Mediapipe

[MediaPipe Android Solutions](https://google.github.io/mediapipe/getting_started/android_solutions.html)
- MediaPipe Hands, Face Detection, and Face Mesh Android Solutions are now available in [Google's Maven Repository](https://maven.google.com/web/index.html?#com.google.mediapipe).
- The Android Studio example project is available in [mediapipe/examples/android/solutions](https://github.com/google/mediapipe/tree/master/mediapipe/examples/android/solutions).

[MediaPipe Hands](https://google.github.io/mediapipe/solutions/hands.html)
- MediaPipe Hands models are updated.
- MediaPipe Hands now supports outputting [world landmarks](https://google.github.io/mediapipe/solutions/hands.html#multi_hand_world_landmarks) in world coordinates.

MediaPipe Dependencies

- MediaPipe [Python wheels](https://pypi.org/project/mediapipe/0.8.9.1/) are now supporting Python 3.10.
- The MediaPipe dependency library protobuf, tensorflow, cere solver, pybind, and apple support are updated.
- The recommended Bazel version is updated to 4.2.1.
- The recommended Android SDK and NDK versions are updated.

* [MediaPipe Face Mesh](https://solutions.mediapipe.dev/face_mesh)
* Added an [`refine_landmarks`](https://google.github.io/mediapipe/solutions/face_mesh#refine_landmarks) option in the Solution APIs to further improve landmarks around eyes and lips, and output additional landmarks around the irises.
* Released the [Attention Mesh ML model](https://google.github.io/mediapipe/solutions/face_mesh.html#attention-mesh-model) that enables `refine_landmarks`.
* [MediaPipe Holistic](https://solutions.mediapipe.dev/holistic)
* Added the [`enable_segmentation`](https://google.github.io/mediapipe/solutions/holistic#enable_segmentation) and [`smooth_segmentation`](https://google.github.io/mediapipe/solutions/holistic#smooth_segmentation) option in the Solution APIs, previously only available in [MediaPipe Pose](https://solutions.mediapipe.dev/pose).

Merged https://github.com/google/mediapipe/pull/1969, https://github.com/google/mediapipe/pull/2039, https://github.com/google/mediapipe/pull/2101, https://github.com/google/mediapipe/pull/2136, https://github.com/google/mediapipe/pull/2154, https://github.com/google/mediapipe/pull/2201, https://github.com/google/mediapipe/pull/2291, https://github.com/google/mediapipe/pull/2292, https://github.com/google/mediapipe/pull/2347, https://github.com/google/mediapipe/pull/2350, https://github.com/google/mediapipe/pull/2450, https://github.com/google/mediapipe/pull/2462, and https://github.com/google/mediapipe/pull/2464.

A huge thank you to all contributors:
Abduttayyeb
brettkoonce
chr0nikler 
daniel13520cs
gabrielsanchez
GantMan
GzuPark 
homuler
magamig
PeterPocsi
TomHsiao1260 
yuripourre

- MediaPipe Pose now outputs "segmentation_mask" when [`enable_segmentation`](https://google.github.io/mediapipe/solutions/pose.html#enable_segmentation) is set.
- MediaPipe Python [FaceMesh](https://google.github.io/mediapipe/solutions/face_mesh.html#python-solution-api), [Hands](https://google.github.io/mediapipe/solutions/hands.html#python-solution-api), [Pose](https://google.github.io/mediapipe/solutions/pose.html#python-solution-api), and [Holistic](https://google.github.io/mediapipe/solutions/holistic.html#python-solution-api) have new drawing styles. Please refer to the documentation and the Colab examples for more details.
- MediaPipe now offers Android [FaceMesh](https://google.github.io/mediapipe/solutions/face_mesh.html#android-solution-api) and [Hands](https://google.github.io/mediapipe/solutions/hands.html#android-solution-api) solution APIs (currently in Alpha). The maven artifacts are available in [Google's Maven Repository](https://maven.google.com/web/index.html?#com.google.mediapipe). To try the example apps, please import [the solution example Android Studio project](https://github.com/google/mediapipe/tree/master/mediapipe/examples/android/solutions) on either Linux, macOS, and Windows.

* MediaPipe Pose (and Holistic) now also outputs estimated real-world 3D coordinates of pose landmarks (in meters with the origin at center of hips)
* MediaPipe Face Detection now supports a "model_selection" option to switch between short-range and full-range models

* Released [MediaPipe Selfie Segmentation](https://solutions.mediapipe.dev/selfie_segmentation)
* JavaScript Solution API w/ a CodePen example
* Python Solution API w/ a Colab example
* Android, iOS and desktop example apps