def __init__(self, project, config, dbConnector, fileServer, options):
super(TridentNet, self).__init__(project, config, dbConnector,
fileServer, options)
try:
# check options
if self.detectron2cfg.MODEL.META_ARCHITECTURE != 'GeneralizedRCNN':
raise Exception(
f'Invalid meta architecture ("{self.detectron2cfg.MODEL.META_ARCHITECTURE}" != "GeneralizedRCNN")'
)
if self.detectron2cfg.MODEL.ROI_HEADS.NAME != 'TridentRes5ROIHeads':
raise Exception(
f'Invalid ROI head architecture ("{self.detectron2cfg.MODEL.ROI_HEADS.NAME}" != "TridentRes5ROIHeads")'
)
if self.detectron2cfg.MODEL.PROPOSAL_GENERATOR.NAME != 'TridentRPN':
raise Exception(
f'Invalid proposal generator ("{self.detectron2cfg.MODEL.PROPOSAL_GENERATOR.NAME}" != "TridentRPN")'
)
assert hasattr(self.detectron2cfg.MODEL,
'TRIDENT'), 'Missing "TRIDENT" option'
except Exception as e:
print(
f'[{self.project}] WARNING: provided options are not valid for TridentNet (message: "{str(e)}"); falling back to defaults.'
)
self.options = self.getDefaultOptions()
self.detectron2cfg = self._get_config()
self.detectron2cfg = GenericDetectron2Model.parse_aide_config(
self.options, self.detectron2cfg)
def getDefaultOptions(cls):
opts = GenericDetectron2Model._load_default_options(
'config/ai/model/detectron2/labels/mobilenetv2.json',
DEFAULT_OPTIONS
)
opts['defs']['model'] = 'labels/mobilenet_v2_ImageNet.yaml'
return opts
def __init__(self, project, config, dbConnector, fileServer, options):
super(RetinaNet, self).__init__(project, config, dbConnector, fileServer, options)
try:
if self.detectron2cfg.MODEL.META_ARCHITECTURE != 'RetinaNet':
# invalid options provided
raise Exception('Invalid model architecture')
except:
print('WARNING: provided options are not valid for RetinaNet; falling back to defaults.')
self.options = self.getDefaultOptions()
self.detectron2cfg = self._get_config()
self.detectron2cfg = GenericDetectron2Model.parse_aide_config(self.options, self.detectron2cfg)
def __init__(self, project, config, dbConnector, fileServer, options):
super(GeneralizedTorchvisionClassifier,
self).__init__(project, config, dbConnector, fileServer, options)
try:
if self.detectron2cfg.MODEL.META_ARCHITECTURE != 'TorchvisionClassifier':
# invalid options provided
raise Exception('Invalid model meta architecture')
except:
print(
f'[{self.project}] WARNING: provided options are not valid for the Torchvision classifier model; falling back to defaults.'
)
self.options = self.getDefaultOptions()
self.detectron2cfg = self._get_config()
self.detectron2cfg = GenericDetectron2Model.parse_aide_config(
self.options, self.detectron2cfg)
def __init__(self, project, config, dbConnector, fileServer, options):
super(FasterRCNN, self).__init__(project, config, dbConnector,
fileServer, options)
try:
if self.detectron2cfg.MODEL.META_ARCHITECTURE != 'GeneralizedRCNN':
# invalid options provided
raise Exception(
f'Invalid meta architecture ("{self.detectron2cfg.MODEL.META_ARCHITECTURE}" != "GeneralizedRCNN")'
)
except Exception as e:
print(
f'[{self.project}] WARNING: provided options are not valid for Faster R-CNN (message: "{str(e)}"); falling back to defaults.'
)
self.options = self.getDefaultOptions()
self.detectron2cfg = self._get_config()
self.detectron2cfg = GenericDetectron2Model.parse_aide_config(
self.options, self.detectron2cfg)
#TODO: Faster R-CNN currently does not work with empty images
self.detectron2cfg.DATALOADER.FILTER_EMPTY_ANNOTATIONS = True
def getDefaultOptions(cls):
return GenericDetectron2Model._load_default_options(
'config/ai/model/detectron2/boundingBoxes/tridentnet.json',
DEFAULT_OPTIONS)
def getDefaultOptions(cls):
return GenericDetectron2Model._load_default_options(
'config/ai/model/detectron2/segmentationMasks/deeplabv3plus.json',
DEFAULT_OPTIONS
)