v0.53.0
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.53.0 for changelog.
- LICENSE +1 -0
- README.md +148 -0
- release_assets.json +29 -0
LICENSE
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The license of the original trained model can be found at https://github.com/thohemp/6DRepNet/blob/master/LICENSE.
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README.md
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---
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library_name: pytorch
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license: other
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tags:
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- real_time
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- android
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pipeline_tag: keypoint-detection
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---
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# SixDRepNet: Optimized for Qualcomm Devices
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6DRepNet predicts head pose (pitch, yaw, roll) from a face image using a RepVGG-B1g2 backbone and a continuous 6D rotation representation, achieving robust and accurate head pose estimation.
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This is based on the implementation of SixDRepNet found [here](https://github.com/thohemp/6DRepNet).
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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/main/src/qai_hub_models/models/sixd_repnet) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
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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.
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## Getting Started
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There are two ways to deploy this model on your device:
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### Option 1: Download Pre-Exported Models
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Below are pre-exported model assets ready for deployment.
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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.3 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/sixd_repnet/releases/v0.53.0/sixd_repnet-onnx-float.zip)
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/sixd_repnet/releases/v0.53.0/sixd_repnet-qnn_dlc-float.zip)
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/sixd_repnet/releases/v0.53.0/sixd_repnet-tflite-float.zip)
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For more device-specific assets and performance metrics, visit **[SixDRepNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/sixd_repnet)**.
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### Option 2: Export with Custom Configurations
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Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/sixd_repnet) Python library to compile and export the model with your own:
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- Custom weights (e.g., fine-tuned checkpoints)
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- Custom input shapes
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- Target device and runtime configurations
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This option is ideal if you need to customize the model beyond the default configuration provided here.
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See our repository for [SixDRepNet on GitHub](https://github.com/qualcomm/ai-hub-models/blob/main/src/qai_hub_models/models/sixd_repnet) for usage instructions.
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## Model Details
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**Model Type:** Model_use_case.pose_estimation
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**Model Stats:**
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- Input resolution: 224x224
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- Number of parameters: 15.3M
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- Model size (float): 58.4 MB
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## Performance Summary
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| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
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|---|---|---|---|---|---|---
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| face_detector | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.483 ms | 0 - 166 MB | NPU
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| face_detector | ONNX | float | Snapdragon® 8 Elite Mobile | 1.863 ms | 3 - 166 MB | NPU
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| face_detector | ONNX | float | Snapdragon® X2 Elite | 1.581 ms | 7 - 7 MB | NPU
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| face_detector | ONNX | float | Snapdragon® X Elite | 3.803 ms | 7 - 7 MB | NPU
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| face_detector | ONNX | float | Snapdragon® X Elite | 3.803 ms | 7 - 7 MB | NPU
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| face_detector | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 2.201 ms | 3 - 169 MB | NPU
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| face_detector | ONNX | float | Qualcomm® QCS8550 (Proxy) | 3.469 ms | 0 - 4 MB | NPU
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| face_detector | ONNX | float | Qualcomm® QCS9075 | 5.366 ms | 4 - 12 MB | NPU
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| face_detector | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.863 ms | 3 - 166 MB | NPU
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| face_detector | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.42 ms | 5 - 159 MB | NPU
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| face_detector | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 6.896 ms | 0 - 150 MB | NPU
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| face_detector | QNN_DLC | float | Snapdragon® X2 Elite | 5.876 ms | 5 - 5 MB | NPU
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| face_detector | QNN_DLC | float | Snapdragon® X Elite | 16.475 ms | 5 - 5 MB | NPU
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| face_detector | QNN_DLC | float | Snapdragon® X Elite | 16.475 ms | 5 - 5 MB | NPU
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| face_detector | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 9.278 ms | 5 - 173 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 28.312 ms | 1 - 151 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 15.67 ms | 5 - 8 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® SA8775P | 16.54 ms | 1 - 153 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® SA8775P | 16.54 ms | 1 - 153 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® SA8775P | 16.54 ms | 1 - 153 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® QCS9075 | 19.498 ms | 5 - 12 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 24.733 ms | 5 - 179 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® SA7255P | 28.312 ms | 1 - 151 MB | NPU
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| face_detector | QNN_DLC | float | Qualcomm® SA8295P | 20.592 ms | 0 - 150 MB | NPU
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| face_detector | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 6.896 ms | 0 - 150 MB | NPU
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| face_detector | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 5.482 ms | 1 - 155 MB | NPU
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| face_detector | TFLITE | float | Snapdragon® 8 Elite Mobile | 6.923 ms | 0 - 150 MB | NPU
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| face_detector | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 9.272 ms | 1 - 171 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 28.26 ms | 1 - 150 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 15.666 ms | 1 - 3 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® SA8775P | 16.531 ms | 1 - 152 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® SA8775P | 16.531 ms | 1 - 152 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® SA8775P | 16.531 ms | 1 - 152 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® QCS9075 | 19.66 ms | 1 - 10 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 24.453 ms | 1 - 171 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® SA7255P | 28.26 ms | 1 - 150 MB | NPU
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| face_detector | TFLITE | float | Qualcomm® SA8295P | 20.653 ms | 1 - 152 MB | NPU
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| face_detector | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 6.923 ms | 0 - 150 MB | NPU
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| pose_estimator | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.334 ms | 0 - 24 MB | NPU
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| pose_estimator | ONNX | float | Snapdragon® 8 Elite Mobile | 1.619 ms | 0 - 22 MB | NPU
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| pose_estimator | ONNX | float | Snapdragon® X2 Elite | 1.318 ms | 75 - 75 MB | NPU
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| pose_estimator | ONNX | float | Snapdragon® X Elite | 2.633 ms | 75 - 75 MB | NPU
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| pose_estimator | ONNX | float | Snapdragon® X Elite | 2.633 ms | 75 - 75 MB | NPU
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| pose_estimator | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 2.059 ms | 0 - 35 MB | NPU
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| pose_estimator | ONNX | float | Qualcomm® QCS8550 (Proxy) | 2.627 ms | 1 - 2 MB | NPU
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| pose_estimator | ONNX | float | Qualcomm® QCS9075 | 4.551 ms | 0 - 4 MB | NPU
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| pose_estimator | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.619 ms | 0 - 22 MB | NPU
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| pose_estimator | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.417 ms | 1 - 29 MB | NPU
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| pose_estimator | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 1.682 ms | 0 - 26 MB | NPU
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| pose_estimator | QNN_DLC | float | Snapdragon® X2 Elite | 1.487 ms | 1 - 1 MB | NPU
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| pose_estimator | QNN_DLC | float | Snapdragon® X Elite | 2.864 ms | 1 - 1 MB | NPU
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| pose_estimator | QNN_DLC | float | Snapdragon® X Elite | 2.864 ms | 1 - 1 MB | NPU
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| pose_estimator | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 2.235 ms | 1 - 40 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 17.816 ms | 1 - 24 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 2.782 ms | 1 - 2 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® SA8775P | 4.813 ms | 1 - 26 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® SA8775P | 4.813 ms | 1 - 26 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® SA8775P | 4.813 ms | 1 - 26 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® QCS9075 | 4.904 ms | 3 - 5 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 6.543 ms | 0 - 39 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® SA7255P | 17.816 ms | 1 - 24 MB | NPU
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| pose_estimator | QNN_DLC | float | Qualcomm® SA8295P | 5.398 ms | 1 - 23 MB | NPU
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| pose_estimator | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.682 ms | 0 - 26 MB | NPU
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| pose_estimator | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 1.374 ms | 0 - 28 MB | NPU
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| pose_estimator | TFLITE | float | Snapdragon® 8 Elite Mobile | 1.701 ms | 0 - 30 MB | NPU
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| pose_estimator | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 2.265 ms | 0 - 46 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 17.398 ms | 0 - 26 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 2.849 ms | 0 - 3 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® SA8775P | 4.813 ms | 0 - 27 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® SA8775P | 4.813 ms | 0 - 27 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® SA8775P | 4.813 ms | 0 - 27 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® QCS9075 | 4.74 ms | 0 - 78 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 6.502 ms | 0 - 43 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® SA7255P | 17.398 ms | 0 - 26 MB | NPU
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| pose_estimator | TFLITE | float | Qualcomm® SA8295P | 5.349 ms | 0 - 28 MB | NPU
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| pose_estimator | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 1.701 ms | 0 - 30 MB | NPU
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## License
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* The license for the original implementation of SixDRepNet can be found
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[here](https://github.com/thohemp/6DRepNet/blob/master/LICENSE).
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## References
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* [6D Rotation Representation for Unconstrained Head Pose Estimation](https://arxiv.org/abs/2109.10948)
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* [Source Model Implementation](https://github.com/thohemp/6DRepNet)
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## Community
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* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
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* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).
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release_assets.json
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{
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"version": "0.53.0",
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"precisions": {
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"float": {
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"universal_assets": {
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"tflite": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327",
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"litert": "1.4.3"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/sixd_repnet/releases/v0.53.0/sixd_repnet-tflite-float.zip"
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},
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"qnn_dlc": {
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"tool_versions": {
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"qairt": "2.45.0.260326154327"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/sixd_repnet/releases/v0.53.0/sixd_repnet-qnn_dlc-float.zip"
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},
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"onnx": {
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"tool_versions": {
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"qairt": "2.42.0.251225135753_193295",
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"onnx_runtime": "1.24.3"
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},
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"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/sixd_repnet/releases/v0.53.0/sixd_repnet-onnx-float.zip"
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}
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}
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}
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}
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}
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