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)