[None,:], cv.Rodrigues(R)[0], t, K, dist.flatten())[0].reshape(-1,2).T
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else:
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pts_2d = cv.projectPoints(pts_3d, R, t, K, dist)[0].reshape(-1,2).T
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return pts_2d
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def projectCamera(camera, pts_3d):
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return project(camera.K, camera.R, camera.t, camera.distortion, pts_3d, camera.is_fisheye)
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def eul2rot(theta): # [x y z]
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# https://learnopencv.com/rotation-matrix-to-euler-angles/
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R_x = np.array([[1, 0, 0 ],
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[0, math.cos(theta[0]), -math.sin(theta[0]) ],
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[0, math.sin(theta[0]), math.cos(theta[0]) ]])
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R_y = np.array([[math.cos(theta[1]), 0, math.sin(theta[1]) ],
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[0, 1, 0 ],
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[-math.sin(theta[1]), 0, math.cos(theta[1]) ]])
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R_z = np.array([[math.cos(theta[2]), -math.sin(theta[2]), 0],
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[math.sin(theta[2]), math.cos(theta[2]), 0],
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[0, 0, 1]])
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return np.dot(R_z, np.dot(R_y, R_x))
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def insideImageMask(pts, w, h):
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return np.logical_and(np.logical_and(pts[0] < w, pts[1] < h), np.logical_and(pts[0] > 0, pts[1] > 0))
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def insideImage(pts, w, h):
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return insideImageMask(pts, w, h).sum()
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def areAllInsideImage(pts, w, h):
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return insideImageMask(pts, w, h).all()
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def writeMatrix(file, M):
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for i in range(M.shape[0]):
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for j in range(M.shape[1]):
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file.write(str(M[i,j]) + ('\n' if j == M.shape[1]-1 else ' '))
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def saveKDRT(cameras, fname):
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file = open(fname, 'w')
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for cam in cameras:
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writeMatrix(file, cam.K)
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writeMatrix(file, cam.distortion)
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writeMatrix(file, cam.R)
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writeMatrix(file, cam.t)
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def export2JSON(pattern_points, image_points, image_sizes, is_fisheye, json_file):
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image_points = image_points.transpose(1,0,3,2)
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image_points_list = [[] for i in range(len(image_sizes))]
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for c in range(len(image_points)):
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for f in range(len(image_points[c])):
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if areAllInsideImage(image_points[c][f], image_sizes[c][0], image_sizes[c][1]):
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image_points_list[c].append(image_points[c][f].tolist())
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else:
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image_points_list[c].append([])
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json.dump({'object_points': pattern_points.tolist(), 'image_points': image_points_list, 'image_sizes': image_sizes, 'is_fisheye': is_fisheye}, open(json_file, 'w'))
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