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License: MIT License
An implementation of Direct Linear Transform for 3D to 2D mapping.
License: MIT License
The np.std() function computes the standard deviation over all the entries of the flattened matrix. So for instance, given an array a = np.array([[1,2],[3,4],[5,6]])
, the std is computed over the 6 entries rather than the 3 points.
I think this line of code in the DLTcalib() function is the correct template to compute the mean distance: err = np.sqrt(np.mean(np.sum((uv2[0:2, :].T - uv)**2, 1))
.
After performing SVD, my V looks like this:
[[ 1.55354266e-01 1.39402993e-01 0.00000000e+00 -3.03476192e-01
-3.03786432e-02 -2.86957032e-02 0.00000000e+00 3.43307361e-02
4.71829848e-01 7.70328897e-01 0.00000000e+00 -2.13023799e-01]
[-3.00446951e-01 -5.23841889e-01 -1.11022302e-16 -1.75237104e-01
4.38715471e-02 4.08005242e-02 0.00000000e+00 1.28648146e-02
-3.72245955e-02 3.08241115e-01 0.00000000e+00 7.10253552e-01]
[-6.42859408e-02 -9.32207274e-02 0.00000000e+00 3.18553088e-02
-5.45330319e-01 -8.29847563e-01 0.00000000e+00 -2.45123670e-03
8.30372253e-04 -1.09565720e-02 0.00000000e+00 -1.89058320e-03]
[ 9.25265800e-03 1.18292006e-02 0.00000000e+00 -8.74320098e-02
-2.83729404e-03 -1.27430430e-03 0.00000000e+00 -9.91956478e-01
-7.52218165e-02 4.74528908e-02 0.00000000e+00 -1.52537037e-02]
[-2.93168546e-01 1.24312410e-01 -2.77555756e-17 -8.46744985e-01
1.08426441e-02 -2.55010380e-02 3.12250226e-17 4.53798129e-02
1.31346070e-01 -3.97105676e-01 0.00000000e+00 -6.20456128e-02]
[ 2.66555443e-01 9.65204669e-02 -1.50920942e-16 -1.42697401e-02
7.60039219e-01 -5.30786928e-01 -1.66533454e-16 -1.18703561e-02
1.11029147e-01 -7.77760097e-02 0.00000000e+00 2.03756001e-01]
[-6.24294035e-01 5.06910648e-01 3.05311332e-16 8.17434491e-02
1.76116152e-01 -1.25932863e-01 -1.11022302e-16 4.19474180e-02
-4.37516395e-01 3.24206628e-01 0.00000000e+00 -3.80848681e-02]
[ 5.21057180e-01 -3.77580936e-02 -5.55111512e-16 -3.80267126e-01
-6.22683392e-02 -1.32578659e-02 -3.33066907e-16 1.02669818e-01
-7.29897752e-01 1.86577704e-01 0.00000000e+00 -1.77335265e-02]
[-2.51267110e-01 -6.43562423e-01 -2.08166817e-15 -8.32277444e-03
2.95106416e-01 -1.02192707e-01 -7.49400542e-16 1.30890959e-02
-1.28768498e-01 7.44699914e-02 0.00000000e+00 -6.34660068e-01]
[-0.00000000e+00 -2.52066149e-16 4.76820672e-01 9.30099886e-33
1.73472348e-16 -7.63278329e-17 -8.79000596e-01 -1.52655666e-16
1.27489903e-16 -1.14722624e-16 0.00000000e+00 -1.57843635e-16]
[-0.00000000e+00 -1.46785158e-15 8.79000596e-01 -1.11022302e-16
6.52256027e-16 -2.77555756e-16 4.76820672e-01 9.71445147e-17
-7.22056875e-16 9.92842677e-17 0.00000000e+00 -1.35679549e-15]
[ 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00
0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00
0.00000000e+00 0.00000000e+00 1.00000000e+00 0.00000000e+00]]
Therefore, creating L will be a division through 0 and the whole matrix can't be computed. Any idea what the problem could be?
When flattening H in line 102, I get TypeError: order must be str, not int
.
From the documentation a letter must be provided indicating wether to flatten in column-major or row-major style. Which is the correct one?
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