Example

Description

DEEPCRAFT Deploy Model Radar

This code example demonstrates how to deploy an DEEPCRAFT™ generated machine learning model. It comes pre-configured with a radar based model generated within DEEPCRAFT™ Studio. The code example collects radar data from the XENSIV™ 60 GHz radar sensor which is then sent to the machine learning model to detect specific gestures (push and circle). It uses the model.c/h files generated from within DEEPCRAFT™ Studio directly. New models based on the Gesture Detection project can be dropped into the project as-is. For more details, see the README on GitHub.

DEEPCRAFT Deploy Ready Model

This code example demonstrates how to integrate a ready model library from DEEPCRAFT™ Studio on ModusToolbox™. The code example includes six different models where five model detect differet sounds such as baby-cry detection, cough detection, alarm detection, siren detection, and snoring detection which uses data from the pulse-density modulation (PDM) to pulse-code modulation (PCM) which is sent to the model for detection. The sixth model detects hand gestures which uses data from XENSIV™ radar sensor. For more details, see the README on GitHub.

DEEPCRAFT Streaming Protocol

This ModusToolbox™ firmware project implements the DEEPCRAFT™ streaming protocol v2 for PSOC™ 6 MCU boards, allowing the streaming of sensor data and other information from the board into DEEPCRAFT™ Studio for development and testing of Edge AI models. For more details, see the README on GitHub.

Dual CPU Cyberon

This code example shows how to use the dual CPU architecture of the PSOC™ 6 MCU to implement a keyword spotting and command processing application. For more details, see the README on GitHub.

Machine Learning Gesture Classification

This code example demonstrates how to perform gesture classification based on motion sensor (accelerometer and gyroscope) data. The code example comes with a pre-trained model that classifies the following gestures: circle, square, and side-to-side. For more details, see the README on GitHub.

Machine Learning Neural Network Profiler

This code example demonstrates how to run through the machine learning (ML) development flow with PSOC™ 6 MCU, where the end user has a pre-trained Neural Network (NN) model, which can be profiled and validated at the PC and target device. For more details, see the README on GitHub.