solvePnPRansac gives unexpected results
I'm running into a spot of unexpected behaviour from solvePnPRansac, one would expect if you calculate the rotation and translation vector using a dataset from 3D and 2D datapoints which were matched before that you'd be able to extract the 2D coordinates matching with the 3D ones again, sadly this doesn't seem to be the case when running the following minimal code:
import cv2
import numpy as np
f = 24
sx = 23.2
sy = 15.4
width = 6016
height = 4000
fx = width * f / sx
fy = height * f / sy
cx = width / 2
cy = height / 2
mtx = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]], dtype=np.float32)
objp = np.array([[336.2260, 638.2822, -131.7110], [292.7631, 637.8978, -136.6205], [292.4433, 518.9155, -136.4933], [500.7705, 517.8542, -137.2822], [430.0151, 610.0834, -161.7526], [364.9480, 610.3971, -161.5365], [502.4865, 635.9937, -137.2524], [364.1737, 545.6596, -161.4099], [429.0482, 545.2378, -161.5822], [396.7234, 577.5511, -131.6136]], dtype=np.float32)
imp = np.array([[2089, 1123],[1507, 1153],[1400, 2863],[4566, 2875],[3421, 1645],[2539, 1621],[4483, 1171],[2539, 2521],[3439, 2521],[2983, 1981]], dtype=np.float32)
dist = np.array([])
print(mtx)
print(objp)
print(imp)
_, rvecs, tvecs, inliers = cv2.solvePnPRansac(objp, imp, mtx, dist)
print(rvecs)
print(tvecs)
print(inliers)
imgpts, jac = cv2.projectPoints(objp, rvecs, tvecs, mtx, dist)
print(imgpts)
To be precise the output is the following:
Camera Matrix:
[[ 6.22344824e+03 0.00000000e+00 3.00800000e+03]
[ 0.00000000e+00 6.23376611e+03 2.00000000e+03]
[ 0.00000000e+00 0.00000000e+00 1.00000000e+00]]
3D Points
[[ 336.22601318 638.28222656 -131.71099854]
[ 292.76309204 637.89782715 -136.62049866]
[ 292.44329834 518.91552734 -136.49330139]
[ 500.77050781 517.85418701 -137.28219604]
[ 430.0151062 610.08337402 -161.75259399]
[ 364.94799805 610.39709473 -161.53649902]
[ 502.48651123 635.99371338 -137.25239563]
[ 364.17370605 545.65960693 -161.40989685]
[ 429.04818726 545.23779297 -161.5821991 ]
[ 396.72338867 577.55108643 -131.61360168]]
2D Points:
[[ 2089. 1123.]
[ 1507. 1153.]
[ 1400. 2863.]
[ 4566. 2875.]
[ 3421. 1645.]
[ 2539. 1621.]
[ 4483. 1171.]
[ 2539. 2521.]
[ 3439. 2521.]
[ 2983. 1981.]]
Rotation Vector:
[[-0.9784294 ]
[ 0.51393317]
[ 0.7867821 ]]
Translation Vector:
[[ -42.0280413 ]
[ -78.03000936]
[ 156.70873622]]
Inliers:
None
Calculated 2D points:
[[[ 7373.86523438 284.01651001]]
[[ 8017.08056641 448.40975952]]
[[ 7350.13916016 815.67822266]]
[[ 4649.390625 296.13134766]]
[[ 5951.33935547 517.70758057]]
[[ 6725.28710938 664.42297363]]
[[ 5423.21484375 71.22388458]]
[[ 6334.44677734 848.40484619]]
[[ 5543.67333984 675.48657227]]
[[ 6205.56494141 298.80780029]]]
So either I'm doing something horribly wrong, or this is a significant portion of unexpected behaviour. I also run into this issue when using the matlab interface (mexopencv).
also see: https://github.com/Itseez/opencv/issu...
Thank you, luckily I had that one figured out already as well by now. but sadly it doesn't really help me solve the wrong coordinates issue.I must say that using OpenCV is turning out to be rather unpleasant at this point in time.