--- library_name: pytorch license: other tags: - android pipeline_tag: other --- ![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centerpoint/web-assets/model_demo.png) # 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](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/centerpoint) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary). Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) 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](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centerpoint/releases/v0.59.0/centerpoint-qnn_dlc-float.zip) | TFLITE | float | Universal | | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centerpoint/releases/v0.59.0/centerpoint-tflite-float.zip) For more device-specific assets and performance metrics, visit **[CenterPoint on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/centerpoint)**. ### Option 2: Export with Custom Configurations Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/centerpoint) 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](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/centerpoint) 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 | 185.015 ms | 2 - 2 MB | NPU | CenterPoint | QNN_DLC | float | Snapdragon® X Elite | 326.336 ms | 2 - 2 MB | NPU | CenterPoint | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 249.841 ms | 0 - 750 MB | NPU | CenterPoint | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 521.899 ms | 2 - 737 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8275 | 920.314 ms | 1 - 450 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 332.766 ms | 2 - 6 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® SA8775P | 397.325 ms | 1 - 703 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® SA8650P | 397.325 ms | 1 - 703 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® SA8255P | 397.325 ms | 1 - 703 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® QCS8450 | 521.899 ms | 2 - 737 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 388.854 ms | 4 - 13 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 326.336 ms | 2 - 2 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 207.78 ms | 0 - 461 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® SA7255P | 920.314 ms | 1 - 450 MB | NPU | CenterPoint | QNN_DLC | float | Qualcomm® SA8295P | 442.028 ms | 1 - 449 MB | NPU | CenterPoint | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 207.78 ms | 0 - 461 MB | NPU | CenterPoint | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 175.341 ms | 2 - 723 MB | NPU | CenterPoint | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 4086.509 ms | 1835 - 1844 MB | CPU | CenterPoint | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 5376.29 ms | 1860 - 1876 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® Dragonwing™ QCS8275 | 6484.61 ms | 1847 - 1856 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 5056.352 ms | 1893 - 1894 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® SA8775P | 5375.999 ms | 1810 - 1816 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® SA8650P | 5375.999 ms | 1810 - 1816 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® SA8255P | 5375.999 ms | 1810 - 1816 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® QCS8450 | 5376.29 ms | 1860 - 1876 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 5153.011 ms | 2363 - 2385 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 2647.479 ms | 1853 - 1865 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® SA7255P | 6484.61 ms | 1847 - 1856 MB | CPU | CenterPoint | TFLITE | float | Qualcomm® SA8295P | 3446.214 ms | 1808 - 1814 MB | CPU | CenterPoint | TFLITE | float | Snapdragon® 8 Elite Mobile | 2647.479 ms | 1853 - 1865 MB | CPU | CenterPoint | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 803.09 ms | 1981 - 1991 MB | CPU ## License * The license for the original implementation of CenterPoint can be found [here](https://github.com/tianweiy/CenterPoint/blob/master/LICENSE). ## Community * Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI. * For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).