This repo explains the intimitading TensorFlow repo and demonstrates TFLite on raptor by making it blinking.

After cloning this repo and cd to it, run the following command:

make -f tensorflow/lite/micro/tools/make/Makefile TARGET=raptor hello_world_bin

Parameters:

• -f tensorflow/lite/micro/tools/make/Makefile: the path to the Makefile.
• TARGET: the target MCU, in this case raptor
• hello_world_bin: the project name (hello_world) + the build type, and in this case we want the binary (bin)

The Tensorflow repo might seem intimitading when you are just starting to experiment with it. Therefore, I created this repo which is a simpler version of if while maintaining the original structure.

When writing TFLite project for MCUs, it is essential that you understand the following directories in TF:

1. Start with the Hello World example and modify it as you want to make it fit your application purpose. It is found in the following path tensorflow/lite/micro/examples/hello_world
2. If you have (and most probably you will) platform specific implementations (such as ADC data collection, DAC, UART, etc.) needed in the application, place these implementations in a subdirectory with the platform name inside the hello_world folder.
   example: hello_world/raptor/ contains the raptor version of output_handler.cc
   
3. Provide your platform's implementation of the tensorflow/lite/micro/<platform_name>/debug_log.cc, here <platform_name> is raptor. This file provides a way to output debug information (for example using the UART).
4. Write a Makefile for your platform and put it in: tensorflow/lite/micro/tools/make/targets/<platform_name>_makefile.inc For example, you will find raptor's Makefile in tensorflow/lite/micro/tools/make/targets/raptor_makefile.inc
5. Finally, build using the command:

make -f tensorflow/lite/micro/tools/make/Makefile TARGET=<platform_name> hello_world_bin