Opencv Camera Calibration Undistortion

Question

I want to use the Camera Calibration Tool on OpenCV on a very specific setting, however, i seem to make one or more Logic Mistakes. I actually don't have a real camera, but a simulated one.

I followed the official Calibration Tutorial

I have a distorted Image (distorted by the simulation), and i have the original Image. Furthermore i have a "map" and i mean by that, that i do know, how points or mapped from the original onto the distorted image

What i now tried is replacing cv2.findChessboardCorners with "my map". objpoints are from my undistorted image in 3D (with fake z-coordinate = 0) imgpoints are the same points from the distorted image in 2D.

What i did in order to make it reproducable, i hardcoded some points into the code. I think, everybody who runs the code, can see my problem. Something is very wrong with my map, i think, but i am not sure.

#%%

import numpy as np
import cv2 as cv
import pandas as pd
import matplotlib.pyplot as plt

# Read Image
img = cv.imread("std.jpg")
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

width = gray.shape[1]
height = gray.shape[0]


#helper

def plotImage(im):
    plt.imshow(im, cmap="gray")
    plt.xlim(0, width)
    plt.ylim(0, height)
    plt.show()



def plotImageAndPoints(im, x, y):
    plt.imshow(im, cmap="gray")
    plt.scatter(x, y, c="red", s=16)
    plt.xlim(0, width)
    plt.ylim(0, height)
    plt.show()


ob=np.array([[ 20., 600.,   0.],
       [200., 570.,   0.],
       [380., 540.,   0.],
       [140., 480.,   0.],
       [320., 450.,   0.],
       [ 80., 390.,   0.],
       [260., 360.,   0.],
       [ 20., 300.,   0.],
       [200., 270.,   0.],
       [380., 240.,   0.],
       [140., 180.,   0.],
       [320., 150.,   0.],
       [ 80.,  90.,   0.],
       [260.,  60.,   0.],
       [ 20.,   0.,   0.]])


# for OpenCV
objp=[ob.astype(np.float32)]


ip =np.array([[ 54.0018, 543.3303],
       [200.    , 586.7835],
       [358.1802, 510.9069],
       [125.5172, 523.4484],
       [338.0666, 472.5831],
       [ 51.0344, 411.7242],
       [291.6206, 391.6206],
       [  8.811 , 300.    ],
       [200.    , 248.7282],
       [388.4496, 237.1836],
       [116.213 , 132.426 ],
       [338.0666, 127.4169],
       [ 74.367 ,  80.1423],
       [265.691 ,  37.2363],
       [ 54.0018,  56.6697]])


#for OpenCV
imgp =[ip.astype(np.float32)]



# Calibration
#ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)

ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objp, imgp, gray.shape[::-1], None, None)

# Displaying required output
print(" Camera matrix:")
print(mtx)

print("\n Distortion coefficient:")
print(dist)

print("\n Rotation Vectors:")
print(rvecs)

print("\n Translation Vectors:")
print(tvecs)

# undistort


imgdist = cv.imread("dist.jpg")


plotImageAndPoints(gray, ob[:,1], ob[:, 0])

plotImageAndPoints(imgdist, ip[:,1], ip[:, 0])


dst = cv.undistort(imgdist, mtx, dist, None)
cv.imwrite('calibresult.png', dst)

distorted with mapping points

undistorted with mapping points

The result i get is basically the distorted image again, not the undistorted.