Development Tools for Embedded Vision
ENCOMPASSING MOST OF THE STANDARD ARSENAL USED FOR DEVELOPING REAL-TIME EMBEDDED PROCESSOR SYSTEMS
The software tools (compilers, debuggers, operating systems, libraries, etc.) encompass most of the standard arsenal used for developing real-time embedded processor systems, while adding in specialized vision libraries and possibly vendor-specific development tools for software development. On the hardware side, the requirements will depend on the application space, since the designer may need equipment for monitoring and testing real-time video data. Most of these hardware development tools are already used for other types of video system design.
Both general-purpose and vender-specific tools
Many vendors of vision devices use integrated CPUs that are based on the same instruction set (ARM, x86, etc), allowing a common set of development tools for software development. However, even though the base instruction set is the same, each CPU vendor integrates a different set of peripherals that have unique software interface requirements. In addition, most vendors accelerate the CPU with specialized computing devices (GPUs, DSPs, FPGAs, etc.) This extended CPU programming model requires a customized version of standard development tools. Most CPU vendors develop their own optimized software tool chain, while also working with 3rd-party software tool suppliers to make sure that the CPU components are broadly supported.
Heterogeneous software development in an integrated development environment
Since vision applications often require a mix of processing architectures, the development tools become more complicated and must handle multiple instruction sets and additional system debugging challenges. Most vendors provide a suite of tools that integrate development tasks into a single interface for the developer, simplifying software development and testing.
Qualcomm Technologies’ IoT Strategy: A New Approach, a New Opportunity
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our new blueprint for enabling our partners and end customers to bring more smarts to the edge was one of the highlights of Investor Day Everything around us is either already a lot smarter or aiming to
What is a Digital Twin and Why is It Important to IoT?
This blog post was originally published at eInfochips’ website. It is reprinted here with the permission of eInfochips. The Internet of Things and digital twins have a mutually beneficial relationship. IoT devices provide the real-time data that powers digital twins, while digital twins realize IoT data’s potential through monitoring, optimization, prediction, and decision support for
Top 4 Computer Vision Problems & Solutions in Agriculture — Part 2
This blog post was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. In Part 1 of this series we introduced you with the top 4 issues you are likely to encounter in agriculture related datasets for object detection: occlusion, label quality, data imbalance and scale variation. In Part 2
On the Brink of the Technological Singularity: Is AI Set to Surpass Human Intelligence?
This blog post was originally published at Geisel Software’s website. It is reprinted here with the permission of Geisel Software. Each advancement in artificial intelligence (AI), machine learning (ML), and contemporary large language models (LLMs), rekindles debates over the technological singularity, a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible,
How NVIDIA Jetson AGX Orin Helps Unlock the Power of Surround-view Camera Solutions
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Autonomous vehicles, such as warehouse robots, rely on precise maneuvering. NVIDIA Jetson AGX Orin™-powered surround-view cameras provide a perfectly synchronized solution, allowing these robots to move freely within designated areas without requiring intensive manual intervention.
Streamlining AI Inference Performance and Deployment with NVIDIA TensorRT-LLM Chunked Prefill
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. In this blog post, we take a closer look at chunked prefill, a feature of NVIDIA TensorRT-LLM that increases GPU utilization and simplifies the deployment experience for developers. This builds on our previous post discussing how advanced
Developing and Deploying Vision-based Multi-camera Solutions
This blog post was originally published at eInfochips’ website. It is reprinted here with the permission of eInfochips. Over the past several years, with strong advances in technology, Artificial Intelligence (AI) and Machine Learning (ML) capabilities have become available in highly compact chipsets. These chipsets have been adopted across vision solutions including low power wearable
Synthetic Data is Revolutionizing Sensor Tech: Real Results from Virtual Worlds
This blog post was originally published at Geisel Software’s website. It is reprinted here with the permission of Geisel Software. Imagine you’re a developer on your first day at a new job. You’re handed a state-of-the-art sensor designed to capture data for an autonomous vehicle. The excitement quickly turns to anxiety as you realize the
