Revision history [back]

unable to replicate fisheye.stereoRectify results in Python

I don't manage to rectify a fisheye stereo pair in Python, so I have recreated a simple script to replicate what is done in test_fisheye.cpp TEST_F(fisheyeTest, rectify).

I do (I think) the exact same operations and I have taken the _exact same input_ which is given to the stereoRectify method and then checked the output. It does not match. Can anybody help me to discover why?

In particular, in the test the results are

P1 = [552.8721387695351, 0, 316.1239882810687, 0; 0, 552.8721387695351, 247.7687370495324, 0; 0, 0, 1, 0]

P2 = [552.8721387695351, 0, 316.1239882810687, -54.88267970005029; 0, 552.8721387695351, 247.7687370495324, 0; 0, 0, 1, 0]

while with my script I get

P1 = [248.02709551, 0 608.5711385, 0; 0, 248.02709551, 385.1740417, 0; 0, 0, 1, 0]

P2 = [248.02709551, 0, 608.5711385, -24.62123676; 0, 248.02709551, 385.1740417, 0; 0, 0, 1, 0]

As a result, the rectification is completely wrong.

Here is what you get with test_fisheye.cpp (rectification_AB_000.png)

test fisheye

and here is what I get with my script.

my results

Here is my full python code (very simple)

import cv2 import numpy as np

 print cv2.__file__
print cv2.__version__
 basePath = '/home/davide/Code/opencv-3.3.1/opencv_extra/testdata/cv/cameracalibration/fisheye/calib-3_stereo_from_JY'
 --- load images
 img1 = cv2.imread(basePath+'/left/stereo_pair_000.jpg',0)
img2 = cv2.imread(basePath+'/right/stereo_pair_000.jpg',0)
 --- input
 R = np.array([
    [0.9975670008442493, 0.06969827764018387, 0.001492956999132114],
    [-0.06971182516232298, 0.9974824984553177, 0.01299718076641846],
    [-0.0005833173639831654, -0.01306963539388498, 0.9999144185236674]])
 t = np.array([-0.0992174, 0.00317418, 0.00018551])
 K = np.array([
    [558.478087865323, 0, 620.458515360843],
    [0, 560.506767351568, 381.939424848348],
    [ 0, 0, 1]])
 D = np.array([-0.0014613319981768, -0.00329861110580401, 0.00605760088590183, -0.00374209380722371])
 --- do the thing
 R1, R2, P1, P2, Q = cv2.fisheye.stereoRectify(K, D, K, D, (1280,800), R, t, flags=cv2.CALIB_ZERO_DISPARITY, balance=1.0, fov_scale=1.1) #
 map11, map12 = cv2.initUndistortRectifyMap(K, D, R1, P1, (1280,800), cv2.CV_32FC1);
map21, map22 = cv2.initUndistortRectifyMap(K, D, R2, P2, (1280,800), cv2.CV_32FC1);
 undistorted_rectified1 = cv2.remap(img1, map11, map12, cv2.INTER_LINEAR);
undistorted_rectified2 = cv2.remap(img2, map21, map22, cv2.INTER_LINEAR);
 --- output
 print 'R1 ', R1
print 'R2 ', R2
print 'P1 ', P1
print 'P2 ', P2
 joined = np.concatenate((undistorted_rectified1, undistorted_rectified2), 1);
 cv2.namedWindow('rectification', cv2.WINDOW_NORMAL);
cv2.imshow('rectification', joined)
 cv2.waitKey()

cv2.imwrite('/tmp/result.png', joined)

unable to replicate fisheye.stereoRectify results in Python

I don't manage to rectify a fisheye stereo pair in Python, so I have recreated a simple script to replicate what is done in test_fisheye.cpp TEST_F(fisheyeTest, rectify).

In particular, in the test the results are

P1 = [552.8721387695351, 0, 316.1239882810687, 0; 0, 552.8721387695351, 247.7687370495324, 0; 0, 0, 1, 0]

0] P2 = [552.8721387695351, 0, 316.1239882810687, -54.88267970005029; 0, 552.8721387695351, 247.7687370495324, 0; 0, 0, 1, 0]0]

while with my script I get

P1 = [248.02709551, 0 608.5711385, 0; 0, 248.02709551, 385.1740417, 0; 0, 0, 1, 0]

P2 = [248.02709551, 0, 608.5711385, -24.62123676; 0, 248.02709551, 385.1740417, 0; 0, 0, 1, 0]0]

As a result, the rectification is completely wrong.

Here is what you get with test_fisheye.cpp (rectification_AB_000.png)

and here is what I get with my script.

Here is my full python code (very simple)

import cv2 import numpy as np
np print cv2.__file__ print cv2.__version__ cv2.__version__ basePath = '/home/davide/Code/opencv-3.3.1/opencv_extra/testdata/cv/cameracalibration/fisheye/calib-3_stereo_from_JY' '/home/davide/Code/opencv-3.3.1/opencv_extra/testdata/cv/cameracalibration/fisheye/calib-3_stereo_from_JY' # --- load images images img1 = cv2.imread(basePath+'/left/stereo_pair_000.jpg',0) img2 = cv2.imread(basePath+'/right/stereo_pair_000.jpg',0) cv2.imread(basePath+'/right/stereo_pair_000.jpg',0) # --- input input R = np.array([ [0.9975670008442493, 0.06969827764018387, 0.001492956999132114], [-0.06971182516232298, 0.9974824984553177, 0.01299718076641846], [-0.0005833173639831654, -0.01306963539388498, 0.9999144185236674]]) 0.9999144185236674]]) t = np.array([-0.0992174, 0.00317418, 0.00018551]) 0.00018551]) K = np.array([ [558.478087865323, 0, 620.458515360843], [0, 560.506767351568, 381.939424848348], [ 0, 0, 1]]) 1]]) D = np.array([-0.0014613319981768, -0.00329861110580401, 0.00605760088590183, -0.00374209380722371]) -0.00374209380722371]) # --- do the thing thing R1, R2, P1, P2, Q = cv2.fisheye.stereoRectify(K, D, K, D, (1280,800), R, t, flags=cv2.CALIB_ZERO_DISPARITY, balance=1.0, fov_scale=1.1) # # map11, map12 = cv2.initUndistortRectifyMap(K, D, R1, P1, (1280,800), cv2.CV_32FC1); map21, map22 = cv2.initUndistortRectifyMap(K, D, R2, P2, (1280,800), cv2.CV_32FC1); cv2.CV_32FC1); undistorted_rectified1 = cv2.remap(img1, map11, map12, cv2.INTER_LINEAR); undistorted_rectified2 = cv2.remap(img2, map21, map22, cv2.INTER_LINEAR); cv2.INTER_LINEAR); # --- output output print 'R1 ', R1 print 'R2 ', R2 print 'P1 ', P1 print 'P2 ', P2 P2 joined = np.concatenate((undistorted_rectified1, undistorted_rectified2), 1); 1); cv2.namedWindow('rectification', cv2.WINDOW_NORMAL); cv2.imshow('rectification', joined) cv2.waitKey()
joined) cv2.waitKey() cv2.imwrite('/tmp/result.png', joined)