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    YOLOv8-Detection

    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.

    4.32ms
    Inference Time
    0-85MB
    Memory Usage
    300NPU
    Layers
    See more metrics
    Model RepositoryHugging FaceResearch Paper

    Technical Details

    Model checkpoint:YOLOv8-N
    Input resolution:640x640
    Number of parameters:3.18M
    Model size:12.2 MB

    Applicable Scenarios

    • Factory Automation
    • Robotic Navigation
    • Camera

    Supported Form Factors

    • Phone
    • Tablet
    • IoT
    • XR

    Licenses

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

    Tags

    • real-time
      A “real-time” model can typically achieve 5-60 predictions per second. This translates to latency ranging up to 200 ms per prediction.

    Supported Devices

    • Google Pixel 3
    • Google Pixel 3a
    • Google Pixel 3a XL
    • Google Pixel 4
    • Google Pixel 4a
    • Google Pixel 5a 5G
    • Samsung Galaxy S21
    • Samsung Galaxy S21 Ultra
    • Samsung Galaxy S21+
    • Samsung Galaxy S22 5G
    • Samsung Galaxy S22 Ultra 5G
    • Samsung Galaxy S22+ 5G
    • Samsung Galaxy S23
    • Samsung Galaxy S23 Ultra
    • Samsung Galaxy S23+
    • Samsung Galaxy S24
    • Samsung Galaxy S24 Ultra
    • Samsung Galaxy S24+
    • Samsung Galaxy Tab S8
    • Xiaomi 12
    • Xiaomi 12 Pro

    Supported Chipsets

    • Snapdragon® 8 Gen 1 Mobile
    • Snapdragon® 8 Gen 2 Mobile
    • Snapdragon® 8 Gen 3 Mobile
    • Snapdragon® 888 Mobile