Yolo-v6

    Real-time object detection optimized for mobile and edge.

    YoloV6 is a machine learning model that predicts bounding boxes and classes of objects in an image.

    Qualcomm® QCS8550
    QCS8550 (Proxy)
    7.95ms
    Inference Time
    0-3MB
    Memory Usage
    182NPU
    Layers

    Technical Details

    Model checkpoint:YoloV6-N
    Input resolution:640x640
    Number of parameters:4.68M
    Model size:17.9 MB

    Applicable Scenarios

    • Factory Automation
    • Robotic Navigation
    • Camera

    Licenses

    Source Model:GPL-3.0
    Deployable Model:GPL-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 IoT Devices

    • QCS8550 (Proxy)

    Supported IoT Chipsets

    • Qualcomm® QCS8550