From 09eb48ffbb4ad699e2eefd25678e10dc59d6a177 Mon Sep 17 00:00:00 2001
From: Daniil Kazantsev <dkazanc@hotmail.com>
Date: Tue, 1 May 2018 09:44:07 +0100
Subject: new inpainters
---
Wrappers/Python/ccpi/filters/regularisers.py | 7 +++-
Wrappers/Python/setup-regularisers.py.in | 3 +-
Wrappers/Python/src/cpu_regularisers.pyx | 50 ++++++++++++++++++++++++++++
3 files changed, 58 insertions(+), 2 deletions(-)
(limited to 'Wrappers/Python')
diff --git a/Wrappers/Python/ccpi/filters/regularisers.py b/Wrappers/Python/ccpi/filters/regularisers.py
index eec8c4d..e62c020 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_cython import TV_ROF_CPU, TV_FGP_CPU, TV_SB_CPU, dTV_FGP_CPU, TNV_CPU, NDF_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
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,
@@ -110,3 +110,8 @@ def NDF(inputData, regularisation_parameter, edge_parameter, iterations,
else:
raise ValueError('Unknown device {0}. Expecting gpu or cpu'\
.format(device))
+def NDF_INP(inputData, maskData, regularisation_parameter, edge_parameter, iterations,
+ time_marching_parameter, penalty_type):
+ return NDF_INPAINT_CPU(inputData, maskData, regularisation_parameter,
+ edge_parameter, iterationsNumb,
+ time_marching_parameter, penalty_type)
diff --git a/Wrappers/Python/setup-regularisers.py.in b/Wrappers/Python/setup-regularisers.py.in
index b900efe..f55c6fe 100644
--- a/Wrappers/Python/setup-regularisers.py.in
+++ b/Wrappers/Python/setup-regularisers.py.in
@@ -34,6 +34,7 @@ extra_libraries = ['cilreg']
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_ROF" ) ,
os.path.join(".." , ".." , "Core", "regularisers_GPU" , "TV_SB" ) ,
@@ -52,7 +53,7 @@ setup(
description='CCPi Core Imaging Library - Image regularisers',
version=cil_version,
cmdclass = {'build_ext': build_ext},
- ext_modules = [Extension("ccpi.filters.cpu_regularisers_cython",
+ ext_modules = [Extension("ccpi.filters.cpu_regularisers",
sources=[os.path.join("." , "src", "cpu_regularisers.pyx" ) ],
include_dirs=extra_include_dirs,
library_dirs=extra_library_dirs,
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
--
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