Objects as Points
Paper
•
1904.07850
•
Published
CenterNet-3D: Optimized for Qualcomm Devices
CenterNet is a machine learning model for generating a birds eye view represenation from the sensors(cameras) mounted on a vehicle.
This is based on the implementation of CenterNet-3D 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® X Elite | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Gen 3 Mobile | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS8550 (Proxy) | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS9075 | QAIRT 2.37, ONNX Runtime 1.23.0 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® X Elite | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Gen 3 Mobile | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8275 (Proxy) | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8550 (Proxy) | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® SA8775P | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite For Galaxy Mobile | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite Gen 5 Mobile | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® SA7255P | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® SA8295P | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS9075 | QAIRT 2.42 | Download |
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8450 (Proxy) | QAIRT 2.42 | Download |
For more device-specific assets and performance metrics, visit CenterNet-3D 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-3D on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.driver_assistance
Model Stats:
- Model checkpoint: ddd_3dop.pth
- Input resolution: 1 x 3 x 384 x 1280
- Number of parameters: 20.6M
- Model size: 79 MB
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| CenterNet-3D | PRECOMPILED_QNN_ONNX | float | Snapdragon® X Elite | 858.199 ms | 61 - 61 MB | NPU |
| CenterNet-3D | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Gen 3 Mobile | 694.92 ms | 9 - 16 MB | NPU |
| CenterNet-3D | PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS8550 (Proxy) | 890.935 ms | 1 - 77 MB | NPU |
| CenterNet-3D | PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS9075 | 887.98 ms | 6 - 14 MB | NPU |
| CenterNet-3D | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 522.696 ms | 3 - 15 MB | NPU |
| CenterNet-3D | PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 503.415 ms | 8 - 18 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Snapdragon® X Elite | 916.937 ms | 6 - 6 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Gen 3 Mobile | 697.873 ms | 6 - 14 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8275 (Proxy) | 1410.696 ms | 0 - 9 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8550 (Proxy) | 935.042 ms | 6 - 7 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Qualcomm® SA8775P | 958.249 ms | 1 - 10 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Qualcomm® QCS9075 | 934.178 ms | 6 - 15 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Qualcomm® QCS8450 (Proxy) | 1016.999 ms | 6 - 16 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Qualcomm® SA7255P | 1410.696 ms | 0 - 9 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Qualcomm® SA8295P | 1051.337 ms | 0 - 6 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite For Galaxy Mobile | 570.565 ms | 0 - 9 MB | NPU |
| CenterNet-3D | QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite Gen 5 Mobile | 508.172 ms | 6 - 15 MB | NPU |
License
- The license for the original implementation of CenterNet-3D can be found [here](https://github.com/xingyizhou/CenterNet/blob/master/LICENSE https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf).
References
Community
- Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
- For questions or feedback please reach out to us.
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support