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Welcome
DEEPCRAFT Studio
Release notes
Download and Install DEEPCRAFT Studio
Getting started
Machine learning Algorithms in DEEPCRAFT Studio
DEEPCRAFT Studio Accelerators and Project Templates
DEEPCRAFT Studio Accelerators
Project Templates
Graph UX
Graph UX Overview
Dataset Node
Infineon Development Kits
PSOC Edge E84 HMI Kit
PSOC Edge E84 AI Kit
PSOC Edge E84 Evaluation Kit
PSOC 6 AI Evaluation Kit
PSOC 6 Wi-Fi BT Pioneer Kit
PSOC 4100S Max Pioneer Kit
Other Infineon Development Kits
Other Development Boards
Streaming Protocol for Real-Time Data Collection
Registering sensors and boards for data streaming using Protocol version 2
Registering sensors and boards for data streaming using Protocol version 1
Flashing your custom firmware using ModusToolbox
Advanced Functionality
Studio Project File
Data Tab
Data Preparation
Real-time Data Collection
Real-time Data Collection using Infineon Boards
PSOC Edge HMI Kit
Collect and label data using microphone sensor
Collect and label data using IMU sensor
Collect and label data using Humidity and Temperature Sensor
Collect and label data using using Radar sensor
PSOC Edge E84 Artificial Intelligence Kit
Collect and label data using microphone sensor
Collect and label data using IMU sensor
Collect and label data using Magnetometer sensor
Collect and label data using Pressure and Temperature Sensor
Collect and label data using Humidity and Temperature Sensor
Collect and label data using using Radar sensor
Collect and label data using multiple sensors
PSOC Edge E84 Evaluation Kit
Collecting and labeling data using microphone sensor
Collecting and labeling data using IMU sensor
Collecting and labeling data using Magnetometer sensor
Collecting and Labeling data using multiple sensors
PSOC 6 AI Evaluation Kit
Collecting and labeling data using microphone sensor
Collecting and labeling data using IMU sensor
Collecting and labeling data using Magnetometer sensor
Collecting and labeling data using Pressure Sensor
Collecting and labeling data using using Radar sensor
Collecting and Labeling data using multiple sensors
Data Collection with PSOC 6 AI Evaluation Kit using old streaming firmware/ Protocol version 1
Data Collection with PSOC 6 Wi-Fi BT Pioneer Kit using old streaming firmware/ Protocol version 1
Real-time Data Collection without using a kit
Image data collection and labeling using camera
Audio data collection and labeling using PC/laptop Microphone
Data Collection using Dataset
Collect and label data using any development boards
Bring your own data
Bring your own data for classification and regression projects
Bring your own data for object detection projects
Adding data to classification and regression projects
Adding data to object detection projects
Exporting data to a training project
Data Labeling
Manual Labeling
ML Assisted Labeling
Sequential Labeling
Labeling Images
Data Labeling using Dataset
Data Distribution
Advanced Functionality
Data Augmentation
Managing labels
Creating multiple label tracks
Preprocessing
Model Training
Generating model
Starting and Tracking Training Job
Downloading model files and Importing model predictions
Training Object Detection Model
Local Model Training
Model Evaluation
Evaluate classification model
Model evaluation using Confusion Matrix
Model explainability using Window Visualization and Grad-CAM
Evaluating model using Graph UX
Evaluate regression model
Evaluating Object Detection Model
Code Generation
Code Generation for Infineon PSOC 6 and PSOC Edge boards
Code Generation for Vision Models
Code Generation for Infineon AURIX, Traveo, XMC7200 and Other Development Boards
Code Generation using Graph UX
Model Deployment
Edge API
Model Deployment on Supported Infineon Boards
Deploy siren detection model on AURIX TC375 Lite Kit
Deploy model on PSOC 6 and PSOC Edge boards
Deploy vision model on PSOC Edge boards
Deploy siren detection model on TRAVEO T2G (KIT_T2G-B-E_LITE)
Deploy siren detection model on TRAVEO T2G (KIT_T2G-B-H_LITE)
Deploy siren detection model on XMC7200 Evaluation Kit
Model Deployment on Other Development Boards
Supported layers and functions
Creating custom layers or functions
Tutorials
Building Siren Detection machine learning model
Data Preparation
Preprocessing
Model Training
Code Generation and Model Deployment
Predicting Power Generation from Wind Turbine
Building Capacitive Sensing machine learning models
Data Preparation
Preprocessing
Model Training
Code Generation
Deploy the CapSense Demo Project on the Kit
Training Manual
Troubleshooting
Installer Issues
Other Issues
Frequently Asked Questions
DEEPCRAFT Model Converter
Release Notes 6.1
Release Notes 6.0
Release Notes 5.11
Release Notes 5.10
Release Notes 5.9
Release Notes 5.8
Install and Launch
Graphical User Interface
Command Line Interface
Model Validation
Model Viewer
Deploy Code on PSOC Edge using the Code Example
Additional Resources: Setup, Compatibility, Formats
Supported Models and Quantization
Setup and Run the PyTorch to TFLite Converter API with Docker or Podman
Supported Data Formats
Supported Layers and Operators
Streaming RNN model validation
Deployment API
Deployment Runtimes
Training Manual
Troubleshooting
Degraded LSTM Model Performance
Insufficient model arena memory during deployment
DEEPCRAFT Ready Models
Getting started
Customize Ready Model
Code generation
Ready Models
Field Testing
Plan your test
Run the tests
Audio models
Radar models
Reports
Baby Cry Detection
Cough Detection
Snore Detection
Siren Detection
Gesture Classification
Legal
Imagimob AI Model Evaluation License Agreement
DEEPCRAFT Studio Terms and Conditions
DEEPCRAFT Studio Licensing Metrics and Fees
DEEPCRAFT Model Converter Agreement
Privacy Policy for DEEPCRAFT Studio and connected services
Free Open Source Software (FOSS)
Ultralytics YOLO License Information
Home
Community
Contact Sales
Sign Up
Welcome
DEEPCRAFT Studio
Release notes
Download and Install DEEPCRAFT Studio
Getting started
Machine learning Algorithms in DEEPCRAFT Studio
DEEPCRAFT Studio Accelerators and Project Templates
DEEPCRAFT Studio Accelerators
Project Templates
Graph UX
Graph UX Overview
Dataset Node
Infineon Development Kits
PSOC Edge E84 HMI Kit
PSOC Edge E84 AI Kit
PSOC Edge E84 Evaluation Kit
PSOC 6 AI Evaluation Kit
PSOC 6 Wi-Fi BT Pioneer Kit
PSOC 4100S Max Pioneer Kit
Other Infineon Development Kits
Other Development Boards
Streaming Protocol for Real-Time Data Collection
Registering sensors and boards for data streaming using Protocol version 2
Registering sensors and boards for data streaming using Protocol version 1
Flashing your custom firmware using ModusToolbox
Advanced Functionality
Studio Project File
Data Tab
Data Preparation
Real-time Data Collection
Real-time Data Collection using Infineon Boards
PSOC Edge HMI Kit
Collect and label data using microphone sensor
Collect and label data using IMU sensor
Collect and label data using Humidity and Temperature Sensor
Collect and label data using using Radar sensor
PSOC Edge E84 Artificial Intelligence Kit
Collect and label data using microphone sensor
Collect and label data using IMU sensor
Collect and label data using Magnetometer sensor
Collect and label data using Pressure and Temperature Sensor
Collect and label data using Humidity and Temperature Sensor
Collect and label data using using Radar sensor
Collect and label data using multiple sensors
PSOC Edge E84 Evaluation Kit
Collecting and labeling data using microphone sensor
Collecting and labeling data using IMU sensor
Collecting and labeling data using Magnetometer sensor
Collecting and Labeling data using multiple sensors
PSOC 6 AI Evaluation Kit
Collecting and labeling data using microphone sensor
Collecting and labeling data using IMU sensor
Collecting and labeling data using Magnetometer sensor
Collecting and labeling data using Pressure Sensor
Collecting and labeling data using using Radar sensor
Collecting and Labeling data using multiple sensors
Data Collection with PSOC 6 AI Evaluation Kit using old streaming firmware/ Protocol version 1
Data Collection with PSOC 6 Wi-Fi BT Pioneer Kit using old streaming firmware/ Protocol version 1
Real-time Data Collection without using a kit
Image data collection and labeling using camera
Audio data collection and labeling using PC/laptop Microphone
Data Collection using Dataset
Collect and label data using any development boards
Bring your own data
Bring your own data for classification and regression projects
Bring your own data for object detection projects
Adding data to classification and regression projects
Adding data to object detection projects
Exporting data to a training project
Data Labeling
Manual Labeling
ML Assisted Labeling
Sequential Labeling
Labeling Images
Data Labeling using Dataset
Data Distribution
Advanced Functionality
Data Augmentation
Managing labels
Creating multiple label tracks
Preprocessing
Model Training
Generating model
Starting and Tracking Training Job
Downloading model files and Importing model predictions
Training Object Detection Model
Local Model Training
Model Evaluation
Evaluate classification model
Model evaluation using Confusion Matrix
Model explainability using Window Visualization and Grad-CAM
Evaluating model using Graph UX
Evaluate regression model
Evaluating Object Detection Model
Code Generation
Code Generation for Infineon PSOC 6 and PSOC Edge boards
Code Generation for Vision Models
Code Generation for Infineon AURIX, Traveo, XMC7200 and Other Development Boards
Code Generation using Graph UX
Model Deployment
Edge API
Model Deployment on Supported Infineon Boards
Deploy siren detection model on AURIX TC375 Lite Kit
Deploy model on PSOC 6 and PSOC Edge boards
Deploy vision model on PSOC Edge boards
Deploy siren detection model on TRAVEO T2G (KIT_T2G-B-E_LITE)
Deploy siren detection model on TRAVEO T2G (KIT_T2G-B-H_LITE)
Deploy siren detection model on XMC7200 Evaluation Kit
Model Deployment on Other Development Boards
Supported layers and functions
Creating custom layers or functions
Tutorials
Building Siren Detection machine learning model
Data Preparation
Preprocessing
Model Training
Code Generation and Model Deployment
Predicting Power Generation from Wind Turbine
Building Capacitive Sensing machine learning models
Data Preparation
Preprocessing
Model Training
Code Generation
Deploy the CapSense Demo Project on the Kit
Training Manual
Troubleshooting
Installer Issues
Other Issues
Frequently Asked Questions
DEEPCRAFT Model Converter
Release Notes 6.1
Release Notes 6.0
Release Notes 5.11
Release Notes 5.10
Release Notes 5.9
Release Notes 5.8
Install and Launch
Graphical User Interface
Command Line Interface
Model Validation
Model Viewer
Deploy Code on PSOC Edge using the Code Example
Additional Resources: Setup, Compatibility, Formats
Supported Models and Quantization
Setup and Run the PyTorch to TFLite Converter API with Docker or Podman
Supported Data Formats
Supported Layers and Operators
Streaming RNN model validation
Deployment API
Deployment Runtimes
Training Manual
Troubleshooting
Degraded LSTM Model Performance
Insufficient model arena memory during deployment
DEEPCRAFT Ready Models
Getting started
Customize Ready Model
Code generation
Ready Models
Field Testing
Plan your test
Run the tests
Audio models
Radar models
Reports
Baby Cry Detection
Cough Detection
Snore Detection
Siren Detection
Gesture Classification
Legal
Imagimob AI Model Evaluation License Agreement
DEEPCRAFT Studio Terms and Conditions
DEEPCRAFT Studio Licensing Metrics and Fees
DEEPCRAFT Model Converter Agreement
Privacy Policy for DEEPCRAFT Studio and connected services
Free Open Source Software (FOSS)
Ultralytics YOLO License Information
Questions? Ask the experts in the DEEPCRAFT forum!
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Welcome to DEEPCRAFT Documentation
Everything you need to build intelligent and low-power Edge AI.
DEEPCRAFT Studio
Build your own model
Build, train, and deploy Edge AI models
End-to-end ML:
from data collection to on-device deployment
Graph-based UX:
visual, node-based workflow for unique insight into ML development process
Build custom models:
develop Edge AI with any time series or image data for any MCU
Read more
DEEPCRAFT Model Converter
Bring your own model (BYOM)
Convert, optimize and validate AI models to run on Infineon MCUs
Convert:
supports many different AI model file formats
Optimize:
deploy with ease onto Infineon hardware
Validate:
verify performance before deployment
Read more
DEEPCRAFT Ready Models
Buy a production-ready model
Take Edge AI to market fast with fully trained and tested models
No ML skills required:
complete, validated models built by expert engineers
Edge-optimized:
low power, small memory footprint, fast inference
Test, buy, deploy:
test for free, purchase for royalty per device, deploy on your device
Read more
DEEPCRAFT Studio Accelerators
Kickstart model development
Shorten development time with pre-trained projects you can fine-tune for your use case
Download and customize:
access in DEEPCRAFT Studio and adapt to your needs
Develop production-ready models:
come with datasets, preprocessing, model architectures and instructions
Learn by doing:
hands-on, end-to-end workflow from data to deployment
Read more
2026
Imagimob
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