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Merge pull request #122 from vais-ral/matlab_fix
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fix to cmakelists file
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dkazanc authored May 15, 2019
2 parents e871292 + 1207b14 commit 5fb5be3
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Showing 5 changed files with 5 additions and 48 deletions.
6 changes: 3 additions & 3 deletions build/run.sh
Original file line number Diff line number Diff line change
Expand Up @@ -6,13 +6,13 @@ rm -r ../build_proj
mkdir ../build_proj
cd ../build_proj/
#make clean
export CIL_VERSION=19.04
export CIL_VERSION=19.06
# install Python modules without CUDA
#cmake ../ -DBUILD_PYTHON_WRAPPER=ON -DBUILD_MATLAB_WRAPPER=OFF -DBUILD_CUDA=OFF -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
# cmake ../ -DBUILD_PYTHON_WRAPPER=ON -DBUILD_MATLAB_WRAPPER=OFF -DBUILD_CUDA=OFF -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
# install Python modules with CUDA
cmake ../ -DBUILD_PYTHON_WRAPPER=ON -DBUILD_MATLAB_WRAPPER=OFF -DBUILD_CUDA=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
# install Matlab modules without CUDA
#cmake ../ -DBUILD_PYTHON_WRAPPER=OFF -DMatlab_ROOT_DIR=/dls_sw/apps/matlab/r2014a/ -DBUILD_MATLAB_WRAPPER=ON -DBUILD_CUDA=OFF -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
# cmake ../ -DBUILD_PYTHON_WRAPPER=OFF -DMatlab_ROOT_DIR=/dls_sw/apps/matlab/r2014a/ -DBUILD_MATLAB_WRAPPER=ON -DBUILD_CUDA=OFF -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
# install Matlab modules with CUDA
# cmake ../ -DBUILD_PYTHON_WRAPPER=OFF -DMatlab_ROOT_DIR=/dls_sw/apps/matlab/r2014a/ -DBUILD_MATLAB_WRAPPER=ON -DBUILD_CUDA=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
# cmake ../ -DBUILD_PYTHON_WRAPPER=OFF -DMatlab_ROOT_DIR=/home/algol/SOFT/MATLAB9/ -DBUILD_MATLAB_WRAPPER=ON -DBUILD_CUDA=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
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2 changes: 1 addition & 1 deletion demos/Matlab_demos/demoMatlab_denoise.m
Original file line number Diff line number Diff line change
Expand Up @@ -2,9 +2,9 @@
clear; close all
fsep = '/';

Path1 = sprintf(['..' fsep '..' fsep 'src' fsep 'Matlab' fsep 'mex_compile' fsep 'installed'], 1i);
Path2 = sprintf(['..' fsep 'data' fsep], 1i);
Path3 = sprintf(['..' fsep '..' fsep 'src' fsep 'Matlab' fsep 'supp'], 1i);
Path1 = sprintf(['..' fsep '..' fsep 'src' fsep 'Matlab' fsep 'mex_compile' fsep 'installed'], 1i);
addpath(Path1);
addpath(Path2);
addpath(Path3);
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1 change: 0 additions & 1 deletion src/Core/CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -68,7 +68,6 @@ add_library(cilreg SHARED
${CMAKE_CURRENT_SOURCE_DIR}/regularisers_CPU/SB_TV_core.c
${CMAKE_CURRENT_SOURCE_DIR}/regularisers_CPU/TGV_core.c
${CMAKE_CURRENT_SOURCE_DIR}/regularisers_CPU/Diffusion_core.c
${CMAKE_CURRENT_SOURCE_DIR}/regularisers_CPU/MASK_merge_core.c
${CMAKE_CURRENT_SOURCE_DIR}/regularisers_CPU/Diffus4th_order_core.c
${CMAKE_CURRENT_SOURCE_DIR}/regularisers_CPU/LLT_ROF_core.c
${CMAKE_CURRENT_SOURCE_DIR}/regularisers_CPU/ROF_TV_core.c
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13 changes: 1 addition & 12 deletions src/Python/ccpi/filters/regularisers.py
Original file line number Diff line number Diff line change
Expand Up @@ -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, Diff4th_CPU, TGV_CPU, LLT_ROF_CPU, PATCHSEL_CPU, NLTV_CPU, MASK_CORR_CPU
from ccpi.filters.cpu_regularisers import TV_ROF_CPU, TV_FGP_CPU, TV_SB_CPU, dTV_FGP_CPU, TNV_CPU, NDF_CPU, Diff4th_CPU, TGV_CPU, LLT_ROF_CPU, PATCHSEL_CPU, NLTV_CPU
try:
from ccpi.filters.gpu_regularisers import TV_ROF_GPU, TV_FGP_GPU, TV_SB_GPU, dTV_FGP_GPU, NDF_GPU, Diff4th_GPU, TGV_GPU, LLT_ROF_GPU, PATCHSEL_GPU
gpu_enabled = True
Expand Down Expand Up @@ -212,15 +212,4 @@ def NDF_INP(inputData, maskData, regularisation_parameter, edge_parameter, itera

def NVM_INP(inputData, maskData, SW_increment, iterations):
return NVM_INPAINT_CPU(inputData, maskData, SW_increment, iterations)

def MASK_CORR(maskdata, select_classes, total_classesNum, CorrectionWindow, device='cpu'):
if device == 'cpu':
return MASK_CORR_CPU(maskdata, select_classes, total_classesNum, CorrectionWindow)
elif device == 'gpu' and gpu_enabled:
return MASK_CORR_CPU(maskdata, select_classes, total_classesNum, CorrectionWindow)
else:
if not gpu_enabled and device == 'gpu':
raise ValueError ('GPU is not available')
raise ValueError('Unknown device {0}. Expecting gpu or cpu'\
.format(device))

31 changes: 0 additions & 31 deletions src/Python/src/cpu_regularisers.pyx
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,6 @@ cdef extern float SB_TV_CPU_main(float *Input, float *Output, float *infovector,
cdef extern float LLT_ROF_CPU_main(float *Input, float *Output, float *infovector, float lambdaROF, float lambdaLLT, int iterationsNumb, float tau, float epsil, int dimX, int dimY, int dimZ);
cdef extern float TGV_main(float *Input, float *Output, float *infovector, float lambdaPar, float alpha1, float alpha0, int iterationsNumb, float L2, float epsil, int dimX, int dimY, int dimZ);
cdef extern float Diffusion_CPU_main(float *Input, float *Output, float *infovector, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int penaltytype, float epsil, int dimX, int dimY, int dimZ);
cdef extern float Mask_merge_main(unsigned char *MASK, unsigned char *MASK_upd, unsigned char *CORRECTEDRegions, unsigned char *SelClassesList, int SelClassesList_length, int classesNumb, int CorrectionWindow, int dimX, int dimY, int dimZ);
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);
Expand Down Expand Up @@ -707,36 +706,6 @@ def NVM_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,

return (outputData, maskData_upd)

##############################################################################
#****************************************************************#
#********Mask (segmented image) correction module **************#
#****************************************************************#
def MASK_CORR_CPU(maskData, select_classes, total_classesNum, CorrectionWindow):
if maskData.ndim == 2:
return MASK_CORR_CPU_2D(maskData, select_classes, total_classesNum, CorrectionWindow)
elif maskData.ndim == 3:
return 0

def MASK_CORR_CPU_2D(np.ndarray[np.uint8_t, ndim=2, mode="c"] maskData,
np.ndarray[np.uint8_t, ndim=1, mode="c"] select_classes,
int total_classesNum,
int CorrectionWindow):

cdef long dims[2]
dims[0] = maskData.shape[0]
dims[1] = maskData.shape[1]

select_classes_length = select_classes.shape[0]

cdef np.ndarray[np.uint8_t, ndim=2, mode="c"] mask_upd = \
np.zeros([dims[0],dims[1]], dtype='uint8')
cdef np.ndarray[np.uint8_t, ndim=2, mode="c"] corr_regions = \
np.zeros([dims[0],dims[1]], dtype='uint8')

# Run the function to process given MASK
Mask_merge_main(&maskData[0,0], &mask_upd[0,0], &corr_regions[0,0], &select_classes[0], select_classes_length,
total_classesNum, CorrectionWindow, dims[1], dims[0], 1)
return (mask_upd,corr_regions)

##############################################################################

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