def internal_update( self ):
self.load_network()
from mmdet.datasets.custom import CustomDataset
signal.signal( signal.SIGINT, lambda signal, frame: self.interupt_handler() )
train_dataset = CustomDataset(
self._training_store,
self._cfg.train_pipeline )
if self._validate:
validation_dataset = CustomDataset(
self._validation_store,
self._cfg.test_pipeline )
self._cfg.data.val = validation_dataset
self._cfg.data.val.type = "CustomDataset"
from mmdet.apis import train_detector
train_detector(
self._model,
train_dataset,
self._cfg,
distributed = self._distributed,
validate = self._validate )
def update_model(self):
with open(self._groundtruth_store, 'wb') as fp:
pickle.dump(self._training_data, fp)
from mmdet.datasets.custom import CustomDataset
train_dataset = CustomDataset(
self._groundtruth_store,
'.',
self._cfg.data.train.img_scale,
self._cfg.data.train.img_norm_cfg,
size_divisor=self._cfg.data.train.size_divisor,
flip_ratio=self._cfg.data.train.flip_ratio,
with_mask=self._cfg.data.train.with_mask,
with_crowd=self._cfg.data.train.with_crowd,
with_label=self._cfg.data.train.with_label)
from mmdet.apis import train_detector
train_detector(self._model,
train_dataset,
self._cfg,
distributed=self._distributed,
validate=self._validate,
logger=self._logger)
def internal_update(self):
self.load_network()
with open(self._groundtruth_store, 'wb') as fp:
pickle.dump(self._training_data, fp)
from mmdet.datasets.custom import CustomDataset
signal.signal(signal.SIGINT,
lambda signal, frame: self.interupt_handler())
train_dataset = CustomDataset(
self._groundtruth_store,
'.',
self._cfg.data.train.img_scale,
self._cfg.data.train.img_norm_cfg,
size_divisor=self._cfg.data.train.size_divisor,
flip_ratio=self._cfg.data.train.flip_ratio,
with_mask=self._cfg.data.train.with_mask,
with_crowd=self._cfg.data.train.with_crowd,
with_label=self._cfg.data.train.with_label)
from mmdet.apis import train_detector
self.save_model_files(is_final=False)
train_detector(self._model,
train_dataset,
self._cfg,
distributed=self._distributed,
validate=self._validate,
logger=self._logger)
self.save_model_files(is_final=True)
def internal_update(self):
self.load_network()
with open(self._groundtruth_store, 'wb') as fp:
pickle.dump(self._training_data, fp)
from mmdet.datasets.custom import CustomDataset
signal.signal(signal.SIGINT,
lambda signal, frame: self.interupt_handler())
train_dataset = CustomDataset(self._groundtruth_store,
self._cfg.train_pipeline)
from mmdet.apis import train_detector
self.save_model_files(is_final=False)
train_detector(self._model,
train_dataset,
self._cfg,
distributed=self._distributed,
validate=self._validate,
logger=self._logger)
self.save_model_files(is_final=True)