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-rw-r--r--demos/demo_cpu_regularisers.py6
-rw-r--r--src/Core/regularisers_CPU/FGP_TV_core.c48
-rw-r--r--src/Python/src/cpu_regularisers.pyx6
3 files changed, 26 insertions, 34 deletions
diff --git a/demos/demo_cpu_regularisers.py b/demos/demo_cpu_regularisers.py
index e58ed2f..8fa7022 100644
--- a/demos/demo_cpu_regularisers.py
+++ b/demos/demo_cpu_regularisers.py
@@ -31,7 +31,7 @@ def printParametersToString(pars):
return txt
###############################################################################
-# filename = os.path.join( "data" ,"lena_gray_512.tif")
+#filename = os.path.join( "data" ,"lena_gray_512.tif")
filename = "/home/kjy41806/Documents/SOFT/CCPi-Regularisation-Toolkit/test/lena_gray_512.tif"
# read image
@@ -128,8 +128,8 @@ imgplot = plt.imshow(u0,cmap="gray")
pars = {'algorithm' : FGP_TV, \
'input' : u0,\
'regularisation_parameter':0.04, \
- 'number_of_iterations' :200 ,\
- 'tolerance_constant':1e-06,\
+ 'number_of_iterations' :800 ,\
+ 'tolerance_constant':1e-07,\
'methodTV': 0 ,\
'nonneg': 0
}
diff --git a/src/Core/regularisers_CPU/FGP_TV_core.c b/src/Core/regularisers_CPU/FGP_TV_core.c
index f613f0e..fc50f13 100644
--- a/src/Core/regularisers_CPU/FGP_TV_core.c
+++ b/src/Core/regularisers_CPU/FGP_TV_core.c
@@ -47,16 +47,12 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
float tkp1 =1.0f;
int count = 0;
- /*adding info into info_vector */
-// infovector[0] = 50.1f; /*iterations number (if stopped earlier based on tolerance)*/
-// infovector[1] = 0.55f; /* reached tolerance */
-
if (dimZ <= 1) {
/*2D case */
float *Output_prev=NULL, *P1=NULL, *P2=NULL, *P1_prev=NULL, *P2_prev=NULL, *R1=NULL, *R2=NULL;
DimTotal = (long)(dimX*dimY);
- Output_prev = calloc(DimTotal, sizeof(float));
+ if (epsil != 0.0f) Output_prev = calloc(DimTotal, sizeof(float));
P1 = calloc(DimTotal, sizeof(float));
P2 = calloc(DimTotal, sizeof(float));
P1_prev = calloc(DimTotal, sizeof(float));
@@ -92,31 +88,24 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
}
re = sqrt(re)/sqrt(re1);
if (re < epsil) count++;
- if (count > 4) break;
-
+ if (count > 4) break;
copyIm(Output, Output_prev, (long)(dimX), (long)(dimY), 1l);
}
+
/*storing old values*/
copyIm(P1, P1_prev, (long)(dimX), (long)(dimY), 1l);
copyIm(P2, P2_prev, (long)(dimX), (long)(dimY), 1l);
tk = tkp1;
- }
- /*adding info into info_vector */
- //info_vector[0] = (float)(ll); /*iterations number (if stopped earlier based on tolerance)*/
-// info_vector[1] = 0.55f; /* reached tolerance */
-
- copyIm(Input, infovector, (long)(dimX), (long)(dimY), 1l);
-
-// printf("%f\n", infovector[128]);
-
- free(Output_prev); free(P1); free(P2); free(P1_prev); free(P2_prev); free(R1); free(R2);
+ }
+ if (epsil != 0.0f) free(Output_prev);
+ free(P1); free(P2); free(P1_prev); free(P2_prev); free(R1); free(R2);
}
else {
/*3D case*/
- float *Output_prev=NULL, *P1=NULL, *P2=NULL, *P3=NULL, *P1_prev=NULL, *P2_prev=NULL, *P3_prev=NULL, *R1=NULL, *R2=NULL, *R3=NULL;
- DimTotal = (long)(dimX*dimY*dimZ);
+ float *Output_prev=NULL, *P1=NULL, *P2=NULL, *P3=NULL, *P1_prev=NULL, *P2_prev=NULL, *P3_prev=NULL, *R1=NULL, *R2=NULL, *R3=NULL;
+ DimTotal = (long)(dimX*dimY*dimZ);
- Output_prev = calloc(DimTotal, sizeof(float));
+ if (epsil != 0.0f) Output_prev = calloc(DimTotal, sizeof(float));
P1 = calloc(DimTotal, sizeof(float));
P2 = calloc(DimTotal, sizeof(float));
P3 = calloc(DimTotal, sizeof(float));
@@ -157,8 +146,8 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
/* stop if the norm residual is less than the tolerance EPS */
if (re < epsil) count++;
if (count > 4) break;
-
- copyIm(Output, Output_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
+
+ copyIm(Output, Output_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
}
/*storing old values*/
@@ -167,13 +156,16 @@ float TV_FGP_CPU_main(float *Input, float *Output, float *infovector, float lamb
copyIm(P3, P3_prev, (long)(dimX), (long)(dimY), (long)(dimZ));
tk = tkp1;
}
- /*adding info into info_vector */
- //infovector[0] = (float)(ll); /*iterations number (if stopped earlier based on tolerance)*/
- //infovector[1] = re; /* reached tolerance */
- free(Output_prev); free(P1); free(P2); free(P3); free(P1_prev); free(P2_prev); free(P3_prev); free(R1); free(R2); free(R3);
- }
- return *Output;
+ if (epsil != 0.0f) free(Output_prev);
+ free(P1); free(P2); free(P3); free(P1_prev); free(P2_prev); free(P3_prev); free(R1); free(R2); free(R3);
+ }
+
+ /*adding info into info_vector */
+ infovector[0] = (float)(ll); /*iterations number (if stopped earlier based on tolerance)*/
+ infovector[1] = re; /* reached tolerance */
+
+ return 0;
}
float Obj_func2D(float *A, float *D, float *R1, float *R2, float lambda, long dimX, long dimY)
diff --git a/src/Python/src/cpu_regularisers.pyx b/src/Python/src/cpu_regularisers.pyx
index b7d029d..49cdf94 100644
--- a/src/Python/src/cpu_regularisers.pyx
+++ b/src/Python/src/cpu_regularisers.pyx
@@ -100,11 +100,11 @@ def TV_FGP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
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=2, mode="c"] infovec = \
- np.ones([dims[0],dims[1]], dtype='float32')
+ cdef np.ndarray[np.float32_t, ndim=1, mode="c"] infovec = \
+ np.ones([2], dtype='float32')
#/* Run FGP-TV iterations for 2D data */
- TV_FGP_CPU_main(&inputData[0,0], &outputData[0,0], &infovec[0,0], regularisation_parameter,
+ TV_FGP_CPU_main(&inputData[0,0], &outputData[0,0], &infovec[0], regularisation_parameter,
iterationsNumb,
tolerance_param,
methodTV,
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-08 06:49:27 +0000