diff options
Diffstat (limited to 'src/Python')
| -rw-r--r-- | src/Python/setup-regularisers.py.in | 1 | ||||
| -rw-r--r-- | src/Python/src/cpu_regularisers.pyx | 29 |
2 files changed, 28 insertions, 2 deletions
diff --git a/src/Python/setup-regularisers.py.in b/src/Python/setup-regularisers.py.in index 9bcd46d..9a5b693 100644 --- a/src/Python/setup-regularisers.py.in +++ b/src/Python/setup-regularisers.py.in @@ -38,7 +38,6 @@ extra_include_dirs += [os.path.join(".." , "Core"), os.path.join(".." , "Core", "regularisers_CPU"), os.path.join(".." , "Core", "inpainters_CPU"), os.path.join(".." , "Core", "regularisers_GPU" , "TV_FGP" ) , - os.path.join(".." , "Core", "regularisers_GPU" , "TV_PD" ) , os.path.join(".." , "Core", "regularisers_GPU" , "TV_ROF" ) , os.path.join(".." , "Core", "regularisers_GPU" , "TV_SB" ) , os.path.join(".." , "Core", "regularisers_GPU" , "TGV" ) , diff --git a/src/Python/src/cpu_regularisers.pyx b/src/Python/src/cpu_regularisers.pyx index 724634b..08e247c 100644 --- a/src/Python/src/cpu_regularisers.pyx +++ b/src/Python/src/cpu_regularisers.pyx @@ -163,7 +163,7 @@ def TV_PD_CPU(inputData, regularisation_parameter, iterationsNumb, tolerance_par if inputData.ndim == 2: return TV_PD_2D(inputData, regularisation_parameter, iterationsNumb, tolerance_param, methodTV, nonneg, lipschitz_const) elif inputData.ndim == 3: - return 0 + return TV_PD_3D(inputData, regularisation_parameter, iterationsNumb, tolerance_param, methodTV, nonneg, lipschitz_const) def TV_PD_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, float regularisation_parameter, @@ -191,7 +191,34 @@ def TV_PD_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData, methodTV, nonneg, dims[1],dims[0], 1) + return (outputData,infovec) + +def TV_PD_3D(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): + + 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') + + #/* Run FGP-TV iterations for 3D data */ + PDTV_CPU_main(&inputData[0,0,0], &outputData[0,0,0], &infovec[0], regularisation_parameter, + iterationsNumb, + tolerance_param, + lipschitz_const, + methodTV, + nonneg, + dims[2], dims[1], dims[0]) return (outputData,infovec) #***************************************************************# |