Closed 1kaiser closed 2 years ago
iter cost cost_change |gradient| |step| tr_ratio tr_radius ls_iter iter_time total_time 0 1.561594e+05 0.00e+00 1.53e+05 0.00e+00 0.00e+00 1.00e+04 0 4.20e-02 3.15e-01
CHOLMOD version 3.0.14, Oct 22, 2019: Symbolic Analysis: status: OK Architecture: Microsoft Windows sizeof(int): 4 sizeof(SuiteSparse_long): 8 sizeof(void *): 8 sizeof(double): 8 sizeof(Int): 4 (CHOLMOD's basic integer) sizeof(BLAS_INT): 4 (integer used in the BLAS) Results from most recent analysis: Cholesky flop count: 9.0091e+06 Nonzeros in L: 45765 memory blocks in use: 11 memory in use (MB): 0.0 peak memory usage (MB): 0.2 maxrank: update/downdate rank: 8 supernodal control: 1 40 (supernodal if flops/lnz >= 40) nmethods: number of ordering methods to try: 1 method 0: natural flop count: 9.0091e+06 nnz(L): 45765 OK 1 1.558150e+05 3.44e+02 3.90e+02 1.89e+00 1.00e+00 3.00e+04 1 1.69e-01 4.86e-01 2 1.558142e+05 8.23e-01 8.97e+01 2.09e-01 1.01e+00 9.00e+04 1 8.68e-02 5.73e-01 3 1.558140e+05 1.82e-01 6.57e+01 1.21e-01 1.03e+00 2.70e+05 1 9.21e-02 6.65e-01 4 1.558140e+05 2.38e-02 2.26e+01 7.41e-02 1.05e+00 8.10e+05 1 8.72e-02 7.53e-01 5 1.558140e+05 1.52e-03 1.37e+01 4.36e-02 1.12e+00 2.43e+06 1 8.64e-02 8.40e-01 6 1.558140e+05 3.56e-04 6.60e+00 4.98e-02 1.08e+00 7.29e+06 1 8.47e-02 9.25e-01 7 1.558140e+05 7.98e-05 2.71e+00 3.25e-02 1.06e+00 2.19e+07 1 8.42e-02 1.01e+00 8 1.558140e+05 5.93e-06 1.03e+00 8.33e-03 1.16e+00 6.56e+07 1 8.34e-02 1.09e+00 9 1.558140e+05 4.76e-07 1.05e+00 7.87e-04 1.37e+00 1.97e+08 1 1.38e-01 1.23e+00 10 1.558140e+05 7.29e-08 1.43e+00 5.31e-05 1.40e+00 5.90e+08 1 8.44e-02 1.32e+00 11 1.558140e+05 1.18e-08 6.63e-01 1.36e-05 1.41e+00 1.77e+09 1 8.37e-02 1.40e+00
Residuals : 179146
Parameters : 69341 Iterations : 12 Time : 1.40682 [s] Initial cost : 0.933642 [px] Final cost : 0.932609 [px] Termination : Convergence
=> Completed observations: 61 => Merged observations: 0 => Filtered observations: 35 => Changed observations: 0.001072 => Filtered images: 0
: : : : : : : ; ; ; ; ; ; ; ;;;
./images/0134.jpg sharpness= 119.97716157485945 ./images/0137.jpg sharpness= 87.292110181125 ./images/0138.jpg sharpness= 153.5903572250282 ./images/0142.jpg sharpness= 273.373650896362 ./images/0139.jpg sharpness= 188.96617858801835 ./images/0107.jpg sharpness= 328.9911469672576 ./images/0126.jpg sharpness= 249.04387470291903 ./images/0140.jpg sharpness= 230.3138767552672 ./images/0143.jpg sharpness= 473.78853254556265 up vector was [-0.9995879 -0.00150619 -0.02866641] computing center of attention... [ 0.25633094 -0.29578212 -0.17005183] avg camera distance from origin 3.1946743361650127 142 frames writing transforms.json
(env) c:\Users\schlb\Documents\GitHub\instant-ngp\data\nerf\test>python C:\Users\schlb\Documents\GitHub\instant-ngp\scripts\colmap2nerf.py --colmap_matcher sequential --run_colmap --aabb_scale 16
done in locall compute resource
1kaiser
commented
2 years ago 1kaiser
commented
2 years ago
iter cost cost_change |gradient| |step| tr_ratio tr_radius ls_iter iter_time total_time 0 1.561594e+05 0.00e+00 1.53e+05 0.00e+00 0.00e+00 1.00e+04 0 4.20e-02 3.15e-01
CHOLMOD version 3.0.14, Oct 22, 2019: Symbolic Analysis: status: OK Architecture: Microsoft Windows sizeof(int): 4 sizeof(SuiteSparse_long): 8 sizeof(void *): 8 sizeof(double): 8 sizeof(Int): 4 (CHOLMOD's basic integer) sizeof(BLAS_INT): 4 (integer used in the BLAS) Results from most recent analysis: Cholesky flop count: 9.0091e+06 Nonzeros in L: 45765 memory blocks in use: 11 memory in use (MB): 0.0 peak memory usage (MB): 0.2 maxrank: update/downdate rank: 8 supernodal control: 1 40 (supernodal if flops/lnz >= 40) nmethods: number of ordering methods to try: 1 method 0: natural flop count: 9.0091e+06 nnz(L): 45765 OK 1 1.558150e+05 3.44e+02 3.90e+02 1.89e+00 1.00e+00 3.00e+04 1 1.69e-01 4.86e-01 2 1.558142e+05 8.23e-01 8.97e+01 2.09e-01 1.01e+00 9.00e+04 1 8.68e-02 5.73e-01 3 1.558140e+05 1.82e-01 6.57e+01 1.21e-01 1.03e+00 2.70e+05 1 9.21e-02 6.65e-01 4 1.558140e+05 2.38e-02 2.26e+01 7.41e-02 1.05e+00 8.10e+05 1 8.72e-02 7.53e-01 5 1.558140e+05 1.52e-03 1.37e+01 4.36e-02 1.12e+00 2.43e+06 1 8.64e-02 8.40e-01 6 1.558140e+05 3.56e-04 6.60e+00 4.98e-02 1.08e+00 7.29e+06 1 8.47e-02 9.25e-01 7 1.558140e+05 7.98e-05 2.71e+00 3.25e-02 1.06e+00 2.19e+07 1 8.42e-02 1.01e+00 8 1.558140e+05 5.93e-06 1.03e+00 8.33e-03 1.16e+00 6.56e+07 1 8.34e-02 1.09e+00 9 1.558140e+05 4.76e-07 1.05e+00 7.87e-04 1.37e+00 1.97e+08 1 1.38e-01 1.23e+00 10 1.558140e+05 7.29e-08 1.43e+00 5.31e-05 1.40e+00 5.90e+08 1 8.44e-02 1.32e+00 11 1.558140e+05 1.18e-08 6.63e-01 1.36e-05 1.41e+00 1.77e+09 1 8.37e-02 1.40e+00
Bundle adjustment report
Parameters : 69341 Iterations : 12 Time : 1.40682 [s] Initial cost : 0.933642 [px] Final cost : 0.932609 [px] Termination : Convergence
=> Completed observations: 61 => Merged observations: 0 => Filtered observations: 35 => Changed observations: 0.001072 => Filtered images: 0
============================================================================== Registering image #143 (52)
: : : : : : : ; ; ; ; ; ; ; ;;;
./images/0134.jpg sharpness= 119.97716157485945 ./images/0137.jpg sharpness= 87.292110181125 ./images/0138.jpg sharpness= 153.5903572250282 ./images/0142.jpg sharpness= 273.373650896362 ./images/0139.jpg sharpness= 188.96617858801835 ./images/0107.jpg sharpness= 328.9911469672576 ./images/0126.jpg sharpness= 249.04387470291903 ./images/0140.jpg sharpness= 230.3138767552672 ./images/0143.jpg sharpness= 473.78853254556265 up vector was [-0.9995879 -0.00150619 -0.02866641] computing center of attention... [ 0.25633094 -0.29578212 -0.17005183] avg camera distance from origin 3.1946743361650127 142 frames writing transforms.json
(env) c:\Users\schlb\Documents\GitHub\instant-ngp\data\nerf\test>python C:\Users\schlb\Documents\GitHub\instant-ngp\scripts\colmap2nerf.py --colmap_matcher sequential --run_colmap --aabb_scale 16