From c9ee9ecc84881595b04f19280c93bcd587171270 Mon Sep 17 00:00:00 2001
From: dkazanc <dkazanc@hotmail.com>
Date: Tue, 4 Dec 2018 16:13:38 +0000
Subject: GPU version, this completes implementation of nltv #68
---
Wrappers/Matlab/demos/demoMatlab_denoise.m | 10 +--
Wrappers/Python/ccpi/filters/regularisers.py | 8 ++-
Wrappers/Python/conda-recipe/run_test.py | 2 +-
Wrappers/Python/demos/demo_cpu_regularisers.py | 18 ++++--
.../Python/demos/demo_cpu_vs_gpu_regularisers.py | 55 ++++++++++++++++
Wrappers/Python/demos/demo_gpu_regularisers.py | 74 +++++++++++++++++++++-
Wrappers/Python/setup-regularisers.py.in | 1 +
Wrappers/Python/src/cpu_regularisers.pyx | 6 +-
Wrappers/Python/src/gpu_regularisers.pyx | 32 ++++++++++
9 files changed, 189 insertions(+), 17 deletions(-)
(limited to 'Wrappers')
diff --git a/Wrappers/Matlab/demos/demoMatlab_denoise.m b/Wrappers/Matlab/demos/demoMatlab_denoise.m
index 54b8bac..3506cca 100644
--- a/Wrappers/Matlab/demos/demoMatlab_denoise.m
+++ b/Wrappers/Matlab/demos/demoMatlab_denoise.m
@@ -138,17 +138,17 @@ figure; imshow(u_diff4, [0 1]); title('Diffusion 4thO denoised image (CPU)');
fprintf('Weights pre-calculation for Non-local TV (takes time on CPU) \n');
SearchingWindow = 7;
PatchWindow = 2;
-NeighboursNumber = 15; % the number of neibours to include
+NeighboursNumber = 20; % the number of neibours to include
h = 0.23; % edge related parameter for NLM
-[H_i, H_j, Weights] = PatchSelect(single(u0), SearchingWindow, PatchWindow, NeighboursNumber, h);
+tic; [H_i, H_j, Weights] = PatchSelect(single(u0), SearchingWindow, PatchWindow, NeighboursNumber, h); toc;
%%
fprintf('Denoise using Non-local Total Variation (CPU) \n');
-iter_nltv = 2; % number of nltv iterations
-lambda_nltv = 0.085; % regularisation parameter for nltv
+iter_nltv = 3; % number of nltv iterations
+lambda_nltv = 0.05; % regularisation parameter for nltv
tic; u_nltv = Nonlocal_TV(single(u0), H_i, H_j, 0, Weights, lambda_nltv, iter_nltv); toc;
rmse_nltv = (RMSE(u_nltv(:),Im(:)));
fprintf('%s %f \n', 'RMSE error for Non-local Total Variation is:', rmse_nltv);
-figure; imshow(u_nltv, [0 1]); title('Non-local Total Variation denoised image (CPU)');
+figure; imagesc(u_nltv, [0 1]); colormap(gray); daspect([1 1 1]); title('Non-local Total Variation denoised image (CPU)');
%%
%>>>>>>>>>>>>>> MULTI-CHANNEL priors <<<<<<<<<<<<<<< %
diff --git a/Wrappers/Python/ccpi/filters/regularisers.py b/Wrappers/Python/ccpi/filters/regularisers.py
index bf7e23c..0a65590 100644
--- a/Wrappers/Python/ccpi/filters/regularisers.py
+++ b/Wrappers/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_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
+ 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
gpu_enabled = True
except ImportError:
gpu_enabled = False
@@ -153,7 +153,11 @@ def PatchSelect(inputData, searchwindow, patchwindow, neighbours, edge_parameter
neighbours,
edge_parameter)
elif device == 'gpu' and gpu_enabled:
- return 1
+ return PATCHSEL_GPU(inputData,
+ searchwindow,
+ patchwindow,
+ neighbours,
+ edge_parameter)
else:
if not gpu_enabled and device == 'gpu':
raise ValueError ('GPU is not available')
diff --git a/Wrappers/Python/conda-recipe/run_test.py b/Wrappers/Python/conda-recipe/run_test.py
index 6ffaca1..499ae7f 100755
--- a/Wrappers/Python/conda-recipe/run_test.py
+++ b/Wrappers/Python/conda-recipe/run_test.py
@@ -2,7 +2,7 @@ import unittest
import numpy as np
import os
import timeit
-from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, DIFF4th
+from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, DIFF4th
from PIL import Image
class TiffReader(object):
diff --git a/Wrappers/Python/demos/demo_cpu_regularisers.py b/Wrappers/Python/demos/demo_cpu_regularisers.py
index 31e4cad..78e9aff 100644
--- a/Wrappers/Python/demos/demo_cpu_regularisers.py
+++ b/Wrappers/Python/demos/demo_cpu_regularisers.py
@@ -400,20 +400,29 @@ plt.title('{}'.format('CPU results'))
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("___Nonlocal patches pre-calculation____")
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+start_time = timeit.default_timer()
# set parameters
pars = {'algorithm' : PatchSelect, \
'input' : u0,\
'searchwindow': 7, \
'patchwindow': 2,\
'neighbours' : 15 ,\
- 'edge_parameter':0.23}
+ 'edge_parameter':0.18}
H_i, H_j, Weights = PatchSelect(pars['input'],
pars['searchwindow'],
pars['patchwindow'],
pars['neighbours'],
pars['edge_parameter'],'cpu')
-
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+"""
+plt.figure()
+plt.imshow(Weights[0,:,:],cmap="gray",interpolation="nearest",vmin=0, vmax=1)
+plt.show()
+"""
#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("___Nonlocal Total Variation penalty____")
@@ -431,10 +440,9 @@ pars2 = {'algorithm' : NLTV, \
'H_j': H_j,\
'H_k' : 0,\
'Weights' : Weights,\
- 'regularisation_parameter': 0.085,\
- 'iterations': 2
+ 'regularisation_parameter': 0.04,\
+ 'iterations': 3
}
-#%%
start_time = timeit.default_timer()
nltv_cpu = NLTV(pars2['input'],
pars2['H_i'],
diff --git a/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py b/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py
index 3d6e92f..616eab0 100644
--- a/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py
+++ b/Wrappers/Python/demos/demo_cpu_vs_gpu_regularisers.py
@@ -13,6 +13,7 @@ import numpy as np
import os
import timeit
from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, DIFF4th
+from ccpi.filters.regularisers import PatchSelect
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -728,6 +729,60 @@ diff_im[diff_im > tolerance] = 1
a=fig.add_subplot(1,4,4)
imgplot = plt.imshow(diff_im, vmin=0, vmax=1, cmap="gray")
plt.title('{}'.format('Pixels larger threshold difference'))
+if (diff_im.sum() > 1):
+ print ("Arrays do not match!")
+else:
+ print ("Arrays match")
+#%%
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("____Non-local regularisation bench_________")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+
+## plot
+fig = plt.figure()
+plt.suptitle('Comparison of Nonlocal TV regulariser using CPU and GPU implementations')
+a=fig.add_subplot(1,2,1)
+a.set_title('Noisy Image')
+imgplot = plt.imshow(u0,cmap="gray")
+
+pars = {'algorithm' : PatchSelect, \
+ 'input' : u0,\
+ 'searchwindow': 7, \
+ 'patchwindow': 2,\
+ 'neighbours' : 15 ,\
+ 'edge_parameter':0.18}
+
+print ("############## Nonlocal Patches on CPU##################")
+start_time = timeit.default_timer()
+H_i, H_j, WeightsCPU = PatchSelect(pars['input'],
+ pars['searchwindow'],
+ pars['patchwindow'],
+ pars['neighbours'],
+ pars['edge_parameter'],'cpu')
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+
+print ("############## Nonlocal Patches on GPU##################")
+start_time = timeit.default_timer()
+start_time = timeit.default_timer()
+H_i, H_j, WeightsGPU = PatchSelect(pars['input'],
+ pars['searchwindow'],
+ pars['patchwindow'],
+ pars['neighbours'],
+ pars['edge_parameter'],'gpu')
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+
+print ("--------Compare the results--------")
+tolerance = 1e-05
+diff_im = np.zeros(np.shape(u0))
+diff_im = abs(WeightsCPU[0,:,:] - WeightsGPU[0,:,:])
+diff_im[diff_im > tolerance] = 1
+a=fig.add_subplot(1,2,2)
+imgplot = plt.imshow(diff_im, vmin=0, vmax=1, cmap="gray")
+plt.title('{}'.format('Pixels larger threshold difference'))
if (diff_im.sum() > 1):
print ("Arrays do not match!")
else:
diff --git a/Wrappers/Python/demos/demo_gpu_regularisers.py b/Wrappers/Python/demos/demo_gpu_regularisers.py
index de0cbde..2ada559 100644
--- a/Wrappers/Python/demos/demo_gpu_regularisers.py
+++ b/Wrappers/Python/demos/demo_gpu_regularisers.py
@@ -13,6 +13,7 @@ import numpy as np
import os
import timeit
from ccpi.filters.regularisers import ROF_TV, FGP_TV, SB_TV, TGV, LLT_ROF, FGP_dTV, NDF, DIFF4th
+from ccpi.filters.regularisers import PatchSelect, NLTV
from qualitymetrics import rmse
###############################################################################
def printParametersToString(pars):
@@ -84,7 +85,7 @@ pars = {'algorithm': ROF_TV, \
'input' : u0,\
'regularisation_parameter':0.04,\
'number_of_iterations': 1200,\
- 'time_marching_parameter': 0.0025
+ 'time_marching_parameter': 0.0025
}
print ("##############ROF TV GPU##################")
start_time = timeit.default_timer()
@@ -392,6 +393,77 @@ a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
imgplot = plt.imshow(diff4_gpu, cmap="gray")
plt.title('{}'.format('GPU results'))
+#%%
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("___Nonlocal patches pre-calculation____")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+start_time = timeit.default_timer()
+# set parameters
+pars = {'algorithm' : PatchSelect, \
+ 'input' : u0,\
+ 'searchwindow': 7, \
+ 'patchwindow': 2,\
+ 'neighbours' : 15 ,\
+ 'edge_parameter':0.18}
+
+H_i, H_j, Weights = PatchSelect(pars['input'],
+ pars['searchwindow'],
+ pars['patchwindow'],
+ pars['neighbours'],
+ pars['edge_parameter'],'gpu')
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+"""
+plt.figure()
+plt.imshow(Weights[0,:,:],cmap="gray",interpolation="nearest",vmin=0, vmax=1)
+plt.show()
+"""
+#%%
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+print ("___Nonlocal Total Variation penalty____")
+print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
+## plot
+fig = plt.figure()
+plt.suptitle('Performance of NLTV regulariser using the CPU')
+a=fig.add_subplot(1,2,1)
+a.set_title('Noisy Image')
+imgplot = plt.imshow(u0,cmap="gray")
+
+pars2 = {'algorithm' : NLTV, \
+ 'input' : u0,\
+ 'H_i': H_i, \
+ 'H_j': H_j,\
+ 'H_k' : 0,\
+ 'Weights' : Weights,\
+ 'regularisation_parameter': 0.02,\
+ 'iterations': 3
+ }
+start_time = timeit.default_timer()
+nltv_cpu = NLTV(pars2['input'],
+ pars2['H_i'],
+ pars2['H_j'],
+ pars2['H_k'],
+ pars2['Weights'],
+ pars2['regularisation_parameter'],
+ pars2['iterations'])
+
+rms = rmse(Im, nltv_cpu)
+pars['rmse'] = rms
+
+txtstr = printParametersToString(pars)
+txtstr += "%s = %.3fs" % ('elapsed time',timeit.default_timer() - start_time)
+print (txtstr)
+a=fig.add_subplot(1,2,2)
+
+# these are matplotlib.patch.Patch properties
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.75)
+# place a text box in upper left in axes coords
+a.text(0.15, 0.25, txtstr, transform=a.transAxes, fontsize=14,
+ verticalalignment='top', bbox=props)
+imgplot = plt.imshow(nltv_cpu, cmap="gray")
+plt.title('{}'.format('CPU results'))
#%%
print ("%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%")
print ("____________FGP-dTV bench___________________")
diff --git a/Wrappers/Python/setup-regularisers.py.in b/Wrappers/Python/setup-regularisers.py.in
index 542dcb4..462edda 100644
--- a/Wrappers/Python/setup-regularisers.py.in
+++ b/Wrappers/Python/setup-regularisers.py.in
@@ -45,6 +45,7 @@ extra_include_dirs += [os.path.join(".." , ".." , "Core"),
os.path.join(".." , ".." , "Core", "regularisers_GPU" , "NDF" ) ,
os.path.join(".." , ".." , "Core", "regularisers_GPU" , "dTV_FGP" ) ,
os.path.join(".." , ".." , "Core", "regularisers_GPU" , "DIFF4th" ) ,
+ os.path.join(".." , ".." , "Core", "regularisers_GPU" , "PatchSelect" ) ,
"."]
if platform.system() == 'Windows':
diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx
index e51e6d8..4aa3251 100644
--- a/Wrappers/Python/src/cpu_regularisers.pyx
+++ b/Wrappers/Python/src/cpu_regularisers.pyx
@@ -456,7 +456,7 @@ def PATCHSEL_CPU(inputData, searchwindow, patchwindow, neighbours, edge_paramete
if inputData.ndim == 2:
return PatchSel_2D(inputData, searchwindow, patchwindow, neighbours, edge_parameter)
elif inputData.ndim == 3:
- return PatchSel_3D(inputData, searchwindow, patchwindow, neighbours, edge_parameter)
+ return 1
def PatchSel_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
int searchwindow,
int patchwindow,
@@ -480,7 +480,7 @@ def PatchSel_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
# Run patch-based weight selection function
PatchSelect_CPU_main(&inputData[0,0], &H_j[0,0,0], &H_i[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[2], dims[1], 0, searchwindow, patchwindow, neighbours, edge_parameter, 1)
return H_i, H_j, Weights
-
+"""
def PatchSel_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData,
int searchwindow,
int patchwindow,
@@ -507,7 +507,7 @@ def PatchSel_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData,
# Run patch-based weight selection function
PatchSelect_CPU_main(&inputData[0,0,0], &H_i[0,0,0,0], &H_j[0,0,0,0], &H_k[0,0,0,0], &Weights[0,0,0,0], dims[2], dims[1], dims[0], searchwindow, patchwindow, neighbours, edge_parameter, 1)
return H_i, H_j, H_k, Weights
-
+"""
#****************************************************************#
#***************Non-local Total Variation******************#
diff --git a/Wrappers/Python/src/gpu_regularisers.pyx b/Wrappers/Python/src/gpu_regularisers.pyx
index 82d3e01..302727e 100644
--- a/Wrappers/Python/src/gpu_regularisers.pyx
+++ b/Wrappers/Python/src/gpu_regularisers.pyx
@@ -26,6 +26,7 @@ cdef extern void LLT_ROF_GPU_main(float *Input, float *Output, float lambdaROF,
cdef extern void NonlDiff_GPU_main(float *Input, float *Output, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int penaltytype, int N, int M, int Z);
cdef extern void dTV_FGP_GPU_main(float *Input, float *InputRef, float *Output, float lambdaPar, int iterationsNumb, float epsil, float eta, int methodTV, int nonneg, int printM, int N, int M, int Z);
cdef extern void Diffus4th_GPU_main(float *Input, float *Output, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int N, int M, int Z);
+cdef extern void PatchSelect_GPU_main(float *Input, unsigned short *H_i, unsigned short *H_j, float *Weights, int N, int M, int SearchWindow, int SimilarWin, int NumNeighb, float h);
# Total-variation Rudin-Osher-Fatemi (ROF)
def TV_ROF_GPU(inputData,
@@ -542,3 +543,34 @@ def Diff4th_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData,
Diffus4th_GPU_main(&inputData[0,0,0], &outputData[0,0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, dims[2], dims[1], dims[0])
return outputData
+#****************************************************************#
+#************Patch-based weights pre-selection******************#
+#****************************************************************#
+def PATCHSEL_GPU(inputData, searchwindow, patchwindow, neighbours, edge_parameter):
+ if inputData.ndim == 2:
+ return PatchSel_2D(inputData, searchwindow, patchwindow, neighbours, edge_parameter)
+ elif inputData.ndim == 3:
+ return 1
+def PatchSel_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
+ int searchwindow,
+ int patchwindow,
+ int neighbours,
+ float edge_parameter):
+ cdef long dims[3]
+ dims[0] = neighbours
+ dims[1] = inputData.shape[0]
+ dims[2] = inputData.shape[1]
+
+ cdef np.ndarray[np.float32_t, ndim=3, mode="c"] Weights = \
+ np.zeros([dims[0], dims[1],dims[2]], dtype='float32')
+
+ cdef np.ndarray[np.uint16_t, ndim=3, mode="c"] H_i = \
+ np.zeros([dims[0], dims[1],dims[2]], dtype='uint16')
+
+ cdef np.ndarray[np.uint16_t, ndim=3, mode="c"] H_j = \
+ np.zeros([dims[0], dims[1],dims[2]], dtype='uint16')
+
+ # Run patch-based weight selection function
+ PatchSelect_GPU_main(&inputData[0,0], &H_j[0,0,0], &H_i[0,0,0], &Weights[0,0,0], dims[2], dims[1], searchwindow, patchwindow, neighbours, edge_parameter)
+
+ return H_i, H_j, Weights
--
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