Navigate to the MNIST Draw code example, shown here:

# Go into the repository
$ cd $HOME/Tool-Solutions/ml-tool-examples/mnist-draw

# Build the armnn-draw application
$ make -C armnn-draw

# Set LD_LIBRARY_PATH for Arm NN (if not already done)
# This is also helpful to put in $HOME/.bashrc for future use
$ export LD_LIBRARY_PATH=$HOME/armnn-devenv/armnn/build

# Start Python server
$ python3 -m http.server --cgi 8000

Then open a browser on any machine which can access the HiKey 960 board, and go to http://ip-address:8000

An example of the website's interface is shown in the following image.

Using the mouse, draw a digit between 0 and 9 on the empty canvas, and then hit the 'Predict' button to process their drawing. Any errors during processing will be indicated with a warning icon and printed to the console. Common errors include not compiling the application in armnn-draw/ and not using python3.

Results are displayed as a bar graph, in which each classification label receives a score between 0.0 and 1.0 from the machine learning model. Clear the canvas with the Clear button to draw and process other digits.

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