diff options
Diffstat (limited to 'src/Python')
| -rw-r--r-- | src/Python/ccpi/filters/regularisers.py | 4 | ||||
| -rw-r--r-- | src/Python/setup-regularisers.py.in | 1 | ||||
| -rw-r--r-- | src/Python/src/gpu_regularisers.pyx | 72 |
3 files changed, 74 insertions, 3 deletions
diff --git a/src/Python/ccpi/filters/regularisers.py b/src/Python/ccpi/filters/regularisers.py index bc745fe..5f4001a 100644 --- a/src/Python/ccpi/filters/regularisers.py +++ b/src/Python/ccpi/filters/regularisers.py @@ -4,7 +4,7 @@ script which assigns a proper device core function based on a flag ('cpu' or 'gp from ccpi.filters.cpu_regularisers import TV_ROF_CPU, TV_FGP_CPU, TV_PD_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 + from ccpi.filters.gpu_regularisers import TV_ROF_GPU, TV_FGP_GPU, TV_PD_GPU, TV_SB_GPU, dTV_FGP_GPU, NDF_GPU, Diff4th_GPU, TGV_GPU, LLT_ROF_GPU, PATCHSEL_GPU gpu_enabled = True except ImportError: gpu_enabled = False @@ -64,7 +64,7 @@ def PD_TV(inputData, regularisation_parameter, iterations, lipschitz_const, tau) elif device == 'gpu' and gpu_enabled: - return TV_PD_CPU(inputData, + return TV_PD_GPU(inputData, regularisation_parameter, iterations, tolerance_param, diff --git a/src/Python/setup-regularisers.py.in b/src/Python/setup-regularisers.py.in index 9a5b693..c4ad143 100644 --- a/src/Python/setup-regularisers.py.in +++ b/src/Python/setup-regularisers.py.in @@ -39,6 +39,7 @@ extra_include_dirs += [os.path.join(".." , "Core"), os.path.join(".." , "Core", "inpainters_CPU"), os.path.join(".." , "Core", "regularisers_GPU" , "TV_FGP" ) , os.path.join(".." , "Core", "regularisers_GPU" , "TV_ROF" ) , + os.path.join(".." , "Core", "regularisers_GPU" , "TV_PD" ) , os.path.join(".." , "Core", "regularisers_GPU" , "TV_SB" ) , os.path.join(".." , "Core", "regularisers_GPU" , "TGV" ) , os.path.join(".." , "Core", "regularisers_GPU" , "LLTROF" ) , diff --git a/src/Python/src/gpu_regularisers.pyx b/src/Python/src/gpu_regularisers.pyx index 8cd8c93..b22d15e 100644 --- a/src/Python/src/gpu_regularisers.pyx +++ b/src/Python/src/gpu_regularisers.pyx @@ -22,6 +22,7 @@ CUDAErrorMessage = 'CUDA error' cdef extern int TV_ROF_GPU_main(float* Input, float* Output, float *infovector, float *lambdaPar, int lambda_is_arr, int iter, float tau, float epsil, int N, int M, int Z); cdef extern int TV_FGP_GPU_main(float *Input, float *Output, float *infovector, float lambdaPar, int iter, float epsil, int methodTV, int nonneg, int N, int M, int Z); +cdef extern int TV_PD_GPU_main(float *Input, float *Output, float *infovector, float lambdaPar, int iter, float epsil, float lipschitz_const, int methodTV, int nonneg, float tau, int dimX, int dimY, int dimZ); cdef extern int TV_SB_GPU_main(float *Input, float *Output, float *infovector, float lambdaPar, int iter, float epsil, int methodTV, int N, int M, int Z); cdef extern int LLT_ROF_GPU_main(float *Input, float *Output, float *infovector, float lambdaROF, float lambdaLLT, int iterationsNumb, float tau, float epsil, int N, int M, int Z); cdef extern int TGV_GPU_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); @@ -70,6 +71,75 @@ def TV_FGP_GPU(inputData, tolerance_param, methodTV, nonneg) +# Total-variation Primal-Dual (PD) +def TV_PD_GPU(inputData, regularisation_parameter, iterationsNumb, tolerance_param, methodTV, nonneg, lipschitz_const, tau): + if inputData.ndim == 2: + return TVPD2D(inputData, regularisation_parameter, iterationsNumb, tolerance_param, methodTV, nonneg, lipschitz_const, tau) + elif inputData.ndim == 3: + return TVPD3D(inputData, regularisation_parameter, iterationsNumb, tolerance_param, methodTV, nonneg, lipschitz_const, tau) + +def TVPD2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, + float regularisation_parameter, + int iterationsNumb, + float tolerance_param, + int methodTV, + int nonneg, + float lipschitz_const, + float tau): + + 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.float32_t, ndim=1, mode="c"] infovec = \ + np.ones([2], dtype='float32') + + if (TV_PD_GPU_main(&inputData[0,0], &outputData[0,0], &infovec[0], regularisation_parameter, + iterationsNumb, + tolerance_param, + lipschitz_const, + methodTV, + nonneg, + tau, + dims[1],dims[0], 1) ==0): + return (outputData,infovec) + else: + raise ValueError(CUDAErrorMessage); + +def TVPD3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData, + float regularisation_parameter, + int iterationsNumb, + float tolerance_param, + int methodTV, + int nonneg, + float lipschitz_const, + float tau): + + 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') + cdef np.ndarray[np.float32_t, ndim=1, mode="c"] infovec = \ + np.zeros([2], dtype='float32') + + if (TV_PD_GPU_main(&inputData[0,0,0], &outputData[0,0,0], &infovec[0], regularisation_parameter, + iterationsNumb, + tolerance_param, + lipschitz_const, + methodTV, + nonneg, + tau, + dims[2], dims[1], dims[0]) ==0): + return (outputData,infovec) + else: + raise ValueError(CUDAErrorMessage); + # Total-variation Split Bregman (SB) def TV_SB_GPU(inputData, regularisation_parameter, @@ -195,7 +265,7 @@ def ROFTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, if isinstance (regularisation_parameter, np.ndarray): reg = regularisation_parameter.copy() # Running CUDA code here - if (TV_ROF_GPU_main(&inputData[0,0], &outputData[0,0], &infovec[0], + if (TV_ROF_GPU_main(&inputData[0,0], &outputData[0,0], &infovec[0], ®[0,0], 1, iterations, time_marching_parameter, |