def get_learner_config(self, pipeline):
data = SemanticSegmentationDataConfig()
data.uri = pipeline.chip_uri
data.class_names = pipeline.dataset.class_config.names
data.class_colors = pipeline.dataset.class_config.colors
data.img_sz = pipeline.train_chip_sz
data.augmentors = self.augmentors
learner = SemanticSegmentationLearnerConfig(
data=data,
model=self.model,
solver=self.solver,
test_mode=self.test_mode,
output_uri=pipeline.train_uri,
log_tensorboard=self.log_tensorboard,
run_tensorboard=self.run_tensorboard)
learner.update()
return learner
def get_learner_config(self, pipeline):
data = SemanticSegmentationDataConfig(
uri=pipeline.chip_uri,
class_names=pipeline.dataset.class_config.names,
class_colors=pipeline.dataset.class_config.colors,
img_sz=pipeline.train_chip_sz,
img_channels=pipeline.dataset.img_channels,
img_format=pipeline.img_format,
label_format=pipeline.label_format,
num_workers=self.num_workers,
augmentors=self.augmentors,
base_transform=self.base_transform,
aug_transform=self.aug_transform,
plot_options=self.plot_options,
channel_display_groups=pipeline.channel_display_groups)
learner = SemanticSegmentationLearnerConfig(
data=data,
model=self.model,
solver=self.solver,
test_mode=self.test_mode,
output_uri=pipeline.train_uri,
log_tensorboard=self.log_tensorboard,
run_tensorboard=self.run_tensorboard)
learner.update()
learner.validate_config()
return learner
def get_learner_config(self, pipeline):
learner = SemanticSegmentationLearnerConfig(
data=self.data,
model=self.model,
solver=self.solver,
test_mode=self.test_mode,
output_uri=pipeline.train_uri,
log_tensorboard=self.log_tensorboard,
run_tensorboard=self.run_tensorboard)
learner.update()
learner.validate_config()
return learner