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| author | Daniil Kazantsev <dkazanc@hotmail.com> | 2019-09-04 13:37:08 +0100 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2019-09-04 13:37:08 +0100 |
| commit | 4fb89fcc4719f24b38a777ed6c7204f5761770ad (patch) | |
| tree | f62e25877912d2cebb18a925886d86dcabfe32a4 /src/Python | |
| parent | e2d85c8557733174690da77f712a0c0a7c2d26e0 (diff) | |
| parent | e2601be8f44c09ff21f259d0ce3219bfd5918f12 (diff) | |
| download | regularization-4fb89fcc4719f24b38a777ed6c7204f5761770ad.tar.gz regularization-4fb89fcc4719f24b38a777ed6c7204f5761770ad.tar.bz2 regularization-4fb89fcc4719f24b38a777ed6c7204f5761770ad.tar.xz regularization-4fb89fcc4719f24b38a777ed6c7204f5761770ad.zip | |
Merge pull request #130 from vais-ral/nltv_fix
NLTV fix for nonsquare images
Diffstat (limited to 'src/Python')
| -rw-r--r-- | src/Python/src/cpu_regularisers.pyx | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/src/Python/src/cpu_regularisers.pyx b/src/Python/src/cpu_regularisers.pyx index 904b4f5..4917d06 100644 --- a/src/Python/src/cpu_regularisers.pyx +++ b/src/Python/src/cpu_regularisers.pyx @@ -27,8 +27,8 @@ cdef extern float Diffusion_CPU_main(float *Input, float *Output, float *infovec cdef extern float Diffus4th_CPU_main(float *Input, float *Output, float *infovector, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, float epsil, int dimX, int dimY, int dimZ); cdef extern float dTV_FGP_CPU_main(float *Input, float *InputRef, float *Output, float *infovector, float lambdaPar, int iterationsNumb, float epsil, float eta, int methodTV, int nonneg, int dimX, int dimY, int dimZ); cdef extern float TNV_CPU_main(float *Input, float *u, float lambdaPar, int maxIter, float tol, int dimX, int dimY, int dimZ); -cdef extern float PatchSelect_CPU_main(float *Input, unsigned short *H_i, unsigned short *H_j, unsigned short *H_k, float *Weights, int dimX, int dimY, int dimZ, int SearchWindow, int SimilarWin, int NumNeighb, float h, int switchM); -cdef extern float Nonlocal_TV_CPU_main(float *A_orig, float *Output, unsigned short *H_i, unsigned short *H_j, unsigned short *H_k, float *Weights, int dimX, int dimY, int dimZ, int NumNeighb, float lambdaReg, int IterNumb); +cdef extern float PatchSelect_CPU_main(float *Input, unsigned short *H_i, unsigned short *H_j, unsigned short *H_k, float *Weights, int dimX, int dimY, int dimZ, int SearchWindow, int SimilarWin, int NumNeighb, float h); +cdef extern float Nonlocal_TV_CPU_main(float *A_orig, float *Output, unsigned short *H_i, unsigned short *H_j, unsigned short *H_k, float *Weights, int dimX, int dimY, int dimZ, int NumNeighb, float lambdaReg, int IterNumb, int switchM); cdef extern float Diffusion_Inpaint_CPU_main(float *Input, unsigned char *Mask, float *Output, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int penaltytype, int dimX, int dimY, int dimZ); cdef extern float NonlocalMarching_Inpaint_main(float *Input, unsigned char *M, float *Output, unsigned char *M_upd, int SW_increment, int iterationsNumb, int trigger, int dimX, int dimY, int dimZ); @@ -570,7 +570,7 @@ def PatchSel_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, np.zeros([dims[0], dims[1],dims[2]], dtype='uint16') # Run patch-based weight selection function - PatchSelect_CPU_main(&inputData[0,0], &H_j[0,0,0], &H_i[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[2], dims[1], 0, searchwindow, patchwindow, neighbours, edge_parameter, 1) + PatchSelect_CPU_main(&inputData[0,0], &H_j[0,0,0], &H_i[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[2], dims[1], 0, searchwindow, patchwindow, neighbours, edge_parameter) return H_i, H_j, Weights """ def PatchSel_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, @@ -625,7 +625,7 @@ def NLTV_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, np.zeros([dims[0],dims[1]], dtype='float32') # Run nonlocal TV regularisation - Nonlocal_TV_CPU_main(&inputData[0,0], &outputData[0,0], &H_i[0,0,0], &H_j[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[1], dims[0], 0, neighbours, regularisation_parameter, iterations) + Nonlocal_TV_CPU_main(&inputData[0,0], &outputData[0,0], &H_i[0,0,0], &H_j[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[1], dims[0], 0, neighbours, regularisation_parameter, iterations, 1) return outputData #*********************Inpainting WITH****************************# |