- NXP Forums
- Product Forums
- General Purpose MicrocontrollersGeneral Purpose Microcontrollers
- i.MX Forumsi.MX Forums
- QorIQ Processing PlatformsQorIQ Processing Platforms
- Identification and SecurityIdentification and Security
- Power ManagementPower Management
- MCX Microcontrollers
- S32G
- S32K
- S32V
- MPC5xxx
- Other NXP Products
- Wireless Connectivity
- S12 / MagniV Microcontrollers
- Powertrain and Electrification Analog Drivers
- Sensors
- Vybrid Processors
- Digital Signal Controllers
- 8-bit Microcontrollers
- ColdFire/68K Microcontrollers and Processors
- PowerQUICC Processors
- OSBDM and TBDML
-
- Solution Forums
- Software Forums
- MCUXpresso Software and ToolsMCUXpresso Software and Tools
- CodeWarriorCodeWarrior
- MQX Software SolutionsMQX Software Solutions
- Model-Based Design Toolbox (MBDT)Model-Based Design Toolbox (MBDT)
- FreeMASTER
- eIQ Machine Learning Software
- Embedded Software and Tools Clinic
- S32 SDK
- S32 Design Studio
- Vigiles
- GUI Guider
- Zephyr Project
- Voice Technology
- Application Software Packs
- Secure Provisioning SDK (SPSDK)
- Processor Expert Software
-
- Topics
- Mobile Robotics - Drones and RoversMobile Robotics - Drones and Rovers
- NXP Training ContentNXP Training Content
- University ProgramsUniversity Programs
- Rapid IoT
- NXP Designs
- SafeAssure-Community
- OSS Security & Maintenance
- Using Our Community
-
-
- Home
- :
- Software Forums
- :
- eIQ Machine Learning Software Knowledge Base
- :
- Glow Demos with Camera Support
Glow Demos with Camera Support
- Subscribe to RSS Feed
- Mark as New
- Mark as Read
- Bookmark
- Subscribe
- Printer Friendly Page
- Report Inappropriate Content
Glow Demos with Camera Support
Glow Demos with Camera Support
The two demos attached for models that were compiled using the GLOW AOT tools and uses a camera connected to the i.MXRT1060-EVK to generate data for inferencing. The default MCUXpresso SDK Glow demos inference on static images, and these demos expand the capability of those projects to do inferencing on camera data. Each demo uses the default model that is found in the SDK.
A readme.txt file found in the /doc folder of each demo provides details for each demo, and there a PDF available inside that same /doc folder for example images to point the camera at for inferencing.
Software requirements
====================
- MCUXpresso IDE 11.2.x
- MCUXpresso SDK for RT1060
Hardware requirements
=====================
- Micro USB cable
- Personal Computer
- IMXRT1060-EVK board with included camera + RK043FN02H-CT LCD
Board settings
==============
Camera and LCD connected to i.MXRT1060-EVK
Prepare the demo
================
1. Install and open MCUXpresso IDE 11.2
2. If not already done, import the RT1060 MCUXpresso SDK by dragging and dropping the zipped SDK file into the "Installed SDKs" tab.
3. Download one of the attached zip files and import the project using "Import project(s) from file system.." from the Quickstart panel. Use the "Archive" option to select the zip file that contains this project.
4. Build the project by clicking on "Build" in the Quickstart Panel
5. Connect a USB cable between the host PC and the OpenSDA port (J41) on the target board.
6. Open a serial terminal with the following settings:
- 115200 baud rate
- 8 data bits
- No parity
- One stop bit
- No flow control
7. Download the program to the target board by clicking on "Debug" in the Quickstart Panel and then click on the "Resume" button in the Debug perspective that comes up to run the demo.
Running the demo
================
- For CIFAR10 demo: Use the camera to look at images of airplanes, ships, deer, etc that can be recognized by the CIFAR10 model. The include PDF can be used for example images.
- For MNIST demo: Use the camera to look at handwritten digits which can be recognized by the LeNet MNIST model. The included PDF can be used for example digits or you can write your own.
For further details see the readme.txt file found inside each demo in the /doc directory. Also see the Glow Lab for i.MX RT for more details on how to compile neural network models with Glow.
