Mercurial > repos > perssond > coreograph

annotate UNet2DtCycifTRAINCoreograph.py @ 1:57f1260ca94e draft

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"planemo upload commit fec9dc76b3dd17b14b02c2f04be9d30f71eba1ae"
author watsocam
date Fri, 11 Mar 2022 23:40:51 +0000
parents 99308601eaa6
children
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1 import numpy as np
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2 from scipy import misc
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3 import tensorflow as tf
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4 import shutil
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5 import scipy.io as sio
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6 import os,fnmatch,PIL,glob
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7
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8 import sys
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9 sys.path.insert(0, 'C:\\Users\\Public\\Documents\\ImageScience')
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10 from toolbox.imtools import *
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11 from toolbox.ftools import *
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12 from toolbox.PartitionOfImage import PI2D
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13
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15 def concat3(lst):
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16 return tf.concat(lst,3)
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17
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18 class UNet2D:
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19 hp = None # hyper-parameters
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20 nn = None # network
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21 tfTraining = None # if training or not (to handle batch norm)
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22 tfData = None # data placeholder
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23 Session = None
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24 DatasetMean = 0
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25 DatasetStDev = 0
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26
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27 def setupWithHP(hp):
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28 UNet2D.setup(hp['imSize'],
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29 hp['nChannels'],
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30 hp['nClasses'],
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31 hp['nOut0'],
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32 hp['featMapsFact'],
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33 hp['downSampFact'],
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34 hp['ks'],
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35 hp['nExtraConvs'],
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36 hp['stdDev0'],
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37 hp['nLayers'],
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38 hp['batchSize'])
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39
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40 def setup(imSize,nChannels,nClasses,nOut0,featMapsFact,downSampFact,kernelSize,nExtraConvs,stdDev0,nDownSampLayers,batchSize):
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41 UNet2D.hp = {'imSize':imSize,
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42 'nClasses':nClasses,
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43 'nChannels':nChannels,
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44 'nExtraConvs':nExtraConvs,
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45 'nLayers':nDownSampLayers,
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46 'featMapsFact':featMapsFact,
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47 'downSampFact':downSampFact,
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48 'ks':kernelSize,
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49 'nOut0':nOut0,
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50 'stdDev0':stdDev0,
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51 'batchSize':batchSize}
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52
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53 nOutX = [UNet2D.hp['nChannels'],UNet2D.hp['nOut0']]
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54 dsfX = []
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55 for i in range(UNet2D.hp['nLayers']):
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56 nOutX.append(nOutX[-1]*UNet2D.hp['featMapsFact'])
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57 dsfX.append(UNet2D.hp['downSampFact'])
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58
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59
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60 # --------------------------------------------------
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61 # downsampling layer
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62 # --------------------------------------------------
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63
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64 with tf.name_scope('placeholders'):
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65 UNet2D.tfTraining = tf.placeholder(tf.bool, name='training')
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66 UNet2D.tfData = tf.placeholder("float", shape=[None,UNet2D.hp['imSize'],UNet2D.hp['imSize'],UNet2D.hp['nChannels']],name='data')
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67
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68 def down_samp_layer(data,index):
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69 with tf.name_scope('ld%d' % index):
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70 ldXWeights1 = tf.Variable(tf.truncated_normal([UNet2D.hp['ks'], UNet2D.hp['ks'], nOutX[index], nOutX[index+1]], stddev=stdDev0),name='kernel1')
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71 ldXWeightsExtra = []
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72 for i in range(nExtraConvs):
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73 ldXWeightsExtra.append(tf.Variable(tf.truncated_normal([UNet2D.hp['ks'], UNet2D.hp['ks'], nOutX[index+1], nOutX[index+1]], stddev=stdDev0),name='kernelExtra%d' % i))
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74
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75 c00 = tf.nn.conv2d(data, ldXWeights1, strides=[1, 1, 1, 1], padding='SAME')
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76 for i in range(nExtraConvs):
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77 c00 = tf.nn.conv2d(tf.nn.relu(c00), ldXWeightsExtra[i], strides=[1, 1, 1, 1], padding='SAME')
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78
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79 ldXWeightsShortcut = tf.Variable(tf.truncated_normal([1, 1, nOutX[index], nOutX[index+1]], stddev=stdDev0),name='shortcutWeights')
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80 shortcut = tf.nn.conv2d(data, ldXWeightsShortcut, strides=[1, 1, 1, 1], padding='SAME')
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81
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82 bn = tf.layers.batch_normalization(tf.nn.relu(c00+shortcut), training=UNet2D.tfTraining)
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83
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84 return tf.nn.max_pool(bn, ksize=[1, dsfX[index], dsfX[index], 1], strides=[1, dsfX[index], dsfX[index], 1], padding='SAME',name='maxpool')
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85
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86 # --------------------------------------------------
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87 # bottom layer
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88 # --------------------------------------------------
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89
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90 with tf.name_scope('lb'):
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91 lbWeights1 = tf.Variable(tf.truncated_normal([UNet2D.hp['ks'], UNet2D.hp['ks'], nOutX[UNet2D.hp['nLayers']], nOutX[UNet2D.hp['nLayers']+1]], stddev=stdDev0),name='kernel1')
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92 def lb(hidden):
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93 return tf.nn.relu(tf.nn.conv2d(hidden, lbWeights1, strides=[1, 1, 1, 1], padding='SAME'),name='conv')
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94
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95 # --------------------------------------------------
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96 # downsampling
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97 # --------------------------------------------------
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98
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99 with tf.name_scope('downsampling'):
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100 dsX = []
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101 dsX.append(UNet2D.tfData)
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102
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103 for i in range(UNet2D.hp['nLayers']):
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104 dsX.append(down_samp_layer(dsX[i],i))
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105
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106 b = lb(dsX[UNet2D.hp['nLayers']])
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107
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108 # --------------------------------------------------
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109 # upsampling layer
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110 # --------------------------------------------------
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111
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112 def up_samp_layer(data,index):
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113 with tf.name_scope('lu%d' % index):
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114 luXWeights1 = tf.Variable(tf.truncated_normal([UNet2D.hp['ks'], UNet2D.hp['ks'], nOutX[index+1], nOutX[index+2]], stddev=stdDev0),name='kernel1')
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115 luXWeights2 = tf.Variable(tf.truncated_normal([UNet2D.hp['ks'], UNet2D.hp['ks'], nOutX[index]+nOutX[index+1], nOutX[index+1]], stddev=stdDev0),name='kernel2')
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116 luXWeightsExtra = []
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117 for i in range(nExtraConvs):
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118 luXWeightsExtra.append(tf.Variable(tf.truncated_normal([UNet2D.hp['ks'], UNet2D.hp['ks'], nOutX[index+1], nOutX[index+1]], stddev=stdDev0),name='kernel2Extra%d' % i))
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119
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120 outSize = UNet2D.hp['imSize']
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121 for i in range(index):
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122 outSize /= dsfX[i]
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123 outSize = int(outSize)
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124
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125 outputShape = [UNet2D.hp['batchSize'],outSize,outSize,nOutX[index+1]]
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126 us = tf.nn.relu(tf.nn.conv2d_transpose(data, luXWeights1, outputShape, strides=[1, dsfX[index], dsfX[index], 1], padding='SAME'),name='conv1')
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127 cc = concat3([dsX[index],us])
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128 cv = tf.nn.relu(tf.nn.conv2d(cc, luXWeights2, strides=[1, 1, 1, 1], padding='SAME'),name='conv2')
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129 for i in range(nExtraConvs):
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130 cv = tf.nn.relu(tf.nn.conv2d(cv, luXWeightsExtra[i], strides=[1, 1, 1, 1], padding='SAME'),name='conv2Extra%d' % i)
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131 return cv
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132
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133 # --------------------------------------------------
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134 # final (top) layer
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135 # --------------------------------------------------
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136
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137 with tf.name_scope('lt'):
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138 ltWeights1 = tf.Variable(tf.truncated_normal([1, 1, nOutX[1], nClasses], stddev=stdDev0),name='kernel')
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139 def lt(hidden):
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140 return tf.nn.conv2d(hidden, ltWeights1, strides=[1, 1, 1, 1], padding='SAME',name='conv')
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141
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142
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143 # --------------------------------------------------
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144 # upsampling
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145 # --------------------------------------------------
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146
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147 with tf.name_scope('upsampling'):
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148 usX = []
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149 usX.append(b)
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150
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151 for i in range(UNet2D.hp['nLayers']):
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152 usX.append(up_samp_layer(usX[i],UNet2D.hp['nLayers']-1-i))
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153
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154 t = lt(usX[UNet2D.hp['nLayers']])
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155
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156
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157 sm = tf.nn.softmax(t,-1)
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158 UNet2D.nn = sm
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159
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160
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161 def train(imPath,logPath,modelPath,pmPath,nTrain,nValid,nTest,restoreVariables,nSteps,gpuIndex,testPMIndex):
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162 os.environ['CUDA_VISIBLE_DEVICES']= '%d' % gpuIndex
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163
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164 outLogPath = logPath
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165 trainWriterPath = pathjoin(logPath,'Train')
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166 validWriterPath = pathjoin(logPath,'Valid')
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167 outModelPath = pathjoin(modelPath,'model.ckpt')
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168 outPMPath = pmPath
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169
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170 batchSize = UNet2D.hp['batchSize']
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171 imSize = UNet2D.hp['imSize']
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172 nChannels = UNet2D.hp['nChannels']
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173 nClasses = UNet2D.hp['nClasses']
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174
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175 # --------------------------------------------------
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176 # data
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177 # --------------------------------------------------
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178
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179 Train = np.zeros((nTrain,imSize,imSize,nChannels))
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180 Valid = np.zeros((nValid,imSize,imSize,nChannels))
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181 Test = np.zeros((nTest,imSize,imSize,nChannels))
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182 LTrain = np.zeros((nTrain,imSize,imSize,nClasses))
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183 LValid = np.zeros((nValid,imSize,imSize,nClasses))
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184 LTest = np.zeros((nTest,imSize,imSize,nClasses))
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185
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186 print('loading data, computing mean / st dev')
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187 if not os.path.exists(modelPath):
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188 os.makedirs(modelPath)
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189 if restoreVariables:
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190 datasetMean = loadData(pathjoin(modelPath,'datasetMean.data'))
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191 datasetStDev = loadData(pathjoin(modelPath,'datasetStDev.data'))
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192 else:
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193 datasetMean = 0.09
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194 datasetStDev = 0.09
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195 #for iSample in range(nTrain+nValid+nTest):
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196 # I = im2double(tifread('%s/I%05d_Img.tif' % (imPath,iSample)))
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197 # datasetMean += np.mean(I)
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198 # datasetStDev += np.std(I)
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199 #datasetMean /= (nTrain+nValid+nTest)
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200 #datasetStDev /= (nTrain+nValid+nTest)
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201 saveData(datasetMean, pathjoin(modelPath,'datasetMean.data'))
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202 saveData(datasetStDev, pathjoin(modelPath,'datasetStDev.data'))
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203
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204 perm = np.arange(nTrain+nValid+nTest)
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205 np.random.shuffle(perm)
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206
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207 for iSample in range(0, nTrain):
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208 path = '%s/I%05d_Img.tif' % (imPath,perm[iSample])
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diff changeset
209 im = im2double(tifread(path))
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210 #im = im[0, 0, 0, :, :]
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211 Train[iSample,:,:,0] = (im-datasetMean)/datasetStDev
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212 path = '%s/I%05d_Ant.tif' % (imPath,perm[iSample])
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213 im = tifread(path)
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214 for i in range(nClasses):
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diff changeset
215 LTrain[iSample,:,:,i] = (im == i+1)
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216
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217 for iSample in range(0, nValid):
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218 path = '%s/I%05d_Img.tif' % (imPath,perm[nTrain+iSample])
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219 im = im2double(tifread(path))
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220 #im = im[0, 0, 0, :, :]
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221 Valid[iSample,:,:,0] = (im-datasetMean)/datasetStDev
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222 path = '%s/I%05d_Ant.tif' % (imPath,perm[nTrain+iSample])
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223 im = tifread(path)
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224 for i in range(nClasses):
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225 LValid[iSample,:,:,i] = (im == i+1)
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226
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227 for iSample in range(0, nTest):
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228 path = '%s/I%05d_Img.tif' % (imPath,perm[nTrain+nValid+iSample])
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229 im = im2double(tifread(path))
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230 #im = im[0, 0, 0, :, :]
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diff changeset
231 Test[iSample,:,:,0] = (im-datasetMean)/datasetStDev
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232 path = '%s/I%05d_Ant.tif' % (imPath,perm[nTrain+nValid+iSample])
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diff changeset
233 im = tifread(path)
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diff changeset
234 for i in range(nClasses):
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diff changeset
235 LTest[iSample,:,:,i] = (im == i+1)
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236
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diff changeset
237 # --------------------------------------------------
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diff changeset
238 # optimization
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diff changeset
239 # --------------------------------------------------
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240
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diff changeset
241 tfLabels = tf.placeholder("float", shape=[None,imSize,imSize,nClasses],name='labels')
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242
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diff changeset
243 globalStep = tf.Variable(0,trainable=False)
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diff changeset
244 learningRate0 = 0.05
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245 decaySteps = 1000
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246 decayRate = 0.95
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diff changeset
247 learningRate = tf.train.exponential_decay(learningRate0,globalStep,decaySteps,decayRate,staircase=True)
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248
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diff changeset
249 with tf.name_scope('optim'):
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250 loss = tf.reduce_mean(-tf.reduce_sum(tf.multiply(tfLabels,tf.log(UNet2D.nn)),3))
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251 updateOps = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
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252 # optimizer = tf.train.MomentumOptimizer(1e-3,0.9)
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253 optimizer = tf.train.MomentumOptimizer(learningRate,0.9)
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254 # optimizer = tf.train.GradientDescentOptimizer(learningRate)
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255 with tf.control_dependencies(updateOps):
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256 optOp = optimizer.minimize(loss,global_step=globalStep)
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257
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diff changeset
258 with tf.name_scope('eval'):
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diff changeset
259 error = []
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diff changeset
260 for iClass in range(nClasses):
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diff changeset
261 labels0 = tf.reshape(tf.to_int32(tf.slice(tfLabels,[0,0,0,iClass],[-1,-1,-1,1])),[batchSize,imSize,imSize])
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262 predict0 = tf.reshape(tf.to_int32(tf.equal(tf.argmax(UNet2D.nn,3),iClass)),[batchSize,imSize,imSize])
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diff changeset
263 correct = tf.multiply(labels0,predict0)
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264 nCorrect0 = tf.reduce_sum(correct)
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265 nLabels0 = tf.reduce_sum(labels0)
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diff changeset
266 error.append(1-tf.to_float(nCorrect0)/tf.to_float(nLabels0))
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267 errors = tf.tuple(error)
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268
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diff changeset
269 # --------------------------------------------------
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diff changeset
270 # inspection
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diff changeset
271 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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272
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
273 with tf.name_scope('scalars'):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
274 tf.summary.scalar('avg_cross_entropy', loss)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
275 for iClass in range(nClasses):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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276 tf.summary.scalar('avg_pixel_error_%d' % iClass, error[iClass])
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
277 tf.summary.scalar('learning_rate', learningRate)
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278 with tf.name_scope('images'):
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279 #split0 = tf.slice(UNet2D.nn,[0,0,0,0],[-1,-1,-1,1])
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diff changeset
280 split0 = tf.slice(UNet2D.nn,[0,0,0,1],[-1,-1,-1,1])
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281 split1 = tf.slice(tfLabels, [0, 0, 0, 0], [-1, -1, -1, 1])
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282 if nClasses > 2:
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283 split2 = tf.slice(UNet2D.nn,[0,0,0,2],[-1,-1,-1,1])
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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284 tf.summary.image('pm0',split0)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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285 tf.summary.image('pm1',split1)
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diff changeset
286 if nClasses > 2:
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287 tf.summary.image('pm2',split2)
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288 merged = tf.summary.merge_all()
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289
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290
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291 # --------------------------------------------------
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292 # session
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293 # --------------------------------------------------
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294
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295 saver = tf.train.Saver()
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296 sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) # config parameter needed to save variables when using GPU
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297
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298 if os.path.exists(outLogPath):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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299 shutil.rmtree(outLogPath)
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300 trainWriter = tf.summary.FileWriter(trainWriterPath, sess.graph)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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301 validWriter = tf.summary.FileWriter(validWriterPath, sess.graph)
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302
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303 if restoreVariables:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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304 saver.restore(sess, outModelPath)
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305 print("Model restored.")
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306 else:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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307 sess.run(tf.global_variables_initializer())
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308
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309 # --------------------------------------------------
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310 # train
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diff changeset
311 # --------------------------------------------------
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312
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313 batchData = np.zeros((batchSize,imSize,imSize,nChannels))
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314 batchLabels = np.zeros((batchSize,imSize,imSize,nClasses))
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315 for i in range(nSteps):
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316 # train
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317
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318 perm = np.arange(nTrain)
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319 np.random.shuffle(perm)
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320
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
321 for j in range(batchSize):
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322 batchData[j,:,:,:] = Train[perm[j],:,:,:]
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diff changeset
323 batchLabels[j,:,:,:] = LTrain[perm[j],:,:,:]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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324
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diff changeset
325 summary,_ = sess.run([merged,optOp],feed_dict={UNet2D.tfData: batchData, tfLabels: batchLabels, UNet2D.tfTraining: 1})
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
326 trainWriter.add_summary(summary, i)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
327
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
328 # validation
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diff changeset
329
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
330 perm = np.arange(nValid)
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diff changeset
331 np.random.shuffle(perm)
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diff changeset
332
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
333 for j in range(batchSize):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
334 batchData[j,:,:,:] = Valid[perm[j],:,:,:]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
335 batchLabels[j,:,:,:] = LValid[perm[j],:,:,:]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
336
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
337 summary, es = sess.run([merged, errors],feed_dict={UNet2D.tfData: batchData, tfLabels: batchLabels, UNet2D.tfTraining: 0})
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diff changeset
338 validWriter.add_summary(summary, i)
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diff changeset
339
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
340 e = np.mean(es)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
341 print('step %05d, e: %f' % (i,e))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
342
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
343 if i == 0:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
344 if restoreVariables:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
345 lowestError = e
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diff changeset
346 else:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
347 lowestError = np.inf
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
348
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
349 if np.mod(i,100) == 0 and e < lowestError:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
350 lowestError = e
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
351 print("Model saved in file: %s" % saver.save(sess, outModelPath))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
352
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
353
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
354 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
355 # test
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
356 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
357
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
358 if not os.path.exists(outPMPath):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
359 os.makedirs(outPMPath)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
360
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
361 for i in range(nTest):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
362 j = np.mod(i,batchSize)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
363
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
364 batchData[j,:,:,:] = Test[i,:,:,:]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
365 batchLabels[j,:,:,:] = LTest[i,:,:,:]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
366
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
367 if j == batchSize-1 or i == nTest-1:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
368
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
369 output = sess.run(UNet2D.nn,feed_dict={UNet2D.tfData: batchData, tfLabels: batchLabels, UNet2D.tfTraining: 0})
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
370
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
371 for k in range(j+1):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
372 pm = output[k,:,:,testPMIndex]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
373 gt = batchLabels[k,:,:,testPMIndex]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
374 im = np.sqrt(normalize(batchData[k,:,:,0]))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
375 imwrite(np.uint8(255*np.concatenate((im,np.concatenate((pm,gt),axis=1)),axis=1)),'%s/I%05d.png' % (outPMPath,i-j+k+1))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
376
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
377
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
378 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
379 # save hyper-parameters, clean-up
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
380 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
381
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
382 saveData(UNet2D.hp,pathjoin(modelPath,'hp.data'))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
383
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
384 trainWriter.close()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
385 validWriter.close()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
386 sess.close()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
387
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
388 def deploy(imPath,nImages,modelPath,pmPath,gpuIndex,pmIndex):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
389 os.environ['CUDA_VISIBLE_DEVICES']= '%d' % gpuIndex
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
390
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
391 variablesPath = pathjoin(modelPath,'model.ckpt')
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
392 outPMPath = pmPath
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
393
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
394 hp = loadData(pathjoin(modelPath,'hp.data'))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
395 UNet2D.setupWithHP(hp)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
396
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
397 batchSize = UNet2D.hp['batchSize']
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
398 imSize = UNet2D.hp['imSize']
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
399 nChannels = UNet2D.hp['nChannels']
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
400 nClasses = UNet2D.hp['nClasses']
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
401
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
402 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
403 # data
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
404 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
405
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
406 Data = np.zeros((nImages,imSize,imSize,nChannels))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
407
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
408 datasetMean = loadData(pathjoin(modelPath,'datasetMean.data'))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
409 datasetStDev = loadData(pathjoin(modelPath,'datasetStDev.data'))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
410
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
411 for iSample in range(0, nImages):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
412 path = '%s/I%05d_Img.tif' % (imPath,iSample)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
413 im = im2double(tifread(path))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
414 #im = im[0, 0, 0, :, :]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
415 Data[iSample,:,:,0] = (im-datasetMean)/datasetStDev
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
416
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
417 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
418 # session
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
419 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
420
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
421 saver = tf.train.Saver()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
422 sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) # config parameter needed to save variables when using GPU
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
423
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
424 saver.restore(sess, variablesPath)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
425 print("Model restored.")
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
426
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
427 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
428 # deploy
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
429 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
430
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
431 batchData = np.zeros((batchSize,imSize,imSize,nChannels))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
432
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
433 if not os.path.exists(outPMPath):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
434 os.makedirs(outPMPath)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
435
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
436 for i in range(nImages):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
437 print(i,nImages)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
438
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
439 j = np.mod(i,batchSize)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
440
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
441 batchData[j,:,:,:] = Data[i,:,:,:]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
442
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
443 if j == batchSize-1 or i == nImages-1:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
444
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
445 output = sess.run(UNet2D.nn,feed_dict={UNet2D.tfData: batchData, UNet2D.tfTraining: 0})
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
446
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
447 for k in range(j+1):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
448 pm = output[k,:,:,pmIndex]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
449 im = np.sqrt(normalize(batchData[k,:,:,0]))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
450 # imwrite(np.uint8(255*np.concatenate((im,pm),axis=1)),'%s/I%05d.png' % (outPMPath,i-j+k+1))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
451 imwrite(np.uint8(255*im),'%s/I%05d_Im.png' % (outPMPath,i-j+k+1))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
452 imwrite(np.uint8(255*pm),'%s/I%05d_PM.png' % (outPMPath,i-j+k+1))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
453
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
perssond
parents:
diff changeset
454
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
455 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
456 # clean-up
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
457 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
458
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
459 sess.close()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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parents:
diff changeset
460
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
461 def singleImageInferenceSetup(modelPath,gpuIndex):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
462 os.environ['CUDA_VISIBLE_DEVICES']= '%d' % gpuIndex
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
463
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
464 variablesPath = pathjoin(modelPath,'model.ckpt')
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
465
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
466 hp = loadData(pathjoin(modelPath,'hp.data'))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
467 UNet2D.setupWithHP(hp)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
468
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
469 UNet2D.DatasetMean = loadData(pathjoin(modelPath,'datasetMean.data'))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
470 UNet2D.DatasetStDev = loadData(pathjoin(modelPath,'datasetStDev.data'))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
471 print(UNet2D.DatasetMean)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
472 print(UNet2D.DatasetStDev)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
473
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
474 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
475 # session
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
476 # --------------------------------------------------
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
477
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
478 saver = tf.train.Saver()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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479 UNet2D.Session = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) # config parameter needed to save variables when using GPU
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
480
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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481 saver.restore(UNet2D.Session, variablesPath)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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482 print("Model restored.")
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
483
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
484 def singleImageInferenceCleanup():
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
485 UNet2D.Session.close()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
486
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
487 def singleImageInference(image,mode,pmIndex):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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488 print('Inference...')
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
489
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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490 batchSize = UNet2D.hp['batchSize']
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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491 imSize = UNet2D.hp['imSize']
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
492 nChannels = UNet2D.hp['nChannels']
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
493
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
494 PI2D.setup(image,imSize,int(imSize/8),mode)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
495 PI2D.createOutput(nChannels)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
496
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
497 batchData = np.zeros((batchSize,imSize,imSize,nChannels))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
498 for i in range(PI2D.NumPatches):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
499 j = np.mod(i,batchSize)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
500 batchData[j,:,:,0] = (PI2D.getPatch(i)-UNet2D.DatasetMean)/UNet2D.DatasetStDev
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
501 if j == batchSize-1 or i == PI2D.NumPatches-1:
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
502 output = UNet2D.Session.run(UNet2D.nn,feed_dict={UNet2D.tfData: batchData, UNet2D.tfTraining: 0})
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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503 for k in range(j+1):
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
504 pm = output[k,:,:,pmIndex]
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
505 PI2D.patchOutput(i-j+k,pm)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
506 # PI2D.patchOutput(i-j+k,normalize(imgradmag(PI2D.getPatch(i-j+k),1)))
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
507
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
508 return PI2D.getValidOutput()
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
509
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
510
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
511 if __name__ == '__main__':
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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512 logPath = 'D:\\LSP\\UNet\\Coreograph\\TFLogs'
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
513 modelPath = 'D:\\LSP\\Coreograph\\model-4layersMaskAug20New'
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
514 pmPath = 'D:\\LSP\\UNet\\Coreograph\\TFProbMaps'
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
515
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
516
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
517 # ----- test 1 -----
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
518
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
519 # imPath = 'D:\\LSP\\UNet\\tonsil20x1bin1chan\\tonsilAnnotations'
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
520 imPath = 'Z:/IDAC/Clarence/LSP/CyCIF/TMA/training data custom unaveraged'
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
521 # UNet2D.setup(128,1,2,8,2,2,3,1,0.1,2,8)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
522 # UNet2D.train(imPath,logPath,modelPath,pmPath,500,100,40,True,20000,1,0)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
523 UNet2D.setup(128, 1, 2, 20, 2, 2, 3, 2, 0.03, 4, 32)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
524 UNet2D.train(imPath, logPath, modelPath, pmPath, 2053, 513 , 641, True, 10, 1, 1)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
525 UNet2D.deploy(imPath,100,modelPath,pmPath,1,1)
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
526
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
527
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
528
99308601eaa6 "planemo upload for repository https://github.com/ohsu-comp-bio/UNetCoreograph commit fb90660a1805b3f68fcff80d525b5459c3f7dfd6-dirty"
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diff changeset
529