Merge pull request #58 from vais-ral/windows_fix

Windows fix

5 files changed, 44 insertions, 17 deletions

diff --git a/Core/regularisers_CPU/FGP_dTV_core.h b/Core/regularisers_CPU/FGP_dTV_core.h
index 95dc249..8d721d5 100644
--- a/Core/regularisers_CPU/FGP_dTV_core.h
+++ b/Core/regularisers_CPU/FGP_dTV_core.h
@@ -52,7 +52,7 @@ limitations under the License.
 #ifdef __cplusplus
 extern "C" {
 #endif
-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);
+CCPI_EXPORT 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);
 
 CCPI_EXPORT float GradNorm_func2D(float *B, float *B_x, float *B_y, float eta, int dimX, int dimY);
 CCPI_EXPORT float ProjectVect_func2D(float *R1, float *R2, float *B_x, float *B_y, int dimX, int dimY);
diff --git a/Core/regularisers_CPU/SB_TV_core.h b/Core/regularisers_CPU/SB_TV_core.h
index ad4f529..ad4f529 100755..100644
--- a/Core/regularisers_CPU/SB_TV_core.h
+++ b/Core/regularisers_CPU/SB_TV_core.h
diff --git a/Core/regularisers_CPU/TNV_core.h b/Core/regularisers_CPU/TNV_core.h
index 1559b83..c082694 100644
--- a/Core/regularisers_CPU/TNV_core.h
+++ b/Core/regularisers_CPU/TNV_core.h
@@ -4,6 +4,7 @@
 #include <stdio.h>
 #include "omp.h"
 #include "utils.h"
+#include "CCPiDefines.h"
 
 #define fTiny 0.00000001f
 #define fLarge 100000000.0f
@@ -31,10 +32,16 @@ See the License for the specific language governing permissions and
 limitations under the License.
 */
 
-float TNV_CPU_main(float *Input, float *u, float lambda, int maxIter, float tol, int dimX, int dimY, int dimZ);
+#ifdef __cplusplus
+extern "C" {
+#endif
+CCPI_EXPORT float TNV_CPU_main(float *Input, float *u, float lambda, int maxIter, float tol, int dimX, int dimY, int dimZ);
 
 /*float PDHG(float *A, float *B, float tau, float sigma, float theta, float lambda, int p, int q, int r, float tol, int maxIter, int d_c, int d_w, int d_h);*/
-float proxG(float *u_upd, float *v, float *f, float taulambda, int dimX, int dimY, int dimZ);
-float gradient(float *u_upd, float *gradx_upd, float *grady_upd, int dimX, int dimY, int dimZ);
-float proxF(float *gx, float *gy, float *vx, float *vy, float sigma, int p, int q, int r, int dimX, int dimY, int dimZ);
-float divergence(float *qx_upd, float *qy_upd, float *div_upd, int dimX, int dimY, int dimZ);
+CCPI_EXPORT float proxG(float *u_upd, float *v, float *f, float taulambda, int dimX, int dimY, int dimZ);
+CCPI_EXPORT float gradient(float *u_upd, float *gradx_upd, float *grady_upd, int dimX, int dimY, int dimZ);
+CCPI_EXPORT float proxF(float *gx, float *gy, float *vx, float *vy, float sigma, int p, int q, int r, int dimX, int dimY, int dimZ);
+CCPI_EXPORT float divergence(float *qx_upd, float *qy_upd, float *div_upd, int dimX, int dimY, int dimZ);
+#ifdef __cplusplus
+}
+#endif
\ No newline at end of file
diff --git a/Wrappers/Python/ccpi/filters/regularisers.py b/Wrappers/Python/ccpi/filters/regularisers.py
index 52c7974..c7ae808 100644
--- a/Wrappers/Python/ccpi/filters/regularisers.py
+++ b/Wrappers/Python/ccpi/filters/regularisers.py
@@ -3,7 +3,11 @@ 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_SB_CPU, dTV_FGP_CPU, TNV_CPU, NDF_CPU, Diff4th_CPU, TGV_CPU, LLT_ROF_CPU
-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
+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
+    gpu_enabled = True
+except ImportError:
+    gpu_enabled = False    
 from ccpi.filters.cpu_regularisers import NDF_INPAINT_CPU, NVM_INPAINT_CPU
 
 def ROF_TV(inputData, regularisation_parameter, iterations,
@@ -13,12 +17,14 @@ def ROF_TV(inputData, regularisation_parameter, iterations,
                      regularisation_parameter,
                      iterations, 
                      time_marching_parameter)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return TV_ROF_GPU(inputData,
                      regularisation_parameter,
                      iterations, 
                      time_marching_parameter)
     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))
 
@@ -32,7 +38,7 @@ def FGP_TV(inputData, regularisation_parameter,iterations,
                      methodTV,
                      nonneg,
                      printM)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return TV_FGP_GPU(inputData,
                      regularisation_parameter,
                      iterations, 
@@ -41,6 +47,8 @@ def FGP_TV(inputData, regularisation_parameter,iterations,
                      nonneg,
                      printM)
     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))
 def SB_TV(inputData, regularisation_parameter, iterations,
@@ -52,7 +60,7 @@ def SB_TV(inputData, regularisation_parameter, iterations,
                      tolerance_param,
                      methodTV,
                      printM)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return TV_SB_GPU(inputData,
                      regularisation_parameter,
                      iterations, 
@@ -60,6 +68,8 @@ def SB_TV(inputData, regularisation_parameter, iterations,
                      methodTV,
                      printM)
     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))
 def FGP_dTV(inputData, refdata, regularisation_parameter, iterations,
@@ -74,7 +84,7 @@ def FGP_dTV(inputData, refdata, regularisation_parameter, iterations,
                      methodTV,
                      nonneg,
                      printM)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return dTV_FGP_GPU(inputData,
                      refdata,
                      regularisation_parameter,
@@ -85,6 +95,8 @@ def FGP_dTV(inputData, refdata, regularisation_parameter, iterations,
                      nonneg,
                      printM)
     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))
 def TNV(inputData, regularisation_parameter, iterations, tolerance_param):
@@ -101,7 +113,7 @@ def NDF(inputData, regularisation_parameter, edge_parameter, iterations,
                      iterations, 
                      time_marching_parameter,
                      penalty_type)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return NDF_GPU(inputData,
                      regularisation_parameter,
                      edge_parameter,
@@ -109,6 +121,8 @@ def NDF(inputData, regularisation_parameter, edge_parameter, iterations,
                      time_marching_parameter,
                      penalty_type)
     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))
 def DIFF4th(inputData, regularisation_parameter, edge_parameter, iterations,
@@ -119,13 +133,15 @@ def DIFF4th(inputData, regularisation_parameter, edge_parameter, iterations,
                      edge_parameter,
                      iterations, 
                      time_marching_parameter)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return Diff4th_GPU(inputData,
                      regularisation_parameter,
                      edge_parameter,
                      iterations, 
                      time_marching_parameter)
     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))
 def TGV(inputData, regularisation_parameter, alpha1, alpha0, iterations,
@@ -137,7 +153,7 @@ def TGV(inputData, regularisation_parameter, alpha1, alpha0, iterations,
 					alpha0, 
 					iterations,
                     LipshitzConst)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return TGV_GPU(inputData, 
 					regularisation_parameter, 
 					alpha1, 
@@ -145,15 +161,19 @@ def TGV(inputData, regularisation_parameter, alpha1, alpha0, iterations,
 					iterations,
                     LipshitzConst)
     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))
 def LLT_ROF(inputData, regularisation_parameterROF, regularisation_parameterLLT, iterations,
                      time_marching_parameter, device='cpu'):
     if device == 'cpu':
         return LLT_ROF_CPU(inputData, regularisation_parameterROF, regularisation_parameterLLT, iterations, time_marching_parameter)
-    elif device == 'gpu':
+    elif device == 'gpu' and gpu_enabled:
         return LLT_ROF_GPU(inputData, regularisation_parameterROF, regularisation_parameterLLT, iterations, time_marching_parameter)
     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))
 def NDF_INP(inputData, maskData, regularisation_parameter, edge_parameter, iterations,
diff --git a/Wrappers/Python/conda-recipe/meta.yaml b/Wrappers/Python/conda-recipe/meta.yaml
index 4774563..ca28bae 100644
--- a/Wrappers/Python/conda-recipe/meta.yaml
+++ b/Wrappers/Python/conda-recipe/meta.yaml
@@ -21,7 +21,7 @@ requirements:
     - numpy x.x
     - setuptools
     - cython
-    - cil_regulariser
+    - cil_regulariser =={{ environ['CIL_VERSION'] }}
     - vc 14 # [win and py36] 
     - vc 14 # [win and py35] 
     - vc 9  # [win and py27]
@@ -30,7 +30,7 @@ requirements:
   run:
     - python
     - numpy x.x
-    - cil_regulariser
+    - cil_regulariser =={{ environ['CIL_VERSION'] }}
     - vc 14 # [win and py36] 
     - vc 14 # [win and py35] 
     - vc 9  # [win and py27]