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Object Detection

Fast and accurate object detection using quantized YOLOv8n optimized for embedded edge devices.

$0.00
More Information
Object Detection
app details
Model Type

Object Detection

Framework

TensorFlow Lite

Algorithm

Ultralytics YOLOv8n (TFLite Quantized)

Technical Details

This unit performs object detection using a quantized YOLOv8n model exported to TensorFlow Lite by Ultralytics. It processes static RGB images or video frames to return bounding boxes with class labels. Designed for real-time inference on edge CPUs and NPUs. Class mapping is provided via metadata.json. Ideal for security, safety, and visual AI tasks in constrained environments.

Use Cases
Quality Control
Supported IoT Devices
AI optimized hardware Fanless embedded PCs Modules
supported chipsets
Intel® Core™ i3 Qualcomm® Dragonwing QCS6490 Qualcomm® Dragonwing QCS5430 NXP i.MX 8M Plus NXP i.MX 95
Performance Benchmark
Hardware
Latency (ms)
Memory Usage
Processing unit
SECO SOM-SMARC-QCS6490
123.16 ms
14.06 MB
CPU
SECO SOM-SMARC-iMX8Plus
1469 ms
10.55 MB
CPU
SECO SOM-SMARC-MX95
363.87 ms
14.06 MB
CPU
SECO Titan 300 TGL-UP3 AI LiteRT
45.9 ms
14.06 MB
CPU
SECO Titan 300 TGL-UP3 AI OpenVino
31.32 ms
14.06 MB
CPU
SECO SOM-SMARC-iMX8Plus
121.43 ms
10.55 MB
NPU

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