Exemplo n.º 1
0
outDir = "/home/sheng/mountData/unaryDepthInference/"
runDir = outDir + "/testRun/"
plotDir = runDir + "plots/"

if not os.path.exists(runDir):
   os.makedirs(runDir)

if not os.path.exists(plotDir):
   os.makedirs(plotDir)

load = True
loadFile = outDir + "/saved/saved.ckpt"

#Get object from which tensorflow will pull data from
testDataObj = kittiObj(imageList, depthList)

#Allocate obj to calc mean/std
trainDataObj = kittiObj(trainImageList, trainDepthList)

#Set mean/std on test set
testDataObj.setMeanVar(trainDataObj.mean, trainDataObj.std)

vggFile = "/home/sheng/mountData/pretrain/imagenet-vgg-f.mat"
#Allocate tf obj with test data
tfObj = unaryDepthInference(testDataObj, vggFile)

#Load weights
if(load):
   tfObj.loadModel(loadFile)
else:
Exemplo n.º 2
0
outDir = "/home/sheng/mountData/unaryDepthInference/"
runDir = outDir + "/run0/"
plotDir = runDir + "plots/"

if not os.path.exists(runDir):
   os.makedirs(runDir)

if not os.path.exists(plotDir):
   os.makedirs(plotDir)

load = False
loadFile = outDir + "/saved/saved.ckpt"

#Get object from which tensorflow will pull data from
trainDataObj = kittiObj(trainImageList, trainDepthList)
testDataObj = kittiObj(testImageList, testDepthList)

testDataObj.setMeanVar(trainDataObj.mean, trainDataObj.std)

##Get all segments
#(drop, gt) = dataObj.allSegments()
#plotImg(dataObj.currSegments, dataObj.segLabels, gt)
#plotImg(dataObj.currSegments, dataObj.segLabels, np.log(gt))
#
#plt.hist(gt)
#plt.show()
#
#plt.hist(np.log(gt))
#plt.show()
#
Exemplo n.º 3
0
outDir = "/home/sheng/mountData/unaryDepthInference/"
runDir = outDir + "/testRun/"
plotDir = runDir + "plots/"

if not os.path.exists(runDir):
    os.makedirs(runDir)

if not os.path.exists(plotDir):
    os.makedirs(plotDir)

load = True
loadFile = outDir + "/saved/saved.ckpt"

#Get object from which tensorflow will pull data from
testDataObj = kittiObj(imageList, depthList)

#Allocate obj to calc mean/std
trainDataObj = kittiObj(trainImageList, trainDepthList)

#Set mean/std on test set
testDataObj.setMeanVar(trainDataObj.mean, trainDataObj.std)

vggFile = "/home/sheng/mountData/pretrain/imagenet-vgg-f.mat"
#Allocate tf obj with test data
tfObj = unaryDepthInference(testDataObj, vggFile)

#Load weights
if (load):
    tfObj.loadModel(loadFile)
else: