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---
library_name: pytorch
license: other
tags:
- android
pipeline_tag: other
---
# 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](https://github.com/xingyizhou/CenterNet).
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/centernet_3d) 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 |
|---|---|---|---|---|
| PRECOMPILED_QNN_ONNX | float | Snapdragon® X Elite | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-precompiled_qnn_onnx-float-qualcomm_snapdragon_x_elite.zip)
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Gen 3 Mobile | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-precompiled_qnn_onnx-float-qualcomm_snapdragon_8gen3.zip)
| PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS8550 (Proxy) | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-precompiled_qnn_onnx-float-qualcomm_qcs8550_proxy.zip)
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-precompiled_qnn_onnx-float-qualcomm_snapdragon_8_elite_for_galaxy.zip)
| PRECOMPILED_QNN_ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-precompiled_qnn_onnx-float-qualcomm_snapdragon_8_elite_gen5.zip)
| PRECOMPILED_QNN_ONNX | float | Qualcomm® QCS9075 | QAIRT 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-precompiled_qnn_onnx-float-qualcomm_qcs9075.zip)
| QNN_CONTEXT_BINARY | float | Snapdragon® X Elite | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_snapdragon_x_elite.zip)
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Gen 3 Mobile | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_snapdragon_8gen3.zip)
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8275 (Proxy) | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_qcs8275_proxy.zip)
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8550 (Proxy) | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_qcs8550_proxy.zip)
| QNN_CONTEXT_BINARY | float | Qualcomm® SA8775P | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_sa8775p.zip)
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite For Galaxy Mobile | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_snapdragon_8_elite_for_galaxy.zip)
| QNN_CONTEXT_BINARY | float | Snapdragon® 8 Elite Gen 5 Mobile | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_snapdragon_8_elite_gen5.zip)
| QNN_CONTEXT_BINARY | float | Qualcomm® SA7255P | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_sa7255p.zip)
| QNN_CONTEXT_BINARY | float | Qualcomm® SA8295P | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_sa8295p.zip)
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS9075 | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_qcs9075.zip)
| QNN_CONTEXT_BINARY | float | Qualcomm® QCS8450 (Proxy) | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/centernet_3d/releases/v0.46.0/centernet_3d-qnn_context_binary-float-qualcomm_qcs8450_proxy.zip)
For more device-specific assets and performance metrics, visit **[CenterNet-3D on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/centernet_3d)**.
### Option 2: Export with Custom Configurations
Use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/centernet_3d) 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](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/centernet_3d) 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
* [Objects as Points](https://arxiv.org/abs/1904.07850)
* [Source Model Implementation](https://github.com/xingyizhou/CenterNet)
## 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).
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