Edge AI SDK/AI Framework/Nvidia x86 64

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RTX-A5000 AI Suite rc

The NVIDIA RTX A5000 is supported by an advanced software suite designed to accelerate AI, data science, and graphics applications on professional workstations.

Spearhead innovation from your desktop with the NVIDIA RTX A5000 graphics card, the perfect balance of power, performance, and reliability to tackle complex workflows. Built on the latest NVIDIA Ampere architecture and featuring 24 gigabytes (GB) of GPU memory, it’s everything designers, engineers, and artists need to realize their visions for the future, today.

 

 

Applications

TAPPAS is a solution designed to streamline the development and deployment of edge applications demanding high AI performance. This reference application software package empowers users to expedite their time-to-market by minimizing the development workload. TAPPAS encompasses a user-friendly set of fully operational application examples based on GStreamer, featuring pipeline elements and pre-trained AI tasks. These examples leverage advanced Deep Neural Networks, highlighting Hailo's AI processors' top-notch throughput and power efficiency. Furthermore, TAPPAS serves as a demonstration of Hailo's system integration capabilities, showcasing specific use cases on predefined software and hardware platforms. Utilizing TAPPAS simplifies integration with Hailo's runtime software stack and offers a starting point for users to fine-tune their applications. By demonstrating Hailo's system integration scenarios on both predefined software and hardware platforms, it can be used for evaluations, reference code, and demos. This approach effectively accelerates time to market, streamlines integration with Hailo's runtime software stack, and provides customers with a foundation to fine-tune their applications.

Refer to github-TAPPAS

 

 

Edge AI SDK / Application

Quick Start / Application / Video or WebCam / VPU

ObjectDetection

 

Application Model
Object Detection yolov5m_wo_spp_60p.hef
Person Detection yolov5s_personface_reid.hef / repvgg_a0_person_reid_2048.hef
Face Detection arcface_mobilefacenet_v1.hef / scrfd_10g.hef
Pose Estimation centerpose_regnetx_1.6gf_fpn.hef

Benchmark

In order to measure FPS, power and latency of the Hailo Model Zoo networks you can use the HailoRT command line interface. For more information please refer to the HailoRT documentation in link.

 

 

 

Hailo-8 Benchmark

hailortcli benchmark <Hailo's Model .hef >

hailortcli benchmark resnet_v1_18.hef

benchmark

 

 

Edge AI SDK / Benchmark

Evaluate the Hailo-8 performance with Edge AI SDK.

Benchmark

 

 

HailoRT CLI

HailoRT CLI - a command line application used to control the Hailo device, run inferences, collect statistics and device events, etc. Use "--help" to exhibit more usages.

hailortcli --help

Refer to github-hailort

 

 

 

Hailo-8 Utilization

hailortcli monitor

Hailo VPU Usage

 

 

Hailo-8 Temperature

python ts_monitoring_2023Sep07.py

  Thermal in hailortcli.png

Edge AI SDK / Monitoring

thermal