Overview Before you begin Run Ubuntu Linux on the HiKey 960 Build an Ubuntu filesystem Flash the base firmware and OS Flash the base firmware and OS - recovery mode Flash the base firmware and OS - fastboot mode Boot Linux Add more diskspace MNIST Draw MNIST Draw - Setup MNIST Draw - Machine Learning model MNIST Draw - MNIST demo application Streamline Streamline - Run the MNIST inference Streamline - Use Streamline to connect and profile the application Streamline - Automate the launch and capture Next steps
MNIST Draw - Machine Learning model
Machine Learning model
For more information about how the web application translates the digit drawn into an image file processed by Arm NN, refer to the python script at cgi-bin/mnist.py.
A convolutional neural network (CNN) is defined within the model/ directory, and is used by the program in armnn-draw/ which incorporates the Arm NN SDK. This model is configured for MNIST data inputs. The default model is optimized_mnist_tf.pb.
Using this model, let’s try something that includes more than one image. In this example application, we will use a larger set of MNIST images, and show inference on both the CPUs and the GPU.