Difference between revisions of "Edge AI SDK/AI Framework/Qualcomm"
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| − | <span style="font-size:larger;">Quick Start / Application / Video or WebCam / | + | <span style="font-size:larger;">Quick Start / Application / Video or WebCam / DSP </span> |
| − | <span style="font-size:larger;">[[File: | + | <span style="font-size:larger;">[[File:QCS6490-VisionAI_GUI.png|800px]]</span> |
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| + | <span style="font-size:larger;">[[File:QCS6490-Object-Detect-1.png|800px]]</span> | ||
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| style="width: 154px;" | <span style="font-size:larger;">Object Detection</span> | | style="width: 154px;" | <span style="font-size:larger;">Object Detection</span> | ||
| − | | style="width: 179px;" | <span style="font-size:larger;"> | + | | style="width: 179px;" | <span style="font-size:larger;">yolov5x (quantized)</span> |
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| style="width: 154px;" | <span style="font-size:larger;">Face Detection</span> | | style="width: 154px;" | <span style="font-size:larger;">Face Detection</span> | ||
| − | | style="width: 179px;" | <span style="font-size:larger;"> | + | | style="width: 179px;" | <span style="font-size:larger;">yolov5n-face (quantized)</span> |
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| − | | style="width: 154px;" | <span style="font-size:larger;"> | + | | style="width: 154px;" | <span style="font-size:larger;">Person Detection</span> |
| − | | style="width: 179px;" | <span style="font-size:larger;"> | + | | style="width: 179px;" | <span style="font-size:larger;">yolov5x (quantized)</span> |
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Revision as of 10:52, 27 February 2025
Contents
QCS6490 AI Suite
AI Software Suite offers breakthrough AI accelerators and Vision processors uniquely designed to accelerate embedded deep learning applications on edge devices.
Qualcomm devices are accompanied by a comprehensive AI SDK that enables the compilation of deep learning models and the implementation of AI applications in production environments. The model build environment seamlessly integrates with common ML frameworks to allow smooth and easy integration in existing development ecosystems. The runtime environment enables integration and deployment in host processors, such as ARM based products, when utilizing QCS6490 vision processor.
Applications
SNPE is a SDK 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. SNPE 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 Qualcomm's AI processors' top-notch throughput and power efficiency. Furthermore, SNPE serves as a demonstration of Qualcomm's system integration capabilities, showcasing specific use cases on predefined software and hardware platforms. Utilizing SNPE simplifies integration with Qualcomm's runtime software stack and offers a starting point for users to fine-tune their applications. By demonstrating Qualcomm'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 Qualcomm's runtime software stack, and provides customers with a foundation to fine-tune their applications.
Edge AI SDK / Application
Quick Start / Application / Video or WebCam / DSP
| Application | Model |
| Object Detection | yolov5x (quantized) |
| Face Detection | yolov5n-face (quantized) |
| Person Detection | yolov5x (quantized) |
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
Edge AI SDK / Benchmark
Evaluate the Hailo-8 performance with Edge AI SDK.
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-8 Temperature
python ts_monitoring_2023Sep07.py
Edge AI SDK / Monitoring
