• MediaPipe in Python
  • Released Python Solution API for MediaPipe Face Mesh and MediaPipe Hands
  • Updated Python Solution API for MediaPipe Pose
  • Also released usage examples as Google Colabs
• MediaPipe Objectron
  • Released a faster two-stage pipeline
  • Added support for more object classes: shoe, chair, cup and camera
  • Released training dataset, (to be) announced in a Google AI Blog post
• New Tensor 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, branched from existing calculators in mediapipe/calculators/tflite
  • Most of the (sub-)graph in 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 by end of 2020.
• MediaPipe Hands
  • Refactored graphs to depend on the new palm_detection and hand_landmark module.
  • Improved model speed for both palm detection and hand landmark.
  • Extended the main hand tracking example apps to support multiple hands, to replace the separate multi-hand tracking examples.
• MediaPipe Face Detection
  • Refactored graphs to depend on the face_detection module.