This Yocto/OpenEmbedded machine-learning meta-layer provides support for machine learning libraries:
The TensorFlow Lite (https://www.tensorflow.org/mobile/tflite/) recipe for the FullMetalUpdate project and is an evolution of the layer developped for the RZ/G1 family of System on Chips: https://github.com/renesas-rz/meta-renesas-ai
In order to add TensorFlow Lite support to your project, make sure tensorflow-lite is listed as a dependency to your recipe/package. Listing tensorflow-lite-staticdev and tensorflow-lite-dev in IMAGE_INSTALL variable could be beneficial when you just want to populate an SDK for developing an application based on TensorFlow Lite.
After the build is complete the static C++ TensorFlow Lite library (libtensorflow-lite.a) will be generated.
The library can be verified with the TensorFlow Lite image classification sample application named label_image which is included in the build (included by package tensorflow-lite-examples). The sample application is installed under /usr/bin/tensorflow-lite/examples/.