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Edge TPU Python API

This repository contains an easy-to-use Python API to work with Coral devices:

You can run inference and do transfer learning.

Build and install from source

  1. Sync the source code as per the Mendel get started guide.

  2. Run cd packages/edgetpu/ to switch current working directory

  3. Run scripts/runtime/install.sh to install Edge TPU runtime

  4. Run scripts/build_swig.sh to build SWIG-based native layer

  5. Run make wheel to generate Python wheel and then pip3 install $(ls dist/*.whl) to install it

Native C++ code

All native code is inside src folder. You can build everything using Makefile. For example, run make tests to build all C++ unit tests or make benchmarks to build all C++ benchmarks. To get the list of all available make targets run make help.

You can cross-compile code for different platforms by setting CPU variable:

make CPU=k8      tests  # Builds for x86_64 (default CPU value)
make CPU=armv7a  tests  # Builds for ARMv7-A, e.g. Pi 3 or Pi 4
make CPU=aarch64 tests  # Builds for ARMv8, e.g. Coral Dev Board

Docker allows to avoid complicated environment setup and run the same Makefile targets:

make DOCKER_IMAGE=debian:buster DOCKER_CPUS="k8 armv7a aarch64" DOCKER_TARGETS=tests docker-build
make DOCKER_IMAGE=ubuntu:18.04  DOCKER_CPUS="k8 armv7a aarch64" DOCKER_TARGETS=tests docker-build

All output goes to out directory.