def get_data_prms(**kwargs): dArgs = edict() dArgs.folderName = 'nicks-house' dArgs.subFolderName = 'Angle1Lighting1' #Save the parameters in a database dbFile = DB % 'folder-data' dArgs.prmStr = msq.get_sql_id(dbFile, dArgs) return dArgs
def get_rcnn_prms(**kwargs): dArgs = edict() #Object class that needs to be detected dArgs.targetClass = 'person' #NMS dArgs.nmsThresh = 0.3 #Detection Confidence dArgs.confThresh = 0.8 dArgs.topK = 5 #What classnames was the detector trained on. dArgs.trainDataSet = 'pascal' #The net to be used dArgs.netName = 'vgg16-pascal-rcnn' dArgs = cu.get_defaults(kwargs, dArgs, True) #Save the parameters in a database dbFile = DB % 'rcnn' dArgs.prmStr = 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 #assert set(dArgs.targetClass).issubset(set(allCls)),\ # '%s cannot be detected' % dArgs.targetClass return dArgs