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Yolo-v5

Real‑time object detection optimized for mobile and edge.

YoloV5 is a machine learning model that predicts bounding boxes and classes of objects in an image.

23.8ms
Inference Time
6 ‑ 39MB
Memory Usage
515NPU
9CPU
Layers
See more metrics
Model RepositoryHugging Face

Technical Details

Model checkpoint:YoloV5-M
Input resolution:640x640
Number of parameters:21.2M
Model size:81.1 MB

Applicable Scenarios

  • Factory Automation
  • Robotic Navigation
  • Camera

Licenses

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

Tags

  • real-time

Supported IoT Devices

  • QCS8275 (Proxy)
  • QCS8550 (Proxy)
  • QCS9075 (Proxy)

Supported IoT Chipsets

  • Qualcomm® QCS8275 (Proxy)
  • Qualcomm® QCS8550 (Proxy)
  • Qualcomm® QCS9075 (Proxy)

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