Requirements

1. [Mbed cli] pip install mbed-cli
2. [uTensor cli] pip install utensor-cgen
3. [Treasure Data Client] pip install td-client
4. Install Tensorflow (1.9.0 is used in this project)

Instructions

1. Following the instructions and import Mbed OS and other libraries from this repo

mbed import https://www.github.com/BlackstoneEngineering/mbed-os-example-e2e-demo

Specifically, First, download mbed os and cd mbed-os-example-e2e-demo Second, configure mbed cloud api key

mbed config CLOUD_SDK_API_KEY 

Third, add folder .update-certificates if there isn't one.

mbed dm init -a mbed_cloud_api_key -d "http://os.mbed.com" --model-name "modelname" -q --force

If need to fetch necessary libraries, mbed deploy

2. uTensor is automatically downloaded from step 1 as well. It can also be manually added as following:

mbed add https://github.com/uTensor/uTensor

Or move uTensor.lib to the folder and mbed deploy. To have a better understanding of uTensor, here is a great blog to get started.

3. Use Jupyter Notebooks in folder tensorflow-models to train models in Tensorflow and save models in .pb files.
   

4. Generate embedded C++ code with utensor-cli and save them in folder models

utensor-cli convert ./tensorflow-models/mnist_model_0to9/deep_ml.pb --output-nodes=y_pred

5. Replace main.cpp in mbed-os-example-e2e-demo with main.cpp in this repo.

6. First, compile model that classifies 0 to 4 with Mbed OS

mbed compile --target DISCO_F413ZH --toolchain GCC_ARM --profile=uTensor/build_profile/release.json --flash

Compile successfully!

7. Flash to the board and run it with mbed sterm -b 115200 or in Serial terminal.

8. The DNN model classifies 0 to 4 correctly but the last 5 digits are predicted wrong.

9. Copy and paste deep_mlp files from the folder deep_mlp_0to9 and compile again.

10. Pelion update the firmware with the model

mbed dm update device -D 016a03d5c97d000000000001001002d8 -m DISCO_F413ZH --build ./BUILD/DISCO_F413ZH/GCC_ARM-RELEASE -vv

11. This time, the new model predicts all 10 digits correctly.