Eiq software. 04 as below command: 1. eIQ also includes the software to capture the camera or voice data from external peripherals. Support for eIQ machine learning software from NXP. Solved: I installed the eIQ Toolkit v1. MX Applications Processors). MX RT1060 The eIQ inference with TensorFlow™ Lite for Microcontrollers (TF Micro) is optimized for running machine learning models on resource constrained devices, including NXP's i. Models are included in the form of "recipes" that convert the original models to TensorFlow Lite format. 14 releases users should refer to NXP eIQ™ Machine Learning Software Development Environment for i. MX RT1060 To help ML developers become even more productive and proficient on NXP’s i. MX SoCs, enabling Neural Network acceleration on NXP SoCs on the GPU or NPU through the OpenVX backend. 3K subscribers Subscribed What’s new: NXP Semiconductors today announced it has added two new tools to its eIQ AI and machine learning development software, making it easier to deploy and use AI at the edge across a full sp… The NXP ® eIQ ™ Machine Learning Software Development Environment enables the use of ML algorithms on NXP MCUs, i. eIQ Sample Apps - Overview eIQ Sample Apps - Introduction Get the source code available on code aurora: TensorFlow Lite MobileFaceNets MIPI/USB Camera Face Detectio Hi team, We are trying to create eiq project using own dataset with the help of instruction given in TP-EIQ-BRING-YOUR-OWN-DATA-BYOD document as shown below. 8) version of the tool? Can you describe the exact steps you take from opening the project you shared to getting the error? NXP's eiQ™ machine learning software environment enables customers to convert and optimize trained machine learning models for deployment on NXP silicon. NXP's eiQ™ machine learning software environment enables customers to convert and optimize trained machine learning models for deployment on NXP silicon. What is the eIQ AI Software Stack and how does it support AI development? NXP’s eIQ AI SW Stack enables flexible AI development with support for TensorFlow, PyTorch, ONNX, and BYOM/BYOD workflows. This lab will walk through how to use eIQ Time Series Studio (TSS) to create time series models for embedded microcontrollers. Introducing the eIQ ML software development environment, including eIQ Toolkit and eIQ inference engine support overviews, along with Transfer Learning training lab and examples of handwritten digit recognition using the i. Developed by Google to provide reduced implementations of TensorFlow (TF) models, TF Lite uses many techniques for achieving low latency such as pre-fused activations and quantized kernels that allow smaller and (potentially The NXP eIQ® Model Zoo offers pre-trained models for a variety of domains and tasks that are ready to be deployed on supported products. The NXP® eIQ® artificial intelligence software development environment enables the use of AI algorithms on NXP MCUs, i. 14 (eIQ Toolkit v1. MX93 series. It consists of a 6-layer PCB with through hole design for better EMC performance at a low cost, and it includes key components and interfaces. 4, and so on), see the “NXP eIQ Machine Learning” chapter in the Linux user’s guide NXP’s eIQ software supports the OpenCV library – a well-known industry standard comprised of programming functions that can perform image processing, video encoding/decoding, video analysis and object detection, in addition to processing of deep neural networks (DNN) and classical machine learning algorithms (ML). eIQ software includes inference engines, neural network compilers and optimized libraries. 66 drivers installed as well. MX 95 applications processor family offers secure, safety enabled platforms with ML acceleration for automotive, industrial, and IoT edge applications. MX RT crossover MCUs, and i. exe I am getting the following hints: [CONVERTER] 2021-09-14 11:26:19. MX RT crossover MCUs. This document describes the eIQ Machine Learning Software for the NXP L4. MX8M applications processors. Hi, I am new to eIQ Portal and wondering what kind of cudnn/Tensorflow version etc. NXP’s eIQ software development environment for AI includes tools for data collection and dataset curation, as well as choosing a model, training and profiling for NXP targets and deployment. MX 8M Plus. eIQ Watermarking model protection can help detect when an ML model has been copied without permission and can also help provide copyright protection based on the creative art of the secret image used. The NXP eIQ is contained in the meta-imx/meta-ml Yocto layer. eIQ TOOLKIT The eIQ machine learning software development environment includes the eIQ Toolkit, an easy-to-use ML workflow tool designed to ease ML development. MX and i. For more information on the eIQ software in these releases (L4. The NXP® eIQ (“edge intelligence”) ML software environment provides the key ingredients to do inference with neural network (NN) models on embedded systems and deploy ML algorithms on NXP microprocessors and microcontrollers for edge nodes. Jul 11, 2019 · The eIQ Machine Learning Software Development Environment takes advantage of existing hardware to accelerate ML application development without requiring hardware specific for machine learning. EiQ is the leading supply chain intelligence software designed to help businesses achieve total supply chain confidence through data-driven insights. notebook The eIQ software integration into our MCUXpresso and Yocto environments takes care of all ML software dependencies, including the necessary hardware abstraction layers that connect the advanced machine learning technology to the underlying compute engines—bridging all the tools needed to bring your ML models to production. 19 BSP, the eIQ software is pre-integrated in the BSP release and this document is no longer necessary or being maintained. The i. 915128: W tensorflow/stream_executor/pla eIQ software includes a variety of application examples that demonstrate how to integrate neural networks into voice, vision and sensor applications. eIQ allows you to get up and running within minutes instead of weeks. When executing inference on Cortex-A cores, NXP eIQ inference engines support multi-threaded execution. NXP Semiconductors eIQ Machine Learning Software Development Environment is a combination of libraries and development tools for use with NXP microprocessors and microcontrollers. Machine Learning Goes Mainstream - eIQ™ ML Software Development Environment NXP Semiconductors 33. EiQ is used by businesses to optimise supply chain risk management. What I do is importing around 200 pictures, annotating each picture, selecting detection mode (Balanced, NPU), and leaving the rest default. 30. 19 releases; L4. MX 8 processing platforms, we’ve significantly expanded our eIQ software environment to include new eIQ Toolkit workflow tools, GUI-based eIQ Portal development environment and the DeepViewRT ™ inference engine optimized for i. eIQ supported inference engines work out of the box and are already tested and optimized, allowing for performance enhancements compared to the original code. My eIQ Portal version is 2. The eIQ software is accompanied by sample applications in object detection and voice recognition, to provide a basis for ML at the edge. Solved: Hi, I was trying to do some training using eIQ Portal v2. 1 Software Stack Introduction The NXP eIQ Machine Learning Software Development Environment (hereinafter referred to as "NXP eIQ") provides a set of libraries and development tools for machine learning applications targeting NXP microcontrollers and application processors. When launching the eIQ Portal. I do have a GeForce RTX 2060 GPU with CUDA 11. eIQ software supports the Arm NN SDK – an inference engine framework that provides a bridge between neural network (NN) frameworks and Arm machine learning processors, including NXP’s i. Download eIQ Toolkit Installer from VEXcode IQ provides tools and resources for coding in Blocks and Python, enabling users to create projects and explore robotics programming. This allows users to find the original re-trainable This Lab 4 explains how to get started with TensorFlow Lite application demo on i. Solved: I tried importing a large folder of images using the script Structured Folders Importer. eIQ Getting Started with NXP Microcontrollers eIQ® is comprised of multiple pieces of hardware and software to enable users to run machine learning models on embedded devices. MX Applications Processors Developing machine learning (ML) applications for embedded devices can be a daunting task. . Machine Learning at the Edge: eIQ Software for i. ipynb and following the Data Import Lab instructions. MX and Layerscape ® processors. It includes tools like eIQ Time Series Studio for sensor-based AI, eIQ GenAI Flow for LLM fine-tuning, and model watermarking for IP protection. datastore as ds from tqdm. , but as you can see in the below image, the GPU utilization is almo To advance AI on the edge, we are introducing the eIQ® Time Series Studio (eIQ TSS), a new tool in our eIQ AI and machine learning development software family. Jul 28, 2025 · NXP’s eIQ (Edge Intelligence Environment) is a development environment that simplifies AI/ML on edge devices. For the traditional embedded developer, the learning curve can be quite steep, as there are numerous decisions that must be made and For more information and complete details please be sure to check out the "NXP eIQ Machine Learning" chapter in the Linux User Guide (starting on L4. MX RT devices. must be pre installed or if they are delivered with the program itself. MX9 and i. The following examples were tested and used for training purposes. The Flow supports conversational AI in English on the NXP i. MX family SoCs. 2. 14 BSP release. Integrated into NXP's Yocto development environment, eIQ software delivers TensorFlow Lite for NXP’s MPU platforms. MX RT1170 evaluation kit (EVK) provides a high-performance solution in a highly integrated board. So I couldn't run the training continuously. eIQ software includes a variety of application examples that demonstrate how to integrate neural networks into voice, vision and sensor applications. eIQ® Time Series Studio (TSS) is an end-to-end development tool with automated machine learning (autoML) that simplifies creating and optimizing time series AI models for NXP processors. NXP eIQ NXP eIQ software provides the basis for Machine Learning application optimized for i. Optimizing specific algorithms for resource-constrained devices being deployed at the edge is a better solution when it comes to accelerating the move to the edge. 14 on Windows 11 but every time I try to start the training process I get this NXP is making it easier to deploy and use AI across a broad spectrum of edge processors with its eIQ AI and machine learning development software. The eIQ Toolkit makes machine learning development faster and easier on NXP EdgeVerse Processors with an intuitive GUI (eIQ Portal) and command line host tools. The developer can choose whether to deploy their ML applications on Arm Cortex A, Cortex M, and GPUs, or for high-end acceleration on the neural processing unit of the i. 1. We created a python script as mentioned in the notebook as shown below : import os import deepview. To be understandable each application contains a read-me file allowing the user to get started with th NXP’s Application Code Hub enables engineers to easily find microcontroller software examples, code snippets, application software packs and demos developed by our in-house experts. 8. 3K subscribers Subscribed eIQ Toolkit依托直观的GUI (eIQ Portal)与命令行主机工具，赋能开发人员在NXP EdgeVerse处理器上更快速、更简易地进行机器学习开发。 eIQ Portal是一款直观的图形用户界面 (GUI)，可简化ML解决方案开发。 开发人员可在该Portal中创建、优化、调试、可视化和导出ML模型。 The NXP eIQ Auto Machine Learning toolkit provides high performance and rapid deployment of ML algorithms across the range of NXP S32 Automotive MCU/MPUs. 0 within Ubuntu 20. eIQ Toolkit依托直观的GUI (eIQ Portal)与命令行主机工具，赋能开发人员在NXP EdgeVerse处理器上更快速、更简易地进行机器学习开发。 eIQ Portal是一款直观的图形用户界面 (GUI)，可简化ML解决方案开发。 开发人员可在该Portal中创建、优化、调试、可视化和导出ML模型。 Accelerate edge AI development with NXP’s eIQ® software for scalable machine learning on EdgeVerse devices. MX RT1060 NXP Semiconductors eIQ Machine Learning Software Development Environment is a combination of libraries and development tools for use with NXP microprocessors and microcontrollers. Are you sure you are using the eIQ Portal v2. It covers how to import time series data, shows how the tool can generate multiple machine learning (ML) algorithms, and describes how to deploy those generated models to y eIQ software includes a variety of application examples that demonstrate how to integrate neural networks into voice, vision and sensor applications. The eIQ Toolkit enables graph-level profiling capabilities with runtime insights to optimize neural network architectures for execution on EdgeVerseTM processors. Through artificial intelligence, proprietary data and robust analytics, EiQ empowers businesses to conduct end-to-end supply chain due diligence, manage their most critical sustainability risks eIQ® GenAI Flow eIQ® GenAI Flow is a software pipeline for AI-powered experiences on edge devices. Hello Team, When using eIQ portal, the CPU utilization is reaching 100% which causes system crash regularly. EiQ integrates AI-powered analytics, industry-leading verified datasets, and technical expertise to provide unparalleled visibility into sourcing risks, compliance requirements and supply chain sustainability challenges. MX8 board using Inference Engines for eIQ Software. It includes toolkits, libraries, and optimized runtimes, all designed to work with NXP’s application processors like the i. NXP’s eIQ™ Machine Learning Software simplifies this process by offering a powerful yet user-friendly platform to build, train, evaluate, and deploy ML models — even for those new to AI. 19, L5. Beginning with the L4. Some of the key pieces of eIQ enablement for NXP microcontrollers include: eIQ Time Series Studio - PC tool to create and d NXP eIQ® Auto Machine Learning (ML) software development kit empowers developers to build intelligent automotive solutions—without requiring deep AI expertise. The eIQ Sample Apps repository hosts Machine Learning applications demos based on the eIQ™ ML Software Development Environment. segzd3, eqq7, h36bu, ztvl8, xce04d, pwus, hnomt, g7svkh, swwj, xzs11v,