Live classifications with a smartphone
When discussing model testing, we usually refer to evaluating the trained model on the test dataset. However, model testing in Edge Impulse is more than that.
In this recipe, we will learn how to test model performance on the test dataset and show a way to perform live classifications with a smartphone.
Getting ready
In Edge Impulse, there are two ways to evaluate the accuracy of a model:
- Model testing on the test dataset: We assess the accuracy using the test dataset. The test dataset provides an unbiased evaluation of model effectiveness because the samples are not used directly or indirectly during training.
- Live classification: This is a unique feature of Edge Impulse whereby we can record new samples from a smartphone or a supported device (for example, the Arduino Nano).
The live classification approach benefits from testing the trained model in the real world before deploying...
