diff options
| -rwxr-xr-x | build/run.sh | 6 | ||||
| -rw-r--r-- | demos/Matlab_demos/demoMatlab_denoise.m | 2 | ||||
| -rw-r--r-- | src/Core/CMakeLists.txt | 1 | ||||
| -rw-r--r-- | src/Python/ccpi/filters/regularisers.py | 13 | ||||
| -rw-r--r-- | src/Python/src/cpu_regularisers.pyx | 31 |
5 files changed, 5 insertions, 48 deletions
diff --git a/build/run.sh b/build/run.sh index 2404d1b..c243b12 100755 --- a/build/run.sh +++ b/build/run.sh @@ -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 diff --git a/demos/Matlab_demos/demoMatlab_denoise.m b/demos/Matlab_demos/demoMatlab_denoise.m index 5af927f..12d5570 100644 --- a/demos/Matlab_demos/demoMatlab_denoise.m +++ b/demos/Matlab_demos/demoMatlab_denoise.m @@ -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); diff --git a/src/Core/CMakeLists.txt b/src/Core/CMakeLists.txt index 8aec749..eea0d63 100644 --- a/src/Core/CMakeLists.txt +++ b/src/Core/CMakeLists.txt @@ -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 diff --git a/src/Python/ccpi/filters/regularisers.py b/src/Python/ccpi/filters/regularisers.py index 2fee8b3..0b5b2ee 100644 --- a/src/Python/ccpi/filters/regularisers.py +++ b/src/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, 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 @@ -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)) diff --git a/src/Python/src/cpu_regularisers.pyx b/src/Python/src/cpu_regularisers.pyx index 9855eca..904b4f5 100644 --- a/src/Python/src/cpu_regularisers.pyx +++ b/src/Python/src/cpu_regularisers.pyx @@ -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); @@ -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) ############################################################################## |