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YOLOv8-Detection-Quantized

Quantized real‑time object detection optimized for mobile and edge by Ultralytics.

Ultralytics YOLOv8 is a machine learning model that predicts bounding boxes and classes of objects in an image. This model is post‑training quantized to int8 using samples from the COCO dataset.

Technical Details

Model checkpoint:YOLOv8-N
Input resolution:640x640
Number of parameters:3.18M
Model size:3.26 MB

Applicable Scenarios

  • Factory Automation
  • Robotic Navigation
  • Camera

Licenses

Source Model:AGPL-3.0
Deployable Model:AGPL-3.0

Tags

  • real-time
  • quantized

Supported IoT Devices

  • QCS6490 (Proxy)
  • QCS8250 (Proxy)
  • QCS8550 (Proxy)
  • RB3 Gen 2 (Proxy)
  • RB5 (Proxy)

Supported IoT Chipsets

  • Qualcomm® QCS6490 (Proxy)
  • Qualcomm® QCS8250 (Proxy)
  • Qualcomm® QCS8550 (Proxy)

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