Shortcuts

InstanceSegmentation

class flash.image.instance_segmentation.model.InstanceSegmentation(num_classes, backbone='resnet18_fpn', head='mask_rcnn', pretrained=True, optimizer='Adam', lr_scheduler=None, learning_rate=None, output_transform=<flash.image.instance_segmentation.data.InstanceSegmentationOutputTransform object>, predict_kwargs=None, **kwargs)[source]

The InstanceSegmentation is a Task for detecting objects in images. For more details, see Object Detection.

Parameters
classmethod available_finetuning_strategies(cls)

Returns a list containing the keys of the available Finetuning Strategies.

Return type

List[str]

classmethod available_lr_schedulers(cls)

Returns a list containing the keys of the available LR schedulers.

Return type

List[str]

classmethod available_optimizers(cls)

Returns a list containing the keys of the available Optimizers.

Return type

List[str]

classmethod available_outputs(cls)

Returns the list of available outputs (that can be used during prediction or serving) for this Task.

Examples

..testsetup:

>>> from flash import Task
>>> print(Task.available_outputs())
['preds', 'raw']
Return type

List[str]

property predict_kwargs: Dict[str, Any]

The kwargs used for the prediction step.

Return type

Dict[str, Any]

Read the Docs v: latest
Versions
latest
stable
0.7.5
0.7.4
0.7.3
0.7.2
0.7.1
0.7.0
0.6.0
0.5.2
0.5.1
0.5.0
0.4.0
0.3.2
0.3.1
0.3.0
0.2.3
0.2.2
0.2.1
0.2.0
0.1.0post1
docs-fix_typing
Downloads
html
On Read the Docs
Project Home
Builds

Free document hosting provided by Read the Docs.