Mediapipe

* Released [experimental new framework APIs](https://github.com/google/mediapipe/tree/master/mediapipe/framework/api2/README.md)
* Updated [MediaPipe Objectron](https://solutions.mediapipe.dev/objectron) to support simultaneous detection of multiple objects
* Bug fixes
* Fixed a crash in the [MediaPipe Iris](https://solutions.mediapipe.dev/iris) iOS example app
* Fixed memory leak in Android example apps (in [ExternalTextureConverter](https://github.com/google/mediapipe/blob/master/mediapipe/java/com/google/mediapipe/components/ExternalTextureConverter.java))
* Fixed a file read mode issue in [pose_landmark_model_loader.pbtxt](https://github.com/google/mediapipe/blob/master/mediapipe/modules/pose_landmark/pose_landmark_model_loader.pbtxt#L51).

* [MediaPipe Holistic](https://solutions.mediapipe.dev/holistic) for real-time simultaneous tracking of human pose, face and hand landmarks
* [Google AI blog post](https://mediapipe.page.link/holistic_ai_blog_post)
* [MediaPipe in Python](https://docs.mediapipe.dev/getting_started/python)
* Ready-to-use Python Solution APIs for MediaPipe Face Mesh, Hands, Pose and Holistic
* Try it in [MediaPipe on Google Colab](https://docs.mediapipe.dev/getting_started/python#mediapipe-on-google-colab)
* [MediaPipe in JavaScript](https://docs.mediapipe.dev/getting_started/javascript)
* Ready-to-use JavaScript Solution APIs for MediaPipe Face Mesh, Hands, Pose and Holistic
* Try it in [MediaPipe on CodePen](https://code.mediapipe.dev/codepen)
* Switch [build](https://github.com/google/mediapipe/blob/master/.bazelrc) from C++14 to C++17

* [MediaPipe in Python](https://google.github.io/mediapipe/#mediapipe-in-python)
* Released Python Solution API for [MediaPipe Face Mesh](https://solutions.mediapipe.dev/face_mesh#python) and [MediaPipe Hands](https://solutions.mediapipe.dev/hands#python)
* Updated Python Solution API for [MediaPipe Pose](https://solutions.mediapipe.dev/pose#python)
* Also released usage examples as [Google Colabs](https://google.github.io/mediapipe/#mediapipe-in-python)
* [MediaPipe Objectron](https://solutions.mediapipe.dev/objectron)
* Released a faster two-stage pipeline
* Added support for more object classes: shoe, chair, cup and camera
* Released [training dataset](https://github.com/google-research-datasets/Objectron/), (to be) announced in a [Google AI Blog post](https://mediapipe.page.link/objectron_dataset_ai_blog)
* New [Tensor](https://github.com/google/mediapipe/blob/master/mediapipe/framework/formats/tensor.h) class
* Released as a multi-dimensional tensor data container, supporting multiple backends like CPU, Metal buffer, GL buffer and GL texture 2D
* Added new Tensor-based pre-processing, inference and post-processing calculators in [mediapipe/calculators/tensor](https://github.com/google/mediapipe/tree/master/mediapipe/calculators/tensor), branched from existing calculators in [mediapipe/calculators/tflite](https://github.com/google/mediapipe/tree/master/mediapipe/calculators/tflite)
* Most of the (sub-)graph in [mediapipe/modules](https://github.com/google/mediapipe/tree/master/mediapipe/modules) have been updated to use Tensor and the associated calculators. The plan is to fully migrate all in the repo (and deprecate [mediapipe/calculators/tflite](https://github.com/google/mediapipe/tree/master/mediapipe/calculators/tflite) by end of 2020.
* [MediaPipe Hands](https://solutions.mediapipe.dev/hands)
* Refactored [graphs](https://github.com/google/mediapipe/tree/master/mediapipe/graphs/hand_tracking) to depend on the new [palm_detection](https://github.com/google/mediapipe/tree/master/mediapipe/modules/palm_detection) and [hand_landmark module](https://github.com/google/mediapipe/tree/master/mediapipe/modules/hand_landmark).
* Improved model speed for both palm detection and hand landmark.
* Extended the main hand tracking [example apps](http://solutions.mediapipe.dev/hands#example-apps) to support multiple hands, to replace the separate multi-hand tracking examples.
* [MediaPipe Face Detection](https://solutions.mediapipe.dev/face_detection)
* Refactored [graphs](https://github.com/google/mediapipe/tree/master/mediapipe/graphs/face_detection) to depend on the [face_detection module](https://github.com/google/mediapipe/tree/master/mediapipe/modules/face_detection).

* Added 3D Face Transform to [MediaPipe Face Mesh](https://solutions.mediapipe.dev/face_mesh)
* Enables [Face Effect Rendering](https://solutions.mediapipe.dev/face_mesh#effect-renderer)
* Demonstrated with an [Face Effect Example App](https://solutions.mediapipe.dev/face_mesh#face-effect-example)
* More info in [Google Developers Blog post](https://mediapipe.page.link/face-geometry-blog)
* Added [MediaPipe Models and Model Cards](https://solutions.mediapipe.dev/models) doc

* [MediaPipe Instant Motion Tracking](https://solutions.mediapipe.dev/instant_motion_tracking) that performs AR tracking without initialization or calibration.
* [Google Developers Blog post](https://mediapipe.page.link/instant-motion-tracking-blog)
* [MediaPipe BlazePose in Python](https://solutions.mediapipe.dev/pose#python) now uses `pip install mediapipe` instead of building from source. Also published a [Colab](https://mediapipe.page.link/mp-py-colab) example.
* [MediaPipe Iris](https://solutions.mediapipe.dev/iris) updated to output a set of 478 3D landmarks, including 468 face landmarks from [MediaPipe Face Mesh](https://solutions.mediapipe.dev/face_mesh), with those around the eyes further refined, and 10 additional iris landmarks appended at the end.

* [MediaPipe Pose](https://solutions.mediapipe.dev/pose) for upper-body pose tracking
* [Google AI blog post for full and upper body Blazepose](https://mediapipe.page.link/blazepose-blog)
* Preview of [Python support](https://google.github.io/mediapipe/getting_started/building_examples.html#python) that runs MediaPipe Pose in Python interpreter