73 lines
2.3 KiB
Python
73 lines
2.3 KiB
Python
#!/usr/bin/env python
|
|
|
|
'''
|
|
camera calibration for distorted images with chess board samples
|
|
reads distorted images, calculates the calibration and write undistorted images
|
|
'''
|
|
|
|
# Python 2/3 compatibility
|
|
from __future__ import print_function
|
|
|
|
import numpy as np
|
|
import cv2 as cv
|
|
|
|
from tests_common import NewOpenCVTests
|
|
|
|
class calibration_test(NewOpenCVTests):
|
|
|
|
def test_calibration(self):
|
|
img_names = []
|
|
for i in range(1, 15):
|
|
if i < 10:
|
|
img_names.append('samples/data/left0{}.jpg'.format(str(i)))
|
|
elif i != 10:
|
|
img_names.append('samples/data/left{}.jpg'.format(str(i)))
|
|
|
|
square_size = 1.0
|
|
pattern_size = (9, 6)
|
|
pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32)
|
|
pattern_points[:, :2] = np.indices(pattern_size).T.reshape(-1, 2)
|
|
pattern_points *= square_size
|
|
|
|
obj_points = []
|
|
img_points = []
|
|
h, w = 0, 0
|
|
for fn in img_names:
|
|
img = self.get_sample(fn, 0)
|
|
if img is None:
|
|
continue
|
|
|
|
h, w = img.shape[:2]
|
|
found, corners = cv.findChessboardCorners(img, pattern_size)
|
|
if found:
|
|
term = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_COUNT, 30, 0.1)
|
|
cv.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
|
|
|
|
if not found:
|
|
continue
|
|
|
|
img_points.append(corners.reshape(-1, 2))
|
|
obj_points.append(pattern_points)
|
|
|
|
# calculate camera distortion
|
|
rms, camera_matrix, dist_coefs, _rvecs, _tvecs = cv.calibrateCamera(obj_points, img_points, (w, h), None, None, flags = 0)
|
|
|
|
eps = 0.01
|
|
normCamEps = 10.0
|
|
normDistEps = 0.05
|
|
|
|
cameraMatrixTest = [[ 532.80992189, 0., 342.4952186 ],
|
|
[ 0., 532.93346422, 233.8879292 ],
|
|
[ 0., 0., 1. ]]
|
|
|
|
distCoeffsTest = [ -2.81325576e-01, 2.91130406e-02,
|
|
1.21234330e-03, -1.40825372e-04, 1.54865844e-01]
|
|
|
|
self.assertLess(abs(rms - 0.196334638034), eps)
|
|
self.assertLess(cv.norm(camera_matrix - cameraMatrixTest, cv.NORM_L1), normCamEps)
|
|
self.assertLess(cv.norm(dist_coefs - distCoeffsTest, cv.NORM_L1), normDistEps)
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
NewOpenCVTests.bootstrap()
|