<br />

|---|
| [![](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/holistic_landmarker.py#L436-L706) |

Class that performs holistic landmarks detection on images.

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

<br />

<br />

<br />

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

<br />

## Methods

### `close`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/holistic_landmarker.py#L687-L694)

```python
close()
```

Closes the HolisticLandmarker.

### `create_from_model_path`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/holistic_landmarker.py#L464-L487)

```python
@classmethod
create_from_model_path(
    model_path: str
) -> 'HolisticLandmarker'
```

Creates an `HolisticLandmarker` object from a TensorFlow Lite model and the default `HolisticLandmarkerOptions`.

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

<br />

<br />

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

<br />

<br />

<br />

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

<br />

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

<br />

### `create_from_options`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/holistic_landmarker.py#L489-L545)

```python
@classmethod
create_from_options(
    options: `mp.tasks.vision.HolisticLandmarkerOptions`
) -> 'HolisticLandmarker'
```

Creates the `HolisticLandmarker` object from holistic landmarker options.

<br />

<br />

<br />

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

<br />

<br />

<br />

<br />

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

<br />

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<br />

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

<br />

### `detect`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/holistic_landmarker.py#L547-L587)

```python
detect(
    image: `mp.Image`,
    image_processing_options: Optional[`mp.tasks.vision.ImageProcessingOptions`] = None
) -> `mp.tasks.vision.HolisticLandmarkerResult`
```

Performs holistic landmarks detection on the given image.

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

The image can be of any size with format RGB or RGBA.

<br />

<br />

<br />

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

<br />

<br />

<br />

<br />

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

<br />

<br />

<br />

<br />

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

<br />

### `detect_async`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/holistic_landmarker.py#L637-L685)

```python
detect_async(
    image: `mp.Image`,
    timestamp_ms: int,
    image_processing_options: Optional[`mp.tasks.vision.ImageProcessingOptions`] = None
) -> None
```

Sends live image data to perform holistic landmarks detection.

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

Only use this method when the HolisticLandmarker 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 `HolisticLandmarkerOptions`. The
`detect_async` method is designed to process live stream data such as
camera input. To lower the overall latency, holistic 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 holistic landmarks detection results.
- The input image that the holistic landmarker runs on.
- The input timestamp in milliseconds.

<br />

<br />

<br />

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

<br />

<br />

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| Raises ||
|---|---|
| `ValueError` | If the current input timestamp is smaller than what the holistic landmarker has already processed. |

<br />

### `detect_for_video`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/holistic_landmarker.py#L589-L635)

```python
detect_for_video(
    image: `mp.Image`,
    timestamp_ms: int,
    image_processing_options: Optional[`mp.tasks.vision.ImageProcessingOptions`] = None
) -> `mp.tasks.vision.HolisticLandmarkerResult`
```

Performs holistic landmarks detection on the provided video frame.

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

Only use this method when the HolisticLandmarker 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.

<br />

<br />

<br />

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

<br />

<br />

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<br />

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

<br />

<br />

<br />

<br />

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

<br />

### `__enter__`

[View source](https://github.com/google-ai-edge/mediapipe/blob/master/mediapipe/tasks/python/vision/holistic_landmarker.py#L696-L698)

```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/holistic_landmarker.py#L700-L703)

```python
__exit__(
    exc_type, exc_value, traceback
)
```

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