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Yolo-X

Real‑time object detection optimized for mobile and edge.

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

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This model is currently not supported on any Compute chipset.

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Model RepositoryHugging FaceResearch Paper

Technical Details

Model checkpoint:YoloX Small
Input resolution:640x640
Number of parameters:8.98M
Model size (float):34.3 MB
Model size (w8a16):9.53 MB
Model size (w8a8):8.96 MB

Applicable Scenarios

  • Factory Automation
  • Robotic Navigation
  • Camera

License

Model:APACHE-2.0

Tags

  • real-time

Supported Compute Devices

  • Snapdragon X Elite CRD
  • Snapdragon X Plus 8-Core CRD
  • Snapdragon X2 Elite CRD

Supported Compute Chipsets

  • Snapdragon® X Elite
  • Snapdragon® X Plus 8-Core
  • Snapdragon® X2 Elite

Related Models

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View details for the Yolo-v6 model.

Yolo-v6

Real-time object detection optimized for mobile and edge.

View details for the Yolo-v7 model.

Yolo-v7

Real-time object detection optimized for mobile and edge.

View details for the YOLOv8-Detection model.

YOLOv8-Detection

Real-time object detection optimized for mobile and edge by Ultralytics.

Sample Appsfeaturing Yolo-X

See all sample apps
View details for the Object Detection Android app.

Object Detection Android

On-device object detection with TFLite

View details for the Object Detection Windows app.

Object Detection Windows

Accelerated object detection with YOLO-X

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