|---| | [ View source on GitHub](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/interactive_segmenter_legacy.py#L183-L348) | Class that performs interactive segmentation on images. ```python mp.tasks.vision.InteractiveSegmenterLegacy( lib: serial_dispatcher.SerialDispatcher, handle: ctypes.c_void_p, dispatcher: async_result_dispatcher.AsyncResultDispatcher ) ``` Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenterLegacy to perform segmentation focusing on the given region of interest. The API expects a TFLite model with mandatory TFLite Model Metadata.


| ## Input tensor || |---|---| | (kTfLiteUInt8/kTfLiteFloat32) - image input of size `[batch x height x width x channels]`. - batch inference is not supported (`batch` is required to be 1). - RGB and greyscale inputs are supported (`channels` is required to be 1 or 3). - if type is kTfLiteFloat32, NormalizationOptions are required to be attached to the metadata for input normalization. ||



| ## Output tensors || |---|---| | (kTfLiteUInt8/kTfLiteFloat32) - list of segmented masks. - if `output_type` is CATEGORY_MASK, uint8 Image, Image vector of size 1. - if `output_type` is CONFIDENCE_MASK, float32 Image list of size `channels`. - batch is always 1 ||
An example of such model can be found at: https://tfhub.dev/tensorflow/lite-model/deeplabv3/1/metadata/2 ## Methods ### `close` [View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/interactive_segmenter_legacy.py#L329-L336) ```python close() ``` Closes the InteractiveSegmenterLegacy. ### `create_from_model_path` [View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/interactive_segmenter_legacy.py#L228-L254) ```python @classmethod create_from_model_path( model_path: str ) -> 'InteractiveSegmenterLegacy' ``` Creates an `InteractiveSegmenterLegacy` object from a TensorFlow Lite model and the default `InteractiveSegmenterLegacyOptions`. Note that the created `InteractiveSegmenterLegacy` instance is in image mode, for performing image segmentation on single image inputs.


| Args || |---|---| | `model_path` | Path to the model. |



| Returns || |---|---| | `InteractiveSegmenterLegacy` object that's created from the model file and the default `InteractiveSegmenterLegacyOptions`. ||



| Raises || |---|---| | `ValueError` | If failed to create `InteractiveSegmenterLegacy` object from the provided file such as invalid file path. | | `RuntimeError` | If other types of error occurred. |
### `create_from_options` [View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/interactive_segmenter_legacy.py#L256-L281) ```python @classmethod create_from_options( options: `mp.tasks.vision.InteractiveSegmenterLegacyOptions` ) -> 'InteractiveSegmenterLegacy' ``` Creates the `InteractiveSegmenterLegacy` object from interactive segmenter options.


| Args || |---|---| | `options` | Options for the interactive segmenter task. |



| Returns || |---|---| | `InteractiveSegmenterLegacy` object that's created from `options`. ||



| Raises || |---|---| | `ValueError` | If failed to create `InteractiveSegmenterLegacy` object from `InteractiveSegmenterLegacyOptions` such as missing the model. | | `RuntimeError` | If other types of error occurred. |
### `segment` [View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/interactive_segmenter_legacy.py#L283-L327) ```python segment( image: `mp.Image`, roi: `mp.tasks.vision.InteractiveSegmenterLegacyRegionOfInterest`, image_processing_options: Optional[`mp.tasks.vision.ImageProcessingOptions`] = None ) -> InteractiveSegmenterLegacyResult ``` Performs the actual segmentation task on the provided MediaPipe Image. The image can be of any size with format RGB.


| Args || |---|---| | `image` | MediaPipe Image. | | `roi` | Optional user-specified region of interest for segmentation. | | `image_processing_options` | Options for image processing. |



| Returns || |---|---| | If the output_type is CATEGORY_MASK, the returned vector of images is per-category segmented image mask. If the output_type is CONFIDENCE_MASK, the returned vector of images contains only one confidence image mask. A segmentation result object that contains a list of segmentation masks as images. ||



| Raises || |---|---| | `ValueError` | If any of the input arguments is invalid. | | `RuntimeError` | If image segmentation failed to run. |
### `__enter__` [View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/interactive_segmenter_legacy.py#L338-L340) ```python __enter__() ``` Returns `self` upon entering the runtime context. ### `__exit__` [View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/interactive_segmenter_legacy.py#L342-L345) ```python __exit__( exc_type, exc_value, traceback ) ``` Shuts down the MediaPipe task instance on exit of the context manager.