Toradex has an extensive partner network as part of its ecosystem aimed toward helping customers achieve their goals with the lowest cost-of-ownership and fastest time-to-market. In an effort to help accelerate this, Toradex and its partners have worked together to bring forth partner demo images for evaluation.
The images are provided in the Toradex Easy Installer format and are available from our feeds for online installation, and also as download tarballs for offline installation.
Refer to the Toradex Easy Installer article for instructions on how to load it on the target and install the image you are interested in.
The table below provides an overview of the partner demo images available and links to their respective cover pages:
|Partner||Demo Image||Supported Modules||Summary Overview|
|Qt Company||Qt for Device Creation||Apalis iMX8
Colibri iMX7 (eMMC)
Verdin iMX8M Mini
|Light-weight, Qt-optimized, full software stack for embedded Linux systems|
|MVTec Software GmbH||MVTec Embedded Vision HPeek Demo||Apalis iMX6
|The essence of MVTec HALCON's key features and performance, ease of use in Machine Vision|
|Mender.io||Mender Easy Installer||Colibri iMX7||Secure and robust Over The Air update manager solution for connected embedded Linux devices|
|DiSTI Corporation||DiSTI GL Studio||Colibri iMX6||DiSTI's technology of GL Studio showcased in a UI with the look and feel of automotive design|
|TES Eletronic Solutions||TES 3D Surround View||Apalis iMX6||3D representation of a vehicle driver assistance system based on the input of cameras, GPU optimized|
|ITTIA||ITTIA DB SQL for Device Data Management||Colibri iMX6
|Interactive relational database utilities and management system for intelligent embedded systems|
|BE.services Matrikon OPC UA Server||Apalis iMX6||Matrikon OPC UA Server implementation by BE.services GmbH|
|Kynetics||Kynetics Android||Apalis iMX8QM V1.0B
Colibri iMX8X V1.0B
|Android port to Toradex hardware by Kynetics|
|Amazon Web Services||AWS AI at the Edge Pasta Detection||Apalis iMX8QM||End-to-end demonstration of pasta detection using deep learning and connected to the AWS cloud|