S32V Knowledge Base

cancel
Showing results for 
Show  only  | Search instead for 
Did you mean: 

S32V Knowledge Base

Labels

Discussions

Sort by:
Index | Previous | Next
View full article
Index | Previous | Next
View full article
Index | Previous | Next
View full article
Index | Previous | Next Explains the three main components of creating a kernel: Implementation, Metadata and Wrapper.
View full article
Index | Previous | Next Introduction to the lesson of how to create an Apex program
View full article
SOFTWARE The S32 Design Studio for ARM® The S32 Design Studio for Vision The Vision Toolbox for MATLAB® The Automotive Ethernet Audio Video Bridging (AVB) HARDWARE The SBC-S32V234 evaluation board The S32V234-EVB2 evaluation system The NXP Blue Box Autonomous Driving Development Platform TOOLS NEXT TOPIC
View full article
The S32V234 is our 2nd generation vision processor family designed to support computation intensive applications for image processing and offers an ISP, powerful 3D GPU, dual APEX-2 vision accelerators, security and supports SafeAssure™. S32V234 is suited for ADAS, NCAP front camera, object detection and recognition, surround view, machine learning and sensor fusion applications. S32V234 is engineered for automotive-grade reliability, functional safety and security measures to support vehicle and industrial automation. S32V234 has a complete enablement platform supported by S32 Design Studio IDE for Vision which includes a compiler, debugger, Vision SDK, Linux BSP and graph tools. Video Link : 8296 The target applications for S32V234 are: Automotive Sensor Fusion Systems Automotive Vision Systems Front View Camera Intelligent Roadside Unit Smart  Rear-View Camera Surround View & Sense Park Assist System Surround View Park Assist System NEXT TOPIC
View full article
WHAT YOU WILL LEARN: Understand the basic aspects of S32V234 vision processors, the second generation vision MPU family for supporting computation intensive applications for image processing 1.1 S32V overview High-level overview Target applications 1. 2 S32V enablement Software Hardware Tools
View full article
Index | Previous | Next This video will present the high level ISP architecture in the S32V234 with some background information.
View full article
Index | Previous | Next This video introduces the concepts of Image Signal Processing for cameras like the ones typically applied to Raw camera data and that could be implemented in the S32V234 ISP.
View full article
Index | Previous | Next This video explains what exactly is the Apex Core Framework, what is for, why it was implemented and some use cases.
View full article
Index | Previous | Next Shows a couple of practical examples of kernels and how to implement them with code
View full article
Index | Previous | Next This video goes on detail over the different vector instructions supported by the vector engine
View full article
Index | Previous | Next Video goes on detail regarding the APU (Kernel) programming
View full article
Index | Previous | Next This video explains the features and advantages of Apex-CV Library, what is included and how it can be used
View full article
Index | Previous | Next This video explains the programming model for Apex, differences between APU vs ACF programming and what HW blocks are involved on this. It also goes over the concept of Kernel, Graph and Process.
View full article
Index | Previous | Next This video explains the different tools and software, their structure and how they work. After watching this video you will have a better understanding how the different Apex software components interact together.
View full article
Index | Previous | Next This video studies the Apex HW architecture in more detail to understand the different internal blocks interact to perform memory transfers, vector and scalar operations in a efficient manner.
View full article
Index | Previous | Next This video provides a quick summary of the previously studied concepts regarding the Apex and image processing 
View full article
Index | Previous | Next The video explains the concept of localization and how that affects performance of image processing
View full article