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|---|
| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3083-L3361) |

Class that performs face landmark detection on images.

    mp.tasks.vision.FaceLandmarker(
        lib: serial_dispatcher.SerialDispatcher,
        handle: ctypes.c_void_p,
        dispatcher: _AsyncResultDispatcher,
        async_callback: _C_TYPES_RESULT_CALLBACK
    )

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| ## Args ||
|---|---|
| `lib` | The dispatch library to use for the face landmarker. |
| `handle` | The C pointer to the face landmarker. |
| `dispatcher` | The async result handler for the face landmarker. |
| `async_callback` | The c callback for the face landmarker. |

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## Methods

### `close`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3332-L3339)

    close()

Closes the FaceLandmarker.

### `create_from_model_path`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3111-L3134)

    @classmethod
    create_from_model_path(
        model_path: str
    ) -> 'FaceLandmarker'

Creates an `FaceLandmarker` object from a TensorFlow Lite model and the default `FaceLandmarkerOptions`.

Note that the created `FaceLandmarker` instance is in image mode, for
detecting face landmarks on single image inputs.

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

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

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| Raises ||
|---|---|
| `ValueError` | If failed to create `FaceLandmarker` object from the provided file such as invalid file path. |
| `RuntimeError` | If other types of error occurred. |

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### `create_from_options`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3136-L3191)

    @classmethod
    create_from_options(
        options: https://developers.google.com/edge/api/mediapipe/python/mp/tasks/vision/FaceLandmarkerOptions
    ) -> 'FaceLandmarker'

Creates the `FaceLandmarker` object from face landmarker options.

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| Args ||
|---|---|
| `options` | Options for the face landmarker task. |

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

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| Raises ||
|---|---|
| `ValueError` | If failed to create `FaceLandmarker` object from `FaceLandmarkerOptions` such as missing the model. |
| `RuntimeError` | If other types of error occurred. |

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### `detect`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3193-L3232)

    detect(
        image: https://developers.google.com/edge/api/mediapipe/python/mp/Image,
        image_processing_options: Optional[https://developers.google.com/edge/api/mediapipe/python/mp/tasks/vision/ImageProcessingOptions] = None
    ) -> https://developers.google.com/edge/api/mediapipe/python/mp/tasks/vision/FaceLandmarkerResult

Performs face landmark detection on the provided MediaPipe Image.

Only use this method when the FaceLandmarker is created with the image
running mode.

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| Args ||
|---|---|
| `image` | MediaPipe Image. |
| `image_processing_options` | Options for image processing. |

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| Returns ||
|---|---|
| A face landmarker result object that contains a list of face landmarks. ||

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| Raises ||
|---|---|
| `ValueError` | If any of the input arguments is invalid. |
| `RuntimeError` | If face landmark detection failed to run. |

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### `detect_async`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3282-L3330)

    detect_async(
        image: https://developers.google.com/edge/api/mediapipe/python/mp/Image,
        timestamp_ms: int,
        image_processing_options: Optional[https://developers.google.com/edge/api/mediapipe/python/mp/tasks/vision/ImageProcessingOptions] = None
    ) -> None

Sends live image data to perform face landmarks detection.

The results will be available via the "result_callback" provided in the
FaceLandmarkerOptions. Only use this method when the FaceLandmarker is
created with the live stream running mode.

Only use this method when the FaceLandmarker is created with the live
stream running mode. The input timestamps should be monotonically increasing
for adjacent calls of this method. This method will return immediately after
the input image is accepted. The results will be available via the
`result_callback` provided in the `FaceLandmarkerOptions`. The
`detect_async` method is designed to process live stream data such as
camera input. To lower the overall latency, face landmarker may drop the
input images if needed. In other words, it's not guaranteed to have output
per input image.

The `result_callback` provides:
- The face landmarks detection results.
- The input image that the face landmarker runs on.
- The input timestamp in milliseconds.

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| Args ||
|---|---|
| `image` | MediaPipe Image. |
| `timestamp_ms` | The timestamp of the input image in milliseconds. |
| `image_processing_options` | Options for image processing. |

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| Raises ||
|---|---|
| `ValueError` | If the current input timestamp is smaller than what the face landmarker has already processed. |
| `RuntimeError` | If the face landmark detection failed to run. |

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### `detect_for_video`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3234-L3280)

    detect_for_video(
        image: https://developers.google.com/edge/api/mediapipe/python/mp/Image,
        timestamp_ms: int,
        image_processing_options: Optional[https://developers.google.com/edge/api/mediapipe/python/mp/tasks/vision/ImageProcessingOptions] = None
    ) -> https://developers.google.com/edge/api/mediapipe/python/mp/tasks/vision/FaceLandmarkerResult

Performs face landmarks detection on the provided video frame.

Only use this method when the FaceLandmarker is created with the video
running mode.

Only use this method when the FaceLandmarker is created with the video
running mode. It's required to provide the video frame's timestamp (in
milliseconds) along with the video frame. The input timestamps should be
monotonically increasing for adjacent calls of this method.

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| Args ||
|---|---|
| `image` | MediaPipe Image. |
| `timestamp_ms` | The timestamp of the input video frame in milliseconds. |
| `image_processing_options` | Options for image processing. |

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| Returns ||
|---|---|
| The face landmarks detection results. ||

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| Raises ||
|---|---|
| `ValueError` | If any of the input arguments is invalid. |
| `RuntimeError` | If face landmarker detection failed to run. |

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### `__enter__`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3341-L3343)

    __enter__()

Returns `self` upon entering the runtime context.

### `__exit__`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/face_landmarker.py#L3345-L3358)

    __exit__(
        exc_type, exc_value, traceback
    )

Shuts down the MediaPipe task instance on exit of the context manager.

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| Args ||
|---|---|
| `exc_type` | The exception type that caused the context manager to exit. |
| `exc_value` | The exception value that caused the context manager to exit. |
| `traceback` | The exception traceback that caused the context manager to exit. |

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| Raises ||
|---|---|
| `RuntimeError` | If the MediaPipe FaceDetector task failed to close. |

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