Object Detection
PyTorch
android

CenterNet-2D: Optimized for Qualcomm Devices

CenterNet-2D is machine learning model that detects objects by finding their center points.

This is based on the implementation of CenterNet-2D found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Getting Started

There are two ways to deploy this model on your device:

Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

Runtime Precision Chipset SDK Versions Download
PRECOMPILED_QNN_ONNX float Snapdragon® X2 Elite QAIRT 2.45, ONNX Runtime 1.27.1 Download
PRECOMPILED_QNN_ONNX float Snapdragon® X Elite QAIRT 2.45, ONNX Runtime 1.27.1 Download
PRECOMPILED_QNN_ONNX float Snapdragon® 8 Gen 3 Mobile QAIRT 2.45, ONNX Runtime 1.27.1 Download
PRECOMPILED_QNN_ONNX float Snapdragon® 8 Gen 1 Mobile QAIRT 2.45, ONNX Runtime 1.27.1 Download
PRECOMPILED_QNN_ONNX float Qualcomm® Dragonwing™ QCS8550 (Proxy) QAIRT 2.45, ONNX Runtime 1.27.1 Download
PRECOMPILED_QNN_ONNX float Qualcomm® Dragonwing™ IQ-9075 QAIRT 2.45, ONNX Runtime 1.27.1 Download
PRECOMPILED_QNN_ONNX float Snapdragon® 8 Elite Mobile QAIRT 2.45, ONNX Runtime 1.27.1 Download
PRECOMPILED_QNN_ONNX float Snapdragon® 8 Elite Gen 5 Mobile QAIRT 2.45, ONNX Runtime 1.27.1 Download
QNN_CONTEXT_BINARY float Snapdragon® X2 Elite QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Snapdragon® X Elite QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Snapdragon® 8 Gen 3 Mobile QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Snapdragon® 8 Gen 1 Mobile QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Qualcomm® Dragonwing™ QCS8550 (Proxy) QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Qualcomm® SA8775P QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Qualcomm® Dragonwing™ IQ-9075 QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Qualcomm® SA7255P QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Qualcomm® SA8295P QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Snapdragon® 8 Elite Mobile QAIRT 2.45 Download
QNN_CONTEXT_BINARY float Snapdragon® 8 Elite Gen 5 Mobile QAIRT 2.45 Download

For more device-specific assets and performance metrics, visit CenterNet-2D on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:

  • Custom weights (e.g., fine-tuned checkpoints)
  • Custom input shapes
  • Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for CenterNet-2D on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.object_detection

Model Stats:

  • Model checkpoint: ctdet_coco_dla_2x.pth
  • Input resolution: 1 x 3 x 512 x 512
  • Number of parameters: 20.2M
  • Model size: 37.6 MB

Performance Summary

Model Runtime Precision Chipset Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit
CenterNet-2D PRECOMPILED_QNN_ONNX float Snapdragon® X2 Elite 241.122 ms 36 - 36 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Snapdragon® X Elite 366.181 ms 56 - 56 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Snapdragon® 8 Gen 3 Mobile 264.402 ms 15 - 22 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Snapdragon® 8 Gen 1 Mobile 752.18 ms 9 - 23 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Qualcomm® Dragonwing™ QCS8550 (Proxy) 357.311 ms 14 - 15 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Qualcomm® QCS8450 752.18 ms 9 - 23 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Qualcomm® Dragonwing™ IQ-9075 365.356 ms 8 - 14 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Qualcomm® Dragonwing™ IQ-X7181 366.181 ms 56 - 56 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Qualcomm® Dragonwing™ Q-8750 290.888 ms 14 - 20 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Snapdragon® 8 Elite Mobile 290.888 ms 14 - 20 MB NPU
CenterNet-2D PRECOMPILED_QNN_ONNX float Snapdragon® 8 Elite Gen 5 Mobile 232.46 ms 16 - 23 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Snapdragon® X2 Elite 239.211 ms 3 - 3 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Snapdragon® X Elite 366.812 ms 3 - 3 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Snapdragon® 8 Gen 3 Mobile 264.595 ms 4 - 11 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Snapdragon® 8 Gen 1 Mobile 722.704 ms 3 - 18 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® Dragonwing™ QCS8275 516.665 ms 1 - 10 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® Dragonwing™ QCS8550 (Proxy) 360.754 ms 3 - 5 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® SA8775P 373.471 ms 1 - 10 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® SA8650P 373.471 ms 1 - 10 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® SA8255P 373.471 ms 1 - 10 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® QCS8450 722.704 ms 3 - 18 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® Dragonwing™ IQ-9075 364.908 ms 3 - 13 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® Dragonwing™ IQ-X7181 366.812 ms 3 - 3 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® Dragonwing™ Q-8750 289.666 ms 1 - 10 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® SA7255P 516.665 ms 1 - 10 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Qualcomm® SA8295P 442.142 ms 2 - 8 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Snapdragon® 8 Elite Mobile 289.666 ms 1 - 10 MB NPU
CenterNet-2D QNN_CONTEXT_BINARY float Snapdragon® 8 Elite Gen 5 Mobile 231.428 ms 3 - 13 MB NPU

License

  • The license for the original implementation of CenterNet-2D can be found here.

References

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Paper for qualcomm/CenterNet-2D