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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.

Snapdragon® X Elite
6.53ms
Inference Time
3MB
Memory Usage
228NPU
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 Compute Chipsets

  • Snapdragon® X Elite