def toImage( result ):
if result == None:
return
image = Image( result[0],purpose=result[1] )
image.segmentationReqTime = result[2]
image.segmentationTime = result[3]
image.segmentationPriority = result[4]
image.segmentationFile = result[5]
image.trainingTime = result[6]
image.trainingPriority = result[7]
image.trainingScore = result[8]
image.annotationTime = result[9]
image.annotationLockTime = result[10]
image.annotationStatus = result[11]
image.annotationLockId = result[12]
image.annotationFile = result[13]
image.modelModifiedTime = result[14]
image.creationTime = result[15]
image.startTime = result[16]
# set a flag when new segmentation is available
creationTime = time.strptime(image.creationTime, '%Y-%m-%d %H:%M:%S')
startTime = time.strptime(image.startTime, '%Y-%m-%d %H:%M:%S')
segTime = time.strptime(image.segmentationTime, '%Y-%m-%d %H:%M:%S')
modelTime = time.strptime(image.modelModifiedTime, '%Y-%m-%d %H:%M:%S')
image.hasNewModel = segTime < modelTime and startTime > creationTime
return image
def addImage(self, imageId, annFile=None, segFile=None, score=0.0, purpose='train'):
image = Image( imageId )
image.purpose = purpose
image.annotationFile = annFile
image.segmentationFile = segFile
image.traningScore = score
self.images.append( image )
def addImage(self,
imageId,
annFile=None,
segFile=None,
score=0.0,
purpose='train'):
image = Image(imageId)
image.purpose = purpose
image.annotationFile = annFile
image.segmentationFile = segFile
image.traningScore = score
self.images.append(image)
