Mercurial > repos > perssond > unmicst

annotate batchUNet2DTMACycif.py @ 0:6bec4fef6b2e draft

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"planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
author perssond
date Fri, 12 Mar 2021 00:17:29 +0000
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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 import skimage.exposure as sk
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8
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9 import sys
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10 sys.path.insert(0, 'C:\\Users\\Public\\Documents\\ImageScience')
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11 from toolbox.imtools import *
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12 from toolbox.ftools import *
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13 from toolbox.PartitionOfImage import PI2D
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14
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15
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16 def concat3(lst):
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17 return tf.concat(lst,3)
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18
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19 class UNet2D:
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20 hp = None # hyper-parameters
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21 nn = None # network
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22 tfTraining = None # if training or not (to handle batch norm)
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23 tfData = None # data placeholder
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24 Session = None
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25 DatasetMean = 0
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26 DatasetStDev = 0
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27
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28 def setupWithHP(hp):
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29 UNet2D.setup(hp['imSize'],
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30 hp['nChannels'],
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31 hp['nClasses'],
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32 hp['nOut0'],
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33 hp['featMapsFact'],
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34 hp['downSampFact'],
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35 hp['ks'],
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36 hp['nExtraConvs'],
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37 hp['stdDev0'],
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38 hp['nLayers'],
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39 hp['batchSize'])
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40
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41 def setup(imSize,nChannels,nClasses,nOut0,featMapsFact,downSampFact,kernelSize,nExtraConvs,stdDev0,nDownSampLayers,batchSize):
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42 UNet2D.hp = {'imSize':imSize,
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43 'nClasses':nClasses,
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44 'nChannels':nChannels,
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45 'nExtraConvs':nExtraConvs,
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46 'nLayers':nDownSampLayers,
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47 'featMapsFact':featMapsFact,
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48 'downSampFact':downSampFact,
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49 'ks':kernelSize,
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50 'nOut0':nOut0,
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51 'stdDev0':stdDev0,
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52 'batchSize':batchSize}
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53
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54 nOutX = [UNet2D.hp['nChannels'],UNet2D.hp['nOut0']]
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55 dsfX = []
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56 for i in range(UNet2D.hp['nLayers']):
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57 nOutX.append(nOutX[-1]*UNet2D.hp['featMapsFact'])
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58 dsfX.append(UNet2D.hp['downSampFact'])
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59
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60
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61 # --------------------------------------------------
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62 # downsampling layer
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63 # --------------------------------------------------
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64
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65 with tf.name_scope('placeholders'):
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66 UNet2D.tfTraining = tf.placeholder(tf.bool, name='training')
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67 UNet2D.tfData = tf.placeholder("float", shape=[None,UNet2D.hp['imSize'],UNet2D.hp['imSize'],UNet2D.hp['nChannels']],name='data')
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68
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69 def down_samp_layer(data,index):
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70 with tf.name_scope('ld%d' % index):
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71 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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72 ldXWeightsExtra = []
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73 for i in range(nExtraConvs):
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74 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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75
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76 c00 = tf.nn.conv2d(data, ldXWeights1, strides=[1, 1, 1, 1], padding='SAME')
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77 for i in range(nExtraConvs):
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78 c00 = tf.nn.conv2d(tf.nn.relu(c00), ldXWeightsExtra[i], strides=[1, 1, 1, 1], padding='SAME')
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79
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80 ldXWeightsShortcut = tf.Variable(tf.truncated_normal([1, 1, nOutX[index], nOutX[index+1]], stddev=stdDev0),name='shortcutWeights')
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81 shortcut = tf.nn.conv2d(data, ldXWeightsShortcut, strides=[1, 1, 1, 1], padding='SAME')
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82
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83 bn = tf.layers.batch_normalization(tf.nn.relu(c00+shortcut), training=UNet2D.tfTraining)
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84
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85 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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86
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87 # --------------------------------------------------
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88 # bottom layer
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89 # --------------------------------------------------
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90
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91 with tf.name_scope('lb'):
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92 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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93 def lb(hidden):
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94 return tf.nn.relu(tf.nn.conv2d(hidden, lbWeights1, strides=[1, 1, 1, 1], padding='SAME'),name='conv')
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95
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96 # --------------------------------------------------
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97 # downsampling
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98 # --------------------------------------------------
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99
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100 with tf.name_scope('downsampling'):
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101 dsX = []
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102 dsX.append(UNet2D.tfData)
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103
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104 for i in range(UNet2D.hp['nLayers']):
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105 dsX.append(down_samp_layer(dsX[i],i))
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106
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107 b = lb(dsX[UNet2D.hp['nLayers']])
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108
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109 # --------------------------------------------------
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110 # upsampling layer
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111 # --------------------------------------------------
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112
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113 def up_samp_layer(data,index):
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114 with tf.name_scope('lu%d' % index):
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115 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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116 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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117 luXWeightsExtra = []
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118 for i in range(nExtraConvs):
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119 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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120
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121 outSize = UNet2D.hp['imSize']
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122 for i in range(index):
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123 outSize /= dsfX[i]
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124 outSize = int(outSize)
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125
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126 outputShape = [UNet2D.hp['batchSize'],outSize,outSize,nOutX[index+1]]
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127 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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128 cc = concat3([dsX[index],us])
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129 cv = tf.nn.relu(tf.nn.conv2d(cc, luXWeights2, strides=[1, 1, 1, 1], padding='SAME'),name='conv2')
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130 for i in range(nExtraConvs):
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131 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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132 return cv
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133
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134 # --------------------------------------------------
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135 # final (top) layer
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136 # --------------------------------------------------
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137
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138 with tf.name_scope('lt'):
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139 ltWeights1 = tf.Variable(tf.truncated_normal([1, 1, nOutX[1], nClasses], stddev=stdDev0),name='kernel')
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140 def lt(hidden):
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141 return tf.nn.conv2d(hidden, ltWeights1, strides=[1, 1, 1, 1], padding='SAME',name='conv')
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142
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143
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144 # --------------------------------------------------
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145 # upsampling
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146 # --------------------------------------------------
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147
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148 with tf.name_scope('upsampling'):
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149 usX = []
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150 usX.append(b)
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151
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152 for i in range(UNet2D.hp['nLayers']):
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153 usX.append(up_samp_layer(usX[i],UNet2D.hp['nLayers']-1-i))
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154
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155 t = lt(usX[UNet2D.hp['nLayers']])
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156
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157
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158 sm = tf.nn.softmax(t,-1)
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159 UNet2D.nn = sm
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160
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161
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162 def train(imPath,logPath,modelPath,pmPath,nTrain,nValid,nTest,restoreVariables,nSteps,gpuIndex,testPMIndex):
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163 os.environ['CUDA_VISIBLE_DEVICES']= '%d' % gpuIndex
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164
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165 outLogPath = logPath
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166 trainWriterPath = pathjoin(logPath,'Train')
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167 validWriterPath = pathjoin(logPath,'Valid')
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168 outModelPath = pathjoin(modelPath,'model.ckpt')
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169 outPMPath = pmPath
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170
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171 batchSize = UNet2D.hp['batchSize']
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172 imSize = UNet2D.hp['imSize']
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173 nChannels = UNet2D.hp['nChannels']
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174 nClasses = UNet2D.hp['nClasses']
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175
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176 # --------------------------------------------------
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diff changeset
177 # data
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178 # --------------------------------------------------
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179
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180 Train = np.zeros((nTrain,imSize,imSize,nChannels))
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181 Valid = np.zeros((nValid,imSize,imSize,nChannels))
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diff changeset
182 Test = np.zeros((nTest,imSize,imSize,nChannels))
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diff changeset
183 LTrain = np.zeros((nTrain,imSize,imSize,nClasses))
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184 LValid = np.zeros((nValid,imSize,imSize,nClasses))
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185 LTest = np.zeros((nTest,imSize,imSize,nClasses))
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186
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187 print('loading data, computing mean / st dev')
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188 if not os.path.exists(modelPath):
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189 os.makedirs(modelPath)
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190 if restoreVariables:
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191 datasetMean = loadData(pathjoin(modelPath,'datasetMean.data'))
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192 datasetStDev = loadData(pathjoin(modelPath,'datasetStDev.data'))
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diff changeset
193 else:
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194 datasetMean = 0
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195 datasetStDev = 0
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196 for iSample in range(nTrain+nValid+nTest):
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197 I = im2double(tifread('%s/I%05d_Img.tif' % (imPath,iSample)))
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198 datasetMean += np.mean(I)
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199 datasetStDev += np.std(I)
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200 datasetMean /= (nTrain+nValid+nTest)
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201 datasetStDev /= (nTrain+nValid+nTest)
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202 saveData(datasetMean, pathjoin(modelPath,'datasetMean.data'))
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parents:
diff changeset
203 saveData(datasetStDev, pathjoin(modelPath,'datasetStDev.data'))
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204
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205 perm = np.arange(nTrain+nValid+nTest)
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206 np.random.shuffle(perm)
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207
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208 for iSample in range(0, nTrain):
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209 path = '%s/I%05d_Img.tif' % (imPath,perm[iSample])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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210 im = im2double(tifread(path))
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diff changeset
211 Train[iSample,:,:,0] = (im-datasetMean)/datasetStDev
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diff changeset
212 path = '%s/I%05d_Ant.tif' % (imPath,perm[iSample])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
213 im = tifread(path)
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diff changeset
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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diff changeset
217 for iSample in range(0, nValid):
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diff changeset
218 path = '%s/I%05d_Img.tif' % (imPath,perm[nTrain+iSample])
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diff changeset
219 im = im2double(tifread(path))
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diff changeset
220 Valid[iSample,:,:,0] = (im-datasetMean)/datasetStDev
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diff changeset
221 path = '%s/I%05d_Ant.tif' % (imPath,perm[nTrain+iSample])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
222 im = tifread(path)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
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223 for i in range(nClasses):
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diff changeset
224 LValid[iSample,:,:,i] = (im == i+1)
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diff changeset
225
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
226 for iSample in range(0, nTest):
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diff changeset
227 path = '%s/I%05d_Img.tif' % (imPath,perm[nTrain+nValid+iSample])
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parents:
diff changeset
228 im = im2double(tifread(path))
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diff changeset
229 Test[iSample,:,:,0] = (im-datasetMean)/datasetStDev
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
230 path = '%s/I%05d_Ant.tif' % (imPath,perm[nTrain+nValid+iSample])
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parents:
diff changeset
231 im = tifread(path)
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parents:
diff changeset
232 for i in range(nClasses):
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parents:
diff changeset
233 LTest[iSample,:,:,i] = (im == i+1)
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diff changeset
234
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
235 # --------------------------------------------------
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perssond
parents:
diff changeset
236 # optimization
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parents:
diff changeset
237 # --------------------------------------------------
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diff changeset
238
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
239 tfLabels = tf.placeholder("float", shape=[None,imSize,imSize,nClasses],name='labels')
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
240
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
241 globalStep = tf.Variable(0,trainable=False)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
242 learningRate0 = 0.01
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
243 decaySteps = 1000
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parents:
diff changeset
244 decayRate = 0.95
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parents:
diff changeset
245 learningRate = tf.train.exponential_decay(learningRate0,globalStep,decaySteps,decayRate,staircase=True)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
246
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perssond
parents:
diff changeset
247 with tf.name_scope('optim'):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
248 loss = tf.reduce_mean(-tf.reduce_sum(tf.multiply(tfLabels,tf.log(UNet2D.nn)),3))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
249 updateOps = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
250 # optimizer = tf.train.MomentumOptimizer(1e-3,0.9)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
251 optimizer = tf.train.MomentumOptimizer(learningRate,0.9)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
252 # optimizer = tf.train.GradientDescentOptimizer(learningRate)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
253 with tf.control_dependencies(updateOps):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
254 optOp = optimizer.minimize(loss,global_step=globalStep)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
255
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
256 with tf.name_scope('eval'):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
257 error = []
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
258 for iClass in range(nClasses):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
259 labels0 = tf.reshape(tf.to_int32(tf.slice(tfLabels,[0,0,0,iClass],[-1,-1,-1,1])),[batchSize,imSize,imSize])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
260 predict0 = tf.reshape(tf.to_int32(tf.equal(tf.argmax(UNet2D.nn,3),iClass)),[batchSize,imSize,imSize])
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261 correct = tf.multiply(labels0,predict0)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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262 nCorrect0 = tf.reduce_sum(correct)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
263 nLabels0 = tf.reduce_sum(labels0)
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diff changeset
264 error.append(1-tf.to_float(nCorrect0)/tf.to_float(nLabels0))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
265 errors = tf.tuple(error)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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266
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diff changeset
267 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
268 # inspection
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diff changeset
269 # --------------------------------------------------
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diff changeset
270
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
271 with tf.name_scope('scalars'):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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272 tf.summary.scalar('avg_cross_entropy', loss)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
273 for iClass in range(nClasses):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
274 tf.summary.scalar('avg_pixel_error_%d' % iClass, error[iClass])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
275 tf.summary.scalar('learning_rate', learningRate)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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276 with tf.name_scope('images'):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
277 split0 = tf.slice(UNet2D.nn,[0,0,0,0],[-1,-1,-1,1])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
278 split1 = tf.slice(UNet2D.nn,[0,0,0,1],[-1,-1,-1,1])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
279 if nClasses > 2:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
280 split2 = tf.slice(UNet2D.nn,[0,0,0,2],[-1,-1,-1,1])
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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281 tf.summary.image('pm0',split0)
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diff changeset
282 tf.summary.image('pm1',split1)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
283 if nClasses > 2:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
284 tf.summary.image('pm2',split2)
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diff changeset
285 merged = tf.summary.merge_all()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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286
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287
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diff changeset
288 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
289 # session
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parents:
diff changeset
290 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
291
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
292 saver = tf.train.Saver()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
293 sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) # config parameter needed to save variables when using GPU
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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294
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295 if os.path.exists(outLogPath):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
296 shutil.rmtree(outLogPath)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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297 trainWriter = tf.summary.FileWriter(trainWriterPath, sess.graph)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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298 validWriter = tf.summary.FileWriter(validWriterPath, sess.graph)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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299
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diff changeset
300 if restoreVariables:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
301 saver.restore(sess, outModelPath)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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302 print("Model restored.")
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
303 else:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
304 sess.run(tf.global_variables_initializer())
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
305
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
306 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
307 # train
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diff changeset
308 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
309
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
310 batchData = np.zeros((batchSize,imSize,imSize,nChannels))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
311 batchLabels = np.zeros((batchSize,imSize,imSize,nClasses))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
312 for i in range(nSteps):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
313 # train
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parents:
diff changeset
314
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parents:
diff changeset
315 perm = np.arange(nTrain)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
316 np.random.shuffle(perm)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
317
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
318 for j in range(batchSize):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
319 batchData[j,:,:,:] = Train[perm[j],:,:,:]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
320 batchLabels[j,:,:,:] = LTrain[perm[j],:,:,:]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
321
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
322 summary,_ = sess.run([merged,optOp],feed_dict={UNet2D.tfData: batchData, tfLabels: batchLabels, UNet2D.tfTraining: 1})
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
323 trainWriter.add_summary(summary, i)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
324
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
325 # validation
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parents:
diff changeset
326
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
327 perm = np.arange(nValid)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
328 np.random.shuffle(perm)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
329
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
330 for j in range(batchSize):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
331 batchData[j,:,:,:] = Valid[perm[j],:,:,:]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
332 batchLabels[j,:,:,:] = LValid[perm[j],:,:,:]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
333
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
334 summary, es = sess.run([merged, errors],feed_dict={UNet2D.tfData: batchData, tfLabels: batchLabels, UNet2D.tfTraining: 0})
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
335 validWriter.add_summary(summary, i)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
336
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
337 e = np.mean(es)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
338 print('step %05d, e: %f' % (i,e))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
339
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
340 if i == 0:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
341 if restoreVariables:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
342 lowestError = e
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
343 else:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
344 lowestError = np.inf
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
345
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
346 if np.mod(i,100) == 0 and e < lowestError:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
347 lowestError = e
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
348 print("Model saved in file: %s" % saver.save(sess, outModelPath))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
349
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
350
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
351 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
352 # test
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
353 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
354
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
355 if not os.path.exists(outPMPath):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
356 os.makedirs(outPMPath)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
357
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
358 for i in range(nTest):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
359 j = np.mod(i,batchSize)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
360
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
361 batchData[j,:,:,:] = Test[i,:,:,:]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
362 batchLabels[j,:,:,:] = LTest[i,:,:,:]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
363
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
364 if j == batchSize-1 or i == nTest-1:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
365
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
366 output = sess.run(UNet2D.nn,feed_dict={UNet2D.tfData: batchData, tfLabels: batchLabels, UNet2D.tfTraining: 0})
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
367
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
368 for k in range(j+1):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
369 pm = output[k,:,:,testPMIndex]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
370 gt = batchLabels[k,:,:,testPMIndex]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
371 im = np.sqrt(normalize(batchData[k,:,:,0]))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
372 imwrite(np.uint8(255*np.concatenate((im,np.concatenate((pm,gt),axis=1)),axis=1)),'%s/I%05d.png' % (outPMPath,i-j+k+1))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
373
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
374
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
375 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
376 # save hyper-parameters, clean-up
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
377 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
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diff changeset
378
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
379 saveData(UNet2D.hp,pathjoin(modelPath,'hp.data'))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
380
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
381 trainWriter.close()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
382 validWriter.close()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
383 sess.close()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
384
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
385 def deploy(imPath,nImages,modelPath,pmPath,gpuIndex,pmIndex):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
386 os.environ['CUDA_VISIBLE_DEVICES']= '%d' % gpuIndex
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
387
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
388 variablesPath = pathjoin(modelPath,'model.ckpt')
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
389 outPMPath = pmPath
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
390
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
391 hp = loadData(pathjoin(modelPath,'hp.data'))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
392 UNet2D.setupWithHP(hp)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
393
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
394 batchSize = UNet2D.hp['batchSize']
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
395 imSize = UNet2D.hp['imSize']
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
396 nChannels = UNet2D.hp['nChannels']
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
397 nClasses = UNet2D.hp['nClasses']
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
398
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
399 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
400 # data
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
401 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
402
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
403 Data = np.zeros((nImages,imSize,imSize,nChannels))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
404
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
405 datasetMean = loadData(pathjoin(modelPath,'datasetMean.data'))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
406 datasetStDev = loadData(pathjoin(modelPath,'datasetStDev.data'))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
407
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
408 for iSample in range(0, nImages):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
409 path = '%s/I%05d_Img.tif' % (imPath,iSample)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
410 im = im2double(tifread(path))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
411 Data[iSample,:,:,0] = (im-datasetMean)/datasetStDev
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
412
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
413 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
414 # session
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
415 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
416
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
417 saver = tf.train.Saver()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
418 sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) # config parameter needed to save variables when using GPU
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
419
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
420 saver.restore(sess, variablesPath)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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parents:
diff changeset
421 print("Model restored.")
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
422
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
423 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
424 # deploy
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
425 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
426
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
427 batchData = np.zeros((batchSize,imSize,imSize,nChannels))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
428
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
429 if not os.path.exists(outPMPath):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
430 os.makedirs(outPMPath)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
431
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
432 for i in range(nImages):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
433 print(i,nImages)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
434
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
435 j = np.mod(i,batchSize)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
436
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
437 batchData[j,:,:,:] = Data[i,:,:,:]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
438
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
439 if j == batchSize-1 or i == nImages-1:
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
perssond
parents:
diff changeset
440
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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441 output = sess.run(UNet2D.nn,feed_dict={UNet2D.tfData: batchData, UNet2D.tfTraining: 0})
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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442
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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443 for k in range(j+1):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
444 pm = output[k,:,:,pmIndex]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
445 im = np.sqrt(normalize(batchData[k,:,:,0]))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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446 # imwrite(np.uint8(255*np.concatenate((im,pm),axis=1)),'%s/I%05d.png' % (outPMPath,i-j+k+1))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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447 imwrite(np.uint8(255*im),'%s/I%05d_Im.png' % (outPMPath,i-j+k+1))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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448 imwrite(np.uint8(255*pm),'%s/I%05d_PM.png' % (outPMPath,i-j+k+1))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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449
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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450
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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451 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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452 # clean-up
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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453 # --------------------------------------------------
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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454
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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455 sess.close()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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456
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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457 def singleImageInferenceSetup(modelPath,gpuIndex):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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458 os.environ['CUDA_VISIBLE_DEVICES']= '%d' % gpuIndex
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459
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460 variablesPath = pathjoin(modelPath,'model.ckpt')
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461
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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462 hp = loadData(pathjoin(modelPath,'hp.data'))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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463 UNet2D.setupWithHP(hp)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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464
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465 UNet2D.DatasetMean = loadData(pathjoin(modelPath,'datasetMean.data'))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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466 UNet2D.DatasetStDev = loadData(pathjoin(modelPath,'datasetStDev.data'))
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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467 print(UNet2D.DatasetMean)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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468 print(UNet2D.DatasetStDev)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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469
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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470 # --------------------------------------------------
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471 # session
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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472 # --------------------------------------------------
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473
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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474 saver = tf.train.Saver()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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475 UNet2D.Session = tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) # config parameter needed to save variables when using GPU
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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476
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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477 saver.restore(UNet2D.Session, variablesPath)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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478 print("Model restored.")
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479
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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480 def singleImageInferenceCleanup():
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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481 UNet2D.Session.close()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
482
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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483 def singleImageInference(image,mode,pmIndex):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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484 print('Inference...')
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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485
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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486 batchSize = UNet2D.hp['batchSize']
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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487 imSize = UNet2D.hp['imSize']
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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488 nChannels = UNet2D.hp['nChannels']
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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489
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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490 PI2D.setup(image,imSize,int(imSize/8),mode)
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491 PI2D.createOutput(nChannels)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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492
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493 batchData = np.zeros((batchSize,imSize,imSize,nChannels))
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494 for i in range(PI2D.NumPatches):
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495 j = np.mod(i,batchSize)
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496 batchData[j,:,:,0] = (PI2D.getPatch(i)-UNet2D.DatasetMean)/UNet2D.DatasetStDev
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diff changeset
497 if j == batchSize-1 or i == PI2D.NumPatches-1:
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498 output = UNet2D.Session.run(UNet2D.nn,feed_dict={UNet2D.tfData: batchData, UNet2D.tfTraining: 0})
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499 for k in range(j+1):
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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500 pm = output[k,:,:,pmIndex]
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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501 PI2D.patchOutput(i-j+k,pm)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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502 # PI2D.patchOutput(i-j+k,normalize(imgradmag(PI2D.getPatch(i-j+k),1)))
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diff changeset
503
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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504 return PI2D.getValidOutput()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
505
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diff changeset
506
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
507 if __name__ == '__main__':
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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508 logPath = 'D:\\LSP\\Sinem\\fromOlympus\\TFLogsssssssss'
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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509 modelPath = 'D:\\LSP\\UNet\\tonsil20x1bin1chan\\TFModel - 3class 16 kernels 5ks 2 layers'
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
510 pmPath = 'D:\\LSP\\Sinem\\fromOlympus\\TFProbMaps'
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
511
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512
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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513 # ----- test 1 -----
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514
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515 # imPath = 'D:\\LSP\\Sinem\\trainingSetContours\\trainingSetSmallLarge'
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516 # # UNet2D.setup(128,1,2,8,2,2,3,1,0.1,2,8)
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517 # # UNet2D.train(imPath,logPath,modelPath,pmPath,500,100,40,True,20000,1,0)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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518 # UNet2D.setup(128, 1, 2, 12, 2, 2, 3, 4, 0.1, 4, 8)
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519 # UNet2D.train(imPath, logPath, modelPath, pmPath, 1600, 400, 500, False, 150000, 1, 0)
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520 # UNet2D.deploy(imPath,100,modelPath,pmPath,1,0)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
521
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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522 # I = im2double(tifread('/home/mc457/files/CellBiology/IDAC/Marcelo/Etc/UNetTestSets/SinemSaka_NucleiSegmentation_SingleImageInferenceTest3.tif'))
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diff changeset
523 # UNet2D.singleImageInferenceSetup(modelPath,0)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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524 # J = UNet2D.singleImageInference(I,'accumulate',0)
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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diff changeset
525 # UNet2D.singleImageInferenceCleanup()
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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526 # # imshowlist([I,J])
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527 # # sys.exit(0)
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528 # # tifwrite(np.uint8(255*I),'/home/mc457/Workspace/I1.tif')
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529 # # tifwrite(np.uint8(255*J),'/home/mc457/Workspace/I2.tif')
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530 # K = np.zeros((2,I.shape[0],I.shape[1]))
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531 # K[0,:,:] = I
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532 # K[1,:,:] = J
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533 # tifwrite(np.uint8(255*K),'/home/mc457/Workspace/Sinem_NucSeg.tif')
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534
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535 UNet2D.singleImageInferenceSetup(modelPath, 1)
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536 imagePath ='Y:/sorger/data/RareCyte/Clarence/NKI_TMA'
6bec4fef6b2e "planemo upload for repository https://github.com/ohsu-comp-bio/unmicst commit 73e4cae15f2d7cdc86719e77470eb00af4b6ebb7-dirty"
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537 sampleList = glob.glob(imagePath + '/ZTMA_18_810*')
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538 dapiChannel = 0
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539 for iSample in sampleList:
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540 # fileList = glob.glob(iSample + '//dearray//*.tif')
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541 fileList = [x for x in glob.glob(iSample + '/dearray/*.tif') if x != (iSample+'/dearray\\TMA_MAP.tif')]
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542 print(fileList)
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543 for iFile in fileList:
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544 fileName = os.path.basename(iFile)
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545 fileNamePrefix = fileName.split(os.extsep, 1)
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546 I = tifffile.imread(iFile, key=dapiChannel)
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547 I = im2double(sk.rescale_intensity(I, in_range=(np.min(I), np.max(I)), out_range=(0, 64424)))
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548 # I=np.moveaxis(I,0,-1)
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549 # I=I[:,:,0]
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550 hsize = int((float(I.shape[0])*float(1)))
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551 vsize = int((float(I.shape[1])*float(1)))
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552 I = resize(I,(hsize,vsize))
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553 #I = im2double(tifread('D:\\LSP\\cycif\\Unet\\Caitlin\\E - 04(fld 8 wv UV - DAPI)downsampled.tif'))
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554 outputPath = iSample + '//prob_maps'
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555 if not os.path.exists(outputPath):
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556 os.makedirs(outputPath)
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557 K = np.zeros((2,I.shape[0],I.shape[1]))
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558 contours = UNet2D.singleImageInference(I,'accumulate',1)
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559 K[1,:,:] = I
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560 K[0,:,:] = contours
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561 tifwrite(np.uint8(255 * K),
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562 outputPath + '//' + fileNamePrefix[0] + '_ContoursPM_' + str(dapiChannel + 1) + '.tif')
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563 del K
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564 K = np.zeros((1, I.shape[0], I.shape[1]))
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565 nuclei = UNet2D.singleImageInference(I,'accumulate',2)
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566 K[0, :, :] = nuclei
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567 tifwrite(np.uint8(255 * K),
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568 outputPath + '//' + fileNamePrefix[0] + '_NucleiPM_' + str(dapiChannel + 1) + '.tif')
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569 del K
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570 UNet2D.singleImageInferenceCleanup()
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571
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572
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573 # ----- test 2 -----
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574
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575 # imPath = '/home/mc457/files/CellBiology/IDAC/Marcelo/Etc/UNetTestSets/ClarenceYapp_NucleiSegmentation'
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576 # UNet2D.setup(128,1,2,8,2,2,3,1,0.1,3,4)
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577 # UNet2D.train(imPath,logPath,modelPath,pmPath,800,100,100,False,10,1)
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578 # UNet2D.deploy(imPath,100,modelPath,pmPath,1)
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579
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580
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diff changeset
581 # ----- test 3 -----
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582
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583 # imPath = '/home/mc457/files/CellBiology/IDAC/Marcelo/Etc/UNetTestSets/CarmanLi_CellTypeSegmentation'
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diff changeset
584 # # UNet2D.setup(256,1,2,8,2,2,3,1,0.1,3,4)
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diff changeset
585 # # UNet2D.train(imPath,logPath,modelPath,pmPath,1400,100,164,False,10000,1)
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586 # UNet2D.deploy(imPath,164,modelPath,pmPath,1)
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587
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588
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589 # ----- test 4 -----
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590
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591 # imPath = '/home/cicconet/Downloads/TrainSet1'
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592 # UNet2D.setup(64,1,2,8,2,2,3,1,0.1,3,4)
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593 # UNet2D.train(imPath,logPath,modelPath,pmPath,200,8,8,False,2000,1,0)
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594 # # UNet2D.deploy(imPath,164,modelPath,pmPath,1)