Exemple #1
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def get_data_prms(folderName='nicks-house', subFolderName='Angle1Lighting1'):
	dArgs = edict()
	dArgs.folderName    = folderName
	dArgs.subFolderName = subFolderName
	#Save the parameters in a database
	dbFile  = DB % 'folder-data'
	dArgs.prmStr = msq.get_sql_id(dbFile, dArgs)	
	return dArgs
Exemple #2
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def get_vatic_prms(**kwargs):
  dArgs = edict()
  pths  = get_basic_paths()
  #Directory where vatic data is
  dArgs.vaticDr   = pths.vatic.dr
  #Directory where vatic data should be output
  dArgs.vaticOpDr = '/mnt/HardDrive/common/vatic' 	
  #merge_threshold - dictates how vatic annotatiosn are merged
  #no need to change this
  dArgs.mergeThreshold = 0.5
	#Save the parameters in a database
  dbFile  = DB % 'vatic'
  dArgs.prmStr = msq.get_sql_id(dbFile, dArgs, 
                ignoreKeys=['vaticDr', 'vaticOpDr'])	
  return dArgs
Exemple #3
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def set_rcnn_prms(**kwargs):
	dArgs = edict()
	#Object class that needs to be detected
	dArgs.targetClass = kwargs.get('targetClass', 'person')
	#NMS
	dArgs.nmsThresh  = kwargs.get('nmsThresh', 0.3)
	#Detection Confidence
	dArgs.confThresh = kwargs.get('confThresh', 0.8)
	dArgs.topK       = kwargs.get('topK', 5)
	#What classnames was the detector trained on.
	dArgs.trainDataSet = kwargs.get('trainDataSet', 'coco')
	#The net to be used 
	dArgs.netName    = kwargs.get('netName', 'vgg16-coco-rcnn')
	dArgs   = cu.get_defaults(kwargs, dArgs, True)
	#Save the parameters in a database
	dbFile  = DB % 'rcnn'
	dArgs._mysqlid = msq.get_sql_id(dbFile, dArgs)	
	#verify that the target class is detectable by the model
	allCls  = dataset2classnames(dArgs.trainDataSet)
	assert dArgs.targetClass in allCls
	return dArgs