CenterPoint: Optimized for Qualcomm Devices

CenterPoint is a LiDAR-based 3D object detection model that detects objects by predicting their centers and regressing other attributes. It is designed for high accuracy and real-time performance in autonomous driving applications.

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
QNN_DLC float Universal QAIRT 2.45 Download
TFLITE float Universal Download

For more device-specific assets and performance metrics, visit CenterPoint 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 CenterPoint on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.driver_assistance

Model Stats:

  • Model checkpoint: PointPillars
  • Input resolution: 5x20x5, 5x4, 5
  • Number of parameters: 21.8M
  • Model size: 83.3 MB

Performance Summary

Model Runtime Precision Chipset Inference Time (ms) Peak Memory Range (MB) Primary Compute Unit
CenterPoint QNN_DLC float Snapdragon® X2 Elite 182.793 ms 2 - 2 MB NPU
CenterPoint QNN_DLC float Snapdragon® X Elite 322.157 ms 2 - 2 MB NPU
CenterPoint QNN_DLC float Snapdragon® 8 Gen 3 Mobile 252.712 ms 0 - 753 MB NPU
CenterPoint QNN_DLC float Snapdragon® 8 Gen 1 Mobile 518.366 ms 2 - 736 MB NPU
CenterPoint QNN_DLC float Qualcomm® QCS8275 920.139 ms 2 - 451 MB NPU
CenterPoint QNN_DLC float Qualcomm® QCS8550 (Proxy) 335.833 ms 2 - 4 MB NPU
CenterPoint QNN_DLC float Qualcomm® QCS8450 518.366 ms 2 - 736 MB NPU
CenterPoint QNN_DLC float Snapdragon® 8 Elite Mobile 210.78 ms 0 - 461 MB NPU
CenterPoint QNN_DLC float Qualcomm® SA8295P 442.021 ms 1 - 449 MB NPU
CenterPoint QNN_DLC float Snapdragon® 8 Elite Gen 5 Mobile 174.671 ms 2 - 722 MB NPU
CenterPoint QNN_DLC float Qualcomm® SA7255P 920.139 ms 2 - 451 MB NPU
CenterPoint QNN_DLC float Qualcomm® QCS9075 423.202 ms 2 - 11 MB NPU
CenterPoint QNN_DLC float Qualcomm® QCS8750 210.78 ms 0 - 461 MB NPU
CenterPoint QNN_DLC float Qualcomm® QCS7181 322.157 ms 2 - 2 MB NPU
CenterPoint TFLITE float Snapdragon® 8 Gen 3 Mobile 3854.229 ms 1835 - 1843 MB CPU
CenterPoint TFLITE float Snapdragon® 8 Gen 1 Mobile 5099.219 ms 1858 - 1870 MB CPU
CenterPoint TFLITE float Qualcomm® QCS8275 6174.644 ms 1848 - 1856 MB CPU
CenterPoint TFLITE float Qualcomm® QCS8550 (Proxy) 5389.073 ms 1828 - 1836 MB CPU
CenterPoint TFLITE float Qualcomm® SA8775P 5380.349 ms 1807 - 1813 MB CPU
CenterPoint TFLITE float Qualcomm® SA8650P 5380.349 ms 1807 - 1813 MB CPU
CenterPoint TFLITE float Qualcomm® SA8255P 5380.349 ms 1807 - 1813 MB CPU
CenterPoint TFLITE float Qualcomm® QCS8450 5099.219 ms 1858 - 1870 MB CPU
CenterPoint TFLITE float Snapdragon® 8 Elite Mobile 2816.604 ms 1853 - 1865 MB CPU
CenterPoint TFLITE float Qualcomm® SA8295P 3502.138 ms 1807 - 1813 MB CPU
CenterPoint TFLITE float Snapdragon® 8 Elite Gen 5 Mobile 805.643 ms 1979 - 1988 MB CPU
CenterPoint TFLITE float Qualcomm® SA7255P 6174.644 ms 1848 - 1856 MB CPU
CenterPoint TFLITE float Qualcomm® QCS9075 5160.994 ms 2362 - 2383 MB CPU
CenterPoint TFLITE float Qualcomm® QCS8750 2816.604 ms 1853 - 1865 MB CPU

License

  • The license for the original implementation of CenterPoint can be found here.

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