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-rw-r--r--Wrappers/Python/ccpi/__init__.py0
-rw-r--r--Wrappers/Python/ccpi/filters/__init__.py0
-rw-r--r--Wrappers/Python/ccpi/filters/regularisers.py214
-rw-r--r--Wrappers/Python/ccpi/supp/__init__.py0
-rw-r--r--Wrappers/Python/ccpi/supp/qualitymetrics.py65
5 files changed, 0 insertions, 279 deletions
diff --git a/Wrappers/Python/ccpi/__init__.py b/Wrappers/Python/ccpi/__init__.py
deleted file mode 100644
index e69de29..0000000
--- a/Wrappers/Python/ccpi/__init__.py
+++ /dev/null
diff --git a/Wrappers/Python/ccpi/filters/__init__.py b/Wrappers/Python/ccpi/filters/__init__.py
deleted file mode 100644
index e69de29..0000000
--- a/Wrappers/Python/ccpi/filters/__init__.py
+++ /dev/null
diff --git a/Wrappers/Python/ccpi/filters/regularisers.py b/Wrappers/Python/ccpi/filters/regularisers.py
deleted file mode 100644
index 588ea32..0000000
--- a/Wrappers/Python/ccpi/filters/regularisers.py
+++ /dev/null
@@ -1,214 +0,0 @@
-"""
-script which assigns a proper device core function based on a flag ('cpu' or 'gpu')
-"""
-
-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, PATCHSEL_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,
- time_marching_parameter,device='cpu'):
- if device == 'cpu':
- return TV_ROF_CPU(inputData,
- regularisation_parameter,
- iterations,
- time_marching_parameter)
- 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))
-
-def FGP_TV(inputData, regularisation_parameter,iterations,
- tolerance_param, methodTV, nonneg, printM, device='cpu'):
- if device == 'cpu':
- return TV_FGP_CPU(inputData,
- regularisation_parameter,
- iterations,
- tolerance_param,
- methodTV,
- nonneg,
- printM)
- elif device == 'gpu' and gpu_enabled:
- return TV_FGP_GPU(inputData,
- regularisation_parameter,
- iterations,
- tolerance_param,
- methodTV,
- 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,
- tolerance_param, methodTV, printM, device='cpu'):
- if device == 'cpu':
- return TV_SB_CPU(inputData,
- regularisation_parameter,
- iterations,
- tolerance_param,
- methodTV,
- printM)
- elif device == 'gpu' and gpu_enabled:
- return TV_SB_GPU(inputData,
- regularisation_parameter,
- iterations,
- tolerance_param,
- 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,
- tolerance_param, eta_const, methodTV, nonneg, printM, device='cpu'):
- if device == 'cpu':
- return dTV_FGP_CPU(inputData,
- refdata,
- regularisation_parameter,
- iterations,
- tolerance_param,
- eta_const,
- methodTV,
- nonneg,
- printM)
- elif device == 'gpu' and gpu_enabled:
- return dTV_FGP_GPU(inputData,
- refdata,
- regularisation_parameter,
- iterations,
- tolerance_param,
- eta_const,
- methodTV,
- 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):
- return TNV_CPU(inputData,
- regularisation_parameter,
- iterations,
- tolerance_param)
-def NDF(inputData, regularisation_parameter, edge_parameter, iterations,
- time_marching_parameter, penalty_type, device='cpu'):
- if device == 'cpu':
- return NDF_CPU(inputData,
- regularisation_parameter,
- edge_parameter,
- iterations,
- time_marching_parameter,
- penalty_type)
- elif device == 'gpu' and gpu_enabled:
- return NDF_GPU(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,
- time_marching_parameter, device='cpu'):
- if device == 'cpu':
- return Diff4th_CPU(inputData,
- regularisation_parameter,
- edge_parameter,
- iterations,
- time_marching_parameter)
- 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 PatchSelect(inputData, searchwindow, patchwindow, neighbours, edge_parameter, device='cpu'):
- if device == 'cpu':
- return PATCHSEL_CPU(inputData,
- searchwindow,
- patchwindow,
- neighbours,
- edge_parameter)
- elif device == 'gpu' and gpu_enabled:
- return PATCHSEL_GPU(inputData,
- searchwindow,
- patchwindow,
- neighbours,
- edge_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 NLTV(inputData, H_i, H_j, H_k, Weights, regularisation_parameter, iterations):
- return NLTV_CPU(inputData,
- H_i,
- H_j,
- H_k,
- Weights,
- regularisation_parameter,
- iterations)
-
-def TGV(inputData, regularisation_parameter, alpha1, alpha0, iterations,
- LipshitzConst, device='cpu'):
- if device == 'cpu':
- return TGV_CPU(inputData,
- regularisation_parameter,
- alpha1,
- alpha0,
- iterations,
- LipshitzConst)
- elif device == 'gpu' and gpu_enabled:
- return TGV_GPU(inputData,
- regularisation_parameter,
- alpha1,
- alpha0,
- 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' 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,
- time_marching_parameter, penalty_type):
- return NDF_INPAINT_CPU(inputData, maskData, regularisation_parameter,
- edge_parameter, iterations, time_marching_parameter, penalty_type)
-
-def NVM_INP(inputData, maskData, SW_increment, iterations):
- return NVM_INPAINT_CPU(inputData, maskData, SW_increment, iterations)
diff --git a/Wrappers/Python/ccpi/supp/__init__.py b/Wrappers/Python/ccpi/supp/__init__.py
deleted file mode 100644
index e69de29..0000000
--- a/Wrappers/Python/ccpi/supp/__init__.py
+++ /dev/null
diff --git a/Wrappers/Python/ccpi/supp/qualitymetrics.py b/Wrappers/Python/ccpi/supp/qualitymetrics.py
deleted file mode 100644
index f44d832..0000000
--- a/Wrappers/Python/ccpi/supp/qualitymetrics.py
+++ /dev/null
@@ -1,65 +0,0 @@
-#!/usr/bin/env python2
-# -*- coding: utf-8 -*-
-"""
-A class for some standard image quality metrics
-"""
-import numpy as np
-
-class QualityTools:
- def __init__(self, im1, im2):
- if im1.size != im2.size:
- print ('Error: Sizes of images/volumes are different')
- raise SystemExit
- self.im1 = im1 # image or volume - 1
- self.im2 = im2 # image or volume - 2
- def nrmse(self):
- """ Normalised Root Mean Square Error """
- rmse = np.sqrt(np.sum((self.im2 - self.im1) ** 2) / float(self.im1.size))
- max_val = max(np.max(self.im1), np.max(self.im2))
- min_val = min(np.min(self.im1), np.min(self.im2))
- return 1 - (rmse / (max_val - min_val))
- def rmse(self):
- """ Root Mean Square Error """
- rmse = np.sqrt(np.sum((self.im1 - self.im2) ** 2) / float(self.im1.size))
- return rmse
- def ssim(self, window, k=(0.01, 0.03), l=255):
- from scipy.signal import fftconvolve
- """See https://ece.uwaterloo.ca/~z70wang/research/ssim/"""
- # Check if the window is smaller than the images.
- for a, b in zip(window.shape, self.im1.shape):
- if a > b:
- return None, None
- # Values in k must be positive according to the base implementation.
- for ki in k:
- if ki < 0:
- return None, None
-
- c1 = (k[0] * l) ** 2
- c2 = (k[1] * l) ** 2
- window = window/np.sum(window)
-
- mu1 = fftconvolve(self.im1, window, mode='valid')
- mu2 = fftconvolve(self.im2, window, mode='valid')
- mu1_sq = mu1 * mu1
- mu2_sq = mu2 * mu2
- mu1_mu2 = mu1 * mu2
- sigma1_sq = fftconvolve(self.im1 * self.im1, window, mode='valid') - mu1_sq
- sigma2_sq = fftconvolve(self.im2 * self.im2, window, mode='valid') - mu2_sq
- sigma12 = fftconvolve(self.im1 * self.im2, window, mode='valid') - mu1_mu2
-
- if c1 > 0 and c2 > 0:
- num = (2 * mu1_mu2 + c1) * (2 * sigma12 + c2)
- den = (mu1_sq + mu2_sq + c1) * (sigma1_sq + sigma2_sq + c2)
- ssim_map = num / den
- else:
- num1 = 2 * mu1_mu2 + c1
- num2 = 2 * sigma12 + c2
- den1 = mu1_sq + mu2_sq + c1
- den2 = sigma1_sq + sigma2_sq + c2
- ssim_map = np.ones(np.shape(mu1))
- index = (den1 * den2) > 0
- ssim_map[index] = (num1[index] * num2[index]) / (den1[index] * den2[index])
- index = (den1 != 0) & (den2 == 0)
- ssim_map[index] = num1[index] / den1[index]
- mssim = ssim_map.mean()
- return mssim, ssim_map
generated by cgit v1.2.3 (git 2.25.1) at 2026-04-09 03:18:28 +0000