Yocto layer for the TensorFlow Lite interpreter with Python.
The official website is:
Reference
Quick start for the Raspberry Pi AArch64 (core-image-weston)
# Clone repositories and oe-init-build-env
$ git clone git://git.yoctoproject.org/poky.git
$ git clone git://git.yoctoproject.org/meta-raspberrypi
$ git clone git://git.openembedded.org/meta-openembedded
$ git clone https://github.com/NobuoTsukamoto/meta-tensorflow-lite.git
$ source poky/oe-init-build-env rpi-build
# Add layer
$ bitbake-layers add-layer ../meta-openembedded/meta-oe/
$ bitbake-layers add-layer ../meta-openembedded/meta-python/
$ bitbake-layers add-layer ../meta-openembedded/meta-networking/
$ bitbake-layers add-layer ../meta-openembedded/meta-multimedia/
$ bitbake-layers add-layer ../meta-raspberrypi/
$ bitbake-layers add-layer ../meta-tensorflow-lite/
# Add the package to 'conf/local.conf' file.
MACHINE ?= "raspberrypi4-64"
IMAGE_INSTALL_append = " python3-tensorflow-lite"
# Build
$ bitbake core-image-weston
- Check only raspberrypi4-64 (aarch64) and raspberrypi4 (armv7l)