From 09eb48ffbb4ad699e2eefd25678e10dc59d6a177 Mon Sep 17 00:00:00 2001 From: Daniil Kazantsev Date: Tue, 1 May 2018 09:44:07 +0100 Subject: new inpainters --- Wrappers/Python/src/cpu_regularisers.pyx | 50 ++++++++++++++++++++++++++++++++ 1 file changed, 50 insertions(+) (limited to 'Wrappers/Python/src') diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx index 7ed8fa1..3625106 100644 --- a/Wrappers/Python/src/cpu_regularisers.pyx +++ b/Wrappers/Python/src/cpu_regularisers.pyx @@ -25,6 +25,9 @@ cdef extern float Diffusion_CPU_main(float *Input, float *Output, float lambdaPa 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 dTV_FGP_CPU_main(float *Input, float *InputRef, float *Output, float lambdaPar, int iterationsNumb, float epsil, float eta, int methodTV, int nonneg, int printM, int dimX, int dimY, int dimZ); +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 dimX, int dimY, int dimZ); + #****************************************************************# #********************** Total-variation ROF *********************# #****************************************************************# @@ -319,3 +322,50 @@ def NDF_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, Diffusion_CPU_main(&inputData[0,0,0], &outputData[0,0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[2], dims[1], dims[0]) return outputData + +#*********************Inpainting WITH****************************# +#***************Nonlinear (Isotropic) Diffusion******************# +#****************************************************************# +def NDF_INPAINT_CPU(inputData, maskData, regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type): + if inputData.ndim == 2: + return NDF_INP_2D(inputData, maskData, regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type) + elif inputData.ndim == 3: + return NDF_INP_3D(inputData, maskData, regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type) + +def NDF_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, + np.ndarray[np.uint8_t, ndim=2, mode="c"] maskData, + float regularisation_parameter, + float edge_parameter, + int iterationsNumb, + float time_marching_parameter, + int penalty_type): + cdef long dims[2] + dims[0] = inputData.shape[0] + dims[1] = inputData.shape[1] + + cdef np.ndarray[np.float32_t, ndim=2, mode="c"] outputData = \ + np.zeros([dims[0],dims[1]], dtype='float32') + + # Run Inpaiting by Diffusion iterations for 2D data + Diffusion_Inpaint_CPU_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1) + return outputData + +def NDF_INP_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, + np.ndarray[np.uint8_t, ndim=3, mode="c"] maskData, + float regularisation_parameter, + float edge_parameter, + int iterationsNumb, + float time_marching_parameter, + int penalty_type): + cdef long dims[3] + dims[0] = inputData.shape[0] + dims[1] = inputData.shape[1] + dims[2] = inputData.shape[2] + + cdef np.ndarray[np.float32_t, ndim=3, mode="c"] outputData = \ + np.zeros([dims[0],dims[1],dims[2]], dtype='float32') + + # Run Inpaiting by Diffusion iterations for 3D data + Diffusion_Inpaint_CPU_main(&inputData[0,0,0], &maskData[0,0,0], &outputData[0,0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[2], dims[1], dims[0]) + + return outputData -- cgit v1.2.3 From 42a10faa06bd56bff3f0f1804ddcdf1a3e1283cd Mon Sep 17 00:00:00 2001 From: Daniil Kazantsev Date: Tue, 1 May 2018 15:16:49 +0100 Subject: inpaint NVM added --- Wrappers/Python/ccpi/filters/regularisers.py | 5 +++- Wrappers/Python/demos/demo_cpu_inpainters.py | 45 ++++++++++++++++++++++++++-- Wrappers/Python/src/cpu_regularisers.pyx | 31 ++++++++++++++++++- 3 files changed, 77 insertions(+), 4 deletions(-) (limited to 'Wrappers/Python/src') diff --git a/Wrappers/Python/ccpi/filters/regularisers.py b/Wrappers/Python/ccpi/filters/regularisers.py index 8120f72..a07b39a 100644 --- a/Wrappers/Python/ccpi/filters/regularisers.py +++ b/Wrappers/Python/ccpi/filters/regularisers.py @@ -2,7 +2,7 @@ script which assigns a proper device core function based on a flag ('cpu' or 'gpu') """ -from ccpi.filters.cpu_regularisers import TV_ROF_CPU, TV_FGP_CPU, TV_SB_CPU, dTV_FGP_CPU, TNV_CPU, NDF_CPU, NDF_INPAINT_CPU +from ccpi.filters.cpu_regularisers import TV_ROF_CPU, TV_FGP_CPU, TV_SB_CPU, dTV_FGP_CPU, TNV_CPU, NDF_CPU, NDF_INPAINT_CPU, NVM_INPAINT_CPU from ccpi.filters.gpu_regularisers import TV_ROF_GPU, TV_FGP_GPU, TV_SB_GPU, dTV_FGP_GPU, NDF_GPU def ROF_TV(inputData, regularisation_parameter, iterations, @@ -114,3 +114,6 @@ def NDF_INP(inputData, maskData, regularisation_parameter, edge_parameter, itera time_marching_parameter, penalty_type): return NDF_INPAINT_CPU(inputData, maskData, regularisation_parameter, edge_parameter, iterations, time_marching_parameter, penalty_type) + +def NVM_INP(inputData, maskData, SW_increment, iterations): + return NVM_INPAINT_CPU(inputData, maskData, SW_increment, iterations) diff --git a/Wrappers/Python/demos/demo_cpu_inpainters.py b/Wrappers/Python/demos/demo_cpu_inpainters.py index b067b11..ab7ed2f 100644 --- a/Wrappers/Python/demos/demo_cpu_inpainters.py +++ b/Wrappers/Python/demos/demo_cpu_inpainters.py @@ -10,7 +10,7 @@ import numpy as np import os import timeit from scipy import io -from ccpi.filters.regularisers import NDF_INP +from ccpi.filters.regularisers import NDF_INP, NVM_INP from qualitymetrics import rmse ############################################################################### def printParametersToString(pars): @@ -146,4 +146,45 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14, verticalalignment='top', bbox=props) imgplot = plt.imshow(ndf_inp_nonlinear, cmap="gray") plt.title('{}'.format('Nonlinear diffusion inpainting results')) -#%% \ No newline at end of file +#%% +print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") +print ("Inpainting using nonlocal vertical marching") +print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") + +## plot +fig = plt.figure(4) +plt.suptitle('Performance of NVM inpainting using the CPU') +a=fig.add_subplot(1,2,1) +a.set_title('Missing data sinogram') +imgplot = plt.imshow(sino_cut,cmap="gray") + +# set parameters +pars = {'algorithm' : NVM_INP, \ + 'input' : sino_cut_new,\ + 'maskData' : mask,\ + 'SW_increment': 1,\ + 'number_of_iterations' :20 + } + +start_time = timeit.default_timer() +nvm_inp = NVM_INP(pars['input'], + pars['maskData'], + pars['SW_increment'], + pars['number_of_iterations']) + +rms = rmse(sino_full, nvm_inp) +pars['rmse'] = rms + +txtstr = printParametersToString(pars) +txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time) +print (txtstr) +a=fig.add_subplot(1,2,2) + +# these are matplotlib.patch.Patch properties +props = dict(boxstyle='round', facecolor='wheat', alpha=0.75) +# place a text box in upper left in axes coords +a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14, + verticalalignment='top', bbox=props) +imgplot = plt.imshow(nvm_inp, cmap="gray") +plt.title('{}'.format('Nonlocal Vertical Marching inpainting results')) +#%% diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx index 3625106..19dd707 100644 --- a/Wrappers/Python/src/cpu_regularisers.pyx +++ b/Wrappers/Python/src/cpu_regularisers.pyx @@ -26,7 +26,7 @@ cdef extern float TNV_CPU_main(float *Input, float *u, float lambdaPar, int maxI cdef extern float dTV_FGP_CPU_main(float *Input, float *InputRef, float *Output, float lambdaPar, int iterationsNumb, float epsil, float eta, int methodTV, int nonneg, int printM, int dimX, int dimY, int dimZ); 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 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 dimX, int dimY, int dimZ); #****************************************************************# #********************** Total-variation ROF *********************# @@ -368,4 +368,33 @@ def NDF_INP_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, # Run Inpaiting by Diffusion iterations for 3D data Diffusion_Inpaint_CPU_main(&inputData[0,0,0], &maskData[0,0,0], &outputData[0,0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[2], dims[1], dims[0]) + return outputData +#*********************Inpainting WITH****************************# +#***************Nonlocal Vertical Marching method****************# +#****************************************************************# +def NVM_INPAINT_CPU(inputData, maskData, SW_increment, iterations): + if inputData.ndim == 2: + return NVM_INP_2D(inputData, maskData, SW_increment, iterations) + elif inputData.ndim == 3: + return + +def NVM_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, + np.ndarray[np.uint8_t, ndim=2, mode="c"] maskData, + int SW_increment, + int iterationsNumb): + cdef long dims[2] + dims[0] = inputData.shape[0] + dims[1] = inputData.shape[1] + + cdef np.ndarray[np.float32_t, ndim=2, mode="c"] outputData = \ + np.zeros([dims[0],dims[1]], dtype='float32') + + cdef np.ndarray[np.uint8_t, ndim=2, mode="c"] maskData_upd = \ + np.zeros([dims[0],dims[1]], dtype='uint8') + + # Run Inpaiting by Nonlocal vertical marching method for 2D data + NonlocalMarching_Inpaint_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], &maskData_upd[0,0], + SW_increment, iterationsNumb, + dims[0], dims[1], 1) + return outputData -- cgit v1.2.3 From c4f50db4f5b318aad785ae577908d37fe05f53d2 Mon Sep 17 00:00:00 2001 From: algol Date: Tue, 1 May 2018 15:30:28 +0100 Subject: some updates in demo --- Wrappers/Python/demos/demo_cpu_inpainters.py | 2 +- Wrappers/Python/src/cpu_regularisers.pyx | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) (limited to 'Wrappers/Python/src') diff --git a/Wrappers/Python/demos/demo_cpu_inpainters.py b/Wrappers/Python/demos/demo_cpu_inpainters.py index ab7ed2f..9a677c4 100644 --- a/Wrappers/Python/demos/demo_cpu_inpainters.py +++ b/Wrappers/Python/demos/demo_cpu_inpainters.py @@ -167,7 +167,7 @@ pars = {'algorithm' : NVM_INP, \ } start_time = timeit.default_timer() -nvm_inp = NVM_INP(pars['input'], +(nvm_inp, mask_upd) = NVM_INP(pars['input'], pars['maskData'], pars['SW_increment'], pars['number_of_iterations']) diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx index 19dd707..52befd7 100644 --- a/Wrappers/Python/src/cpu_regularisers.pyx +++ b/Wrappers/Python/src/cpu_regularisers.pyx @@ -397,4 +397,4 @@ def NVM_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, SW_increment, iterationsNumb, dims[0], dims[1], 1) - return outputData + return (outputData, maskData_upd) -- cgit v1.2.3 From 73965b6b80c49a2867d54e4a42f3069fe35d9cc6 Mon Sep 17 00:00:00 2001 From: algol Date: Wed, 2 May 2018 09:47:58 +0100 Subject: corrections to dimens issues --- Wrappers/Python/demos/demo_cpu_inpainters.py | 18 ++++++++++-------- Wrappers/Python/demos/demo_cpu_regularisers.py | 17 +++++++++++++++++ Wrappers/Python/demos/demo_gpu_regularisers.py | 16 ++++++++++++++++ Wrappers/Python/src/cpu_regularisers.pyx | 10 ++++++---- 4 files changed, 49 insertions(+), 12 deletions(-) (limited to 'Wrappers/Python/src') diff --git a/Wrappers/Python/demos/demo_cpu_inpainters.py b/Wrappers/Python/demos/demo_cpu_inpainters.py index 9a677c4..348d235 100644 --- a/Wrappers/Python/demos/demo_cpu_inpainters.py +++ b/Wrappers/Python/demos/demo_cpu_inpainters.py @@ -37,12 +37,14 @@ Mask = sino.get('Mask') sino_full = sino_full/np.max(sino_full) #apply mask to sinogram sino_cut = sino_full*(1-Mask) -sino_cut_new = np.zeros((angles_dim,detectors_dim),'float32') +#sino_cut_new = np.zeros((angles_dim,detectors_dim),'float32') #sino_cut_new = sino_cut.copy(order='c') -sino_cut_new[:] = sino_cut[:] -mask = np.zeros((angles_dim,detectors_dim),'uint8') +#sino_cut_new[:] = sino_cut[:] +sino_cut_new = np.ascontiguousarray(sino_cut, dtype=np.float32); +#mask = np.zeros((angles_dim,detectors_dim),'uint8') #mask =Mask.copy(order='c') -mask[:] = Mask[:] +#mask[:] = Mask[:] +mask = np.ascontiguousarray(Mask, dtype=np.uint8); plt.figure(1) plt.subplot(121) @@ -68,11 +70,11 @@ imgplot = plt.imshow(sino_cut_new,cmap="gray") pars = {'algorithm' : NDF_INP, \ 'input' : sino_cut_new,\ 'maskData' : mask,\ - 'regularisation_parameter':1000,\ - 'edge_parameter':0.0,\ + 'regularisation_parameter':5000,\ + 'edge_parameter':0,\ 'number_of_iterations' :1000 ,\ 'time_marching_parameter':0.000075,\ - 'penalty_type':1 + 'penalty_type':0 } start_time = timeit.default_timer() @@ -163,7 +165,7 @@ pars = {'algorithm' : NVM_INP, \ 'input' : sino_cut_new,\ 'maskData' : mask,\ 'SW_increment': 1,\ - 'number_of_iterations' :20 + 'number_of_iterations' :0 } start_time = timeit.default_timer() diff --git a/Wrappers/Python/demos/demo_cpu_regularisers.py b/Wrappers/Python/demos/demo_cpu_regularisers.py index 3567f91..f803870 100644 --- a/Wrappers/Python/demos/demo_cpu_regularisers.py +++ b/Wrappers/Python/demos/demo_cpu_regularisers.py @@ -50,7 +50,24 @@ u_ref = Im + np.random.normal(loc = 0 , u0 = u0.astype('float32') u_ref = u_ref.astype('float32') +# change dims to check that modules work with non-squared images +(N,M) = np.shape(u0) +u_ref2 = np.zeros([N,M-100],dtype='float32') +u_ref2[:,0:M-100] = u_ref[:,0:M-100] +u_ref = u_ref2 +del u_ref2 + +u02 = np.zeros([N,M-100],dtype='float32') +u02[:,0:M-100] = u0[:,0:M-100] +u0 = u02 +del u02 + +Im2 = np.zeros([N,M-100],dtype='float32') +Im2[:,0:M-100] = Im[:,0:M-100] +Im = Im2 +del Im2 +#%% print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") print ("_______________ROF-TV (2D)_________________") print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") diff --git a/Wrappers/Python/demos/demo_gpu_regularisers.py b/Wrappers/Python/demos/demo_gpu_regularisers.py index b873700..dfdceee 100644 --- a/Wrappers/Python/demos/demo_gpu_regularisers.py +++ b/Wrappers/Python/demos/demo_gpu_regularisers.py @@ -49,6 +49,22 @@ u_ref = Im + np.random.normal(loc = 0 , u0 = u0.astype('float32') u_ref = u_ref.astype('float32') +(N,M) = np.shape(u0) +u_ref2 = np.zeros([N,M-100],dtype='float32') +u_ref2[:,0:M-100] = u_ref[:,0:M-100] +u_ref = u_ref2 +del u_ref2 + +u02 = np.zeros([N,M-100],dtype='float32') +u02[:,0:M-100] = u0[:,0:M-100] +u0 = u02 +del u02 + +Im2 = np.zeros([N,M-100],dtype='float32') +Im2[:,0:M-100] = Im[:,0:M-100] +Im = Im2 +del Im2 + print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") print ("____________ROF-TV regulariser_____________") print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%") diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx index 52befd7..21a1a00 100644 --- a/Wrappers/Python/src/cpu_regularisers.pyx +++ b/Wrappers/Python/src/cpu_regularisers.pyx @@ -49,7 +49,7 @@ def TV_ROF_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, np.zeros([dims[0],dims[1]], dtype='float32') # Run ROF iterations for 2D data - TV_ROF_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, iterationsNumb, marching_step_parameter, dims[0], dims[1], 1) + TV_ROF_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, iterationsNumb, marching_step_parameter, dims[1], dims[0], 1) return outputData @@ -333,18 +333,20 @@ def NDF_INPAINT_CPU(inputData, maskData, regularisation_parameter, edge_paramete return NDF_INP_3D(inputData, maskData, regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type) def NDF_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, - np.ndarray[np.uint8_t, ndim=2, mode="c"] maskData, + np.ndarray[np.uint8_t, ndim=2, mode="c"] maskData, float regularisation_parameter, float edge_parameter, int iterationsNumb, float time_marching_parameter, int penalty_type): + cdef long dims[2] dims[0] = inputData.shape[0] dims[1] = inputData.shape[1] - + + cdef np.ndarray[np.float32_t, ndim=2, mode="c"] outputData = \ - np.zeros([dims[0],dims[1]], dtype='float32') + np.zeros([dims[0],dims[1]], dtype='float32') # Run Inpaiting by Diffusion iterations for 2D data Diffusion_Inpaint_CPU_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1) -- cgit v1.2.3 From a64fe4d083173cc67dd7585c3160a94ea24bca80 Mon Sep 17 00:00:00 2001 From: Daniil Kazantsev Date: Wed, 2 May 2018 10:06:38 +0100 Subject: cyth corr --- Wrappers/Python/src/cpu_regularisers.pyx | 13 ++++++------- Wrappers/Python/src/gpu_regularisers.pyx | 10 +++++----- 2 files changed, 11 insertions(+), 12 deletions(-) (limited to 'Wrappers/Python/src') diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx index 21a1a00..7c06c28 100644 --- a/Wrappers/Python/src/cpu_regularisers.pyx +++ b/Wrappers/Python/src/cpu_regularisers.pyx @@ -102,7 +102,7 @@ def TV_FGP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, methodTV, nonneg, printM, - dims[0], dims[1], 1) + dims[1],dims[0],1) return outputData @@ -161,7 +161,7 @@ def TV_SB_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, tolerance_param, methodTV, printM, - dims[0], dims[1], 1) + dims[1],dims[0],1) return outputData @@ -222,7 +222,7 @@ def dTV_FGP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, methodTV, nonneg, printM, - dims[0], dims[1], 1) + dims[1], dims[0], 1) return outputData @@ -301,7 +301,7 @@ def NDF_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, np.zeros([dims[0],dims[1]], dtype='float32') # Run Nonlinear Diffusion iterations for 2D data - Diffusion_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1) + Diffusion_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[1], dims[0], 1) return outputData def NDF_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, @@ -349,7 +349,7 @@ def NDF_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, np.zeros([dims[0],dims[1]], dtype='float32') # Run Inpaiting by Diffusion iterations for 2D data - Diffusion_Inpaint_CPU_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1) + Diffusion_Inpaint_CPU_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[1], dims[0], 1) return outputData def NDF_INP_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, @@ -396,7 +396,6 @@ def NVM_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, # Run Inpaiting by Nonlocal vertical marching method for 2D data NonlocalMarching_Inpaint_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], &maskData_upd[0,0], - SW_increment, iterationsNumb, - dims[0], dims[1], 1) + SW_increment, iterationsNumb,dims[1], dims[0], 1) return (outputData, maskData_upd) diff --git a/Wrappers/Python/src/gpu_regularisers.pyx b/Wrappers/Python/src/gpu_regularisers.pyx index b0775054..7eab5d5 100644 --- a/Wrappers/Python/src/gpu_regularisers.pyx +++ b/Wrappers/Python/src/gpu_regularisers.pyx @@ -157,7 +157,7 @@ def ROFTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, regularisation_parameter, iterations , time_marching_parameter, - dims[0], dims[1], 1); + dims[1], dims[0], 1); return outputData @@ -210,7 +210,7 @@ def FGPTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, methodTV, nonneg, printM, - dims[0], dims[1], 1); + dims[1], dims[0], 1); return outputData @@ -266,7 +266,7 @@ def SBTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, tolerance_param, methodTV, printM, - dims[0], dims[1], 1); + dims[1], dims[0], 1); return outputData @@ -325,7 +325,7 @@ def FGPdTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, methodTV, nonneg, printM, - dims[0], dims[1], 1); + dims[1], dims[0], 1); return outputData @@ -381,7 +381,7 @@ def NDF_GPU_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, # Run Nonlinear Diffusion iterations for 2D data # Running CUDA code here - NonlDiff_GPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1) + NonlDiff_GPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[1], dims[0], 1) return outputData def NDF_GPU_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, -- cgit v1.2.3 From 14edd18d07c871c0a355d70e68350a899014dbc7 Mon Sep 17 00:00:00 2001 From: algol Date: Wed, 2 May 2018 13:11:50 +0100 Subject: bugs in NVM fixed --- .../inpainters_CPU/NonlocalMarching_Inpaint_core.c | 48 +++++++++++++++++----- Wrappers/Python/demos/demo_cpu_inpainters.py | 6 ++- Wrappers/Python/src/cpu_regularisers.pyx | 12 +++--- 3 files changed, 48 insertions(+), 18 deletions(-) (limited to 'Wrappers/Python/src') diff --git a/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c b/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c index 3a846bb..a197375 100644 --- a/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c +++ b/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c @@ -42,7 +42,7 @@ float NonlocalMarching_Inpaint_main(float *Input, unsigned char *M, float *Outpu { int i, j, i_m, j_m, counter, iter, iterations_number, W_fullsize, switchmask, switchcurr, counterElements; float *Gauss_weights; - + /* copying M to M_upd */ copyIm_unchar(M, M_upd, dimX, dimY, 1); @@ -54,11 +54,11 @@ float NonlocalMarching_Inpaint_main(float *Input, unsigned char *M, float *Outpu iterations_number = 0; for (i=0; i dimX) iterations_number = dimX; } - else iterations_number = (int)(iterationsNumb/dimX); - if (iterations_number > dimX) iterations_number = dimX; - + else iterations_number = iterationsNumb; + if (iterations_number == 0) printf("%s \n", "Nothing to inpaint, zero mask!"); else { @@ -81,11 +81,38 @@ float NonlocalMarching_Inpaint_main(float *Input, unsigned char *M, float *Outpu counter++; } } + + if (trigger == 0) { + /*Matlab*/ + #pragma omp parallel for shared(Output, M_upd, Gauss_weights) private(i, j, switchmask, switchcurr) + for(j=0; j Date: Wed, 2 May 2018 15:47:19 +0100 Subject: bugs of NVM are fixed --- .../inpainters_CPU/NonlocalMarching_Inpaint_core.c | 100 ++++++++++----------- .../inpainters_CPU/NonlocalMarching_Inpaint_core.h | 2 +- .../regularisers_CPU/NonlocalMarching_Inpaint.c | 2 +- Wrappers/Python/src/cpu_regularisers.pyx | 4 +- 4 files changed, 54 insertions(+), 54 deletions(-) (limited to 'Wrappers/Python/src') diff --git a/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c b/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c index a197375..66be15c 100644 --- a/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c +++ b/Core/inpainters_CPU/NonlocalMarching_Inpaint_core.c @@ -30,7 +30,7 @@ * 1. 2D image or sinogram with horizontal or inclined regions of missing data * 2. Mask of the same size as A in 'unsigned char' format (ones mark the region to inpaint, zeros belong to the data) * 3. Linear increment to increase searching window size in iterations, values from 1-3 is a good choice - + * * Output: * 1. Inpainted image or a sinogram * 2. updated mask @@ -38,11 +38,11 @@ * Reference: TBA */ -float NonlocalMarching_Inpaint_main(float *Input, unsigned char *M, float *Output, unsigned char *M_upd, int SW_increment, int iterationsNumb, int dimX, int dimY, int dimZ) +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) { int i, j, i_m, j_m, counter, iter, iterations_number, W_fullsize, switchmask, switchcurr, counterElements; float *Gauss_weights; - + /* copying M to M_upd */ copyIm_unchar(M, M_upd, dimX, dimY, 1); @@ -54,11 +54,11 @@ float NonlocalMarching_Inpaint_main(float *Input, unsigned char *M, float *Outpu iterations_number = 0; for (i=0; i dimX) iterations_number = dimX; + } + if ((int)(iterations_number/dimY) > dimX) iterations_number = dimX; } - else iterations_number = iterationsNumb; - + else iterations_number = iterationsNumb; + if (iterations_number == 0) printf("%s \n", "Nothing to inpaint, zero mask!"); else { @@ -83,54 +83,54 @@ float NonlocalMarching_Inpaint_main(float *Input, unsigned char *M, float *Outpu } if (trigger == 0) { - /*Matlab*/ - #pragma omp parallel for shared(Output, M_upd, Gauss_weights) private(i, j, switchmask, switchcurr) - for(j=0; j