1# TensorFlow Lite Micro Mbed Project 2 3This folder has been autogenerated by TensorFlow, and contains source, header, 4and project files needed to build a single TensorFlow Lite Micro target using 5the Mbed command line interface. 6 7## Usage 8 9To load the dependencies this code requires, run: 10 11``` 12mbed config root . 13mbed deploy 14``` 15 16TensorFlow requires C++ 11, so you'll need to update your profiles to reflect 17this. Here's a short Python command that does that: 18 19``` 20python -c 'import fileinput, glob; 21for filename in glob.glob("mbed-os/tools/profiles/*.json"): 22 for line in fileinput.input(filename, inplace=True): 23 print line.replace("\"-std=gnu++98\"","\"-std=c++11\", \"-fpermissive\"")' 24``` 25 26With that setting updated, you should now be able to compile: 27 28``` 29mbed compile -m auto -t GCC_ARM 30``` 31 32If this works, it will give you a .bin file that you can flash onto the device 33you're targeting. For example, using a Discovery STM3246G board, you can deploy 34it by copying the bin to the volume mounted as a USB drive, just by dragging 35over the file. 36 37## Project Generation 38 39See 40[tensorflow/lite/micro](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro) 41for details on how projects like this can be generated from the main source 42tree. 43 44## License 45 46TensorFlow's code is covered by the Apache2 License included in the repository, 47and third party dependencies are covered by their respective licenses, in the 48third_party folder of this package. 49