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README.md
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| Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| HRNetPose | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 2.
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| HRNetPose | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 2.
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| HRNetPose | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX |
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| HRNetPose | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 2.
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| HRNetPose | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 2.
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| HRNetPose | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 2.
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| HRNetPose | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.
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| HRNetPose | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 2.036 ms | 1 -
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| HRNetPose | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 2.
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| HRNetPose | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 2.801 ms | 0 -
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| HRNetPose | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 2.
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| HRNetPose | SA7255P ADP | SA7255P | TFLITE | 103.
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| HRNetPose | SA7255P ADP | SA7255P | QNN | 103.
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| HRNetPose | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 2.
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| HRNetPose | SA8255 (Proxy) | SA8255P Proxy | QNN | 2.
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| HRNetPose | SA8295P ADP | SA8295P | TFLITE | 4.
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| HRNetPose | SA8295P ADP | SA8295P | QNN |
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| HRNetPose | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 2.
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| HRNetPose | SA8650 (Proxy) | SA8650P Proxy | QNN | 2.
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| HRNetPose | SA8775P ADP | SA8775P | TFLITE | 5.
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| HRNetPose | SA8775P ADP | SA8775P | QNN | 5.
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| HRNetPose | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 3.
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| HRNetPose | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 3.
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| HRNetPose | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 2.
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| HRNetPose | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 2.
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## Installation
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This model can be installed as a Python package via pip.
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```bash
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pip install "qai-hub-models[
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```
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## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
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torch_model = Model.from_pretrained()
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# Device
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device = hub.Device("Samsung Galaxy
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# Trace model
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input_shape = torch_model.get_input_spec()
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## License
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* The license for the original implementation of HRNetPose can be found
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* The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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| Model | Device | Chipset | Target Runtime | Inference Time (ms) | Peak Memory Range (MB) | Precision | Primary Compute Unit | Target Model
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| HRNetPose | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | TFLITE | 2.808 ms | 0 - 59 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | QNN | 2.902 ms | 0 - 32 MB | FP16 | NPU | [HRNetPose.so](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.so) |
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| HRNetPose | Samsung Galaxy S23 | Snapdragon® 8 Gen 2 | ONNX | 2.906 ms | 0 - 137 MB | FP16 | NPU | [HRNetPose.onnx](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.onnx) |
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| HRNetPose | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | TFLITE | 2.048 ms | 0 - 41 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 2.129 ms | 0 - 35 MB | FP16 | NPU | [HRNetPose.so](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.so) |
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| HRNetPose | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | ONNX | 2.211 ms | 0 - 70 MB | FP16 | NPU | [HRNetPose.onnx](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.onnx) |
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| HRNetPose | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | TFLITE | 1.968 ms | 0 - 38 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 2.036 ms | 1 - 37 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | ONNX | 2.155 ms | 0 - 49 MB | FP16 | NPU | [HRNetPose.onnx](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.onnx) |
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| HRNetPose | QCS8550 (Proxy) | QCS8550 Proxy | TFLITE | 2.801 ms | 0 - 39 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 2.733 ms | 1 - 2 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | SA7255P ADP | SA7255P | TFLITE | 103.032 ms | 0 - 34 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | SA7255P ADP | SA7255P | QNN | 103.017 ms | 1 - 10 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | SA8255 (Proxy) | SA8255P Proxy | TFLITE | 2.805 ms | 0 - 39 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | SA8255 (Proxy) | SA8255P Proxy | QNN | 2.733 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | SA8295P ADP | SA8295P | TFLITE | 4.632 ms | 0 - 31 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | SA8295P ADP | SA8295P | QNN | 4.716 ms | 1 - 15 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | SA8650 (Proxy) | SA8650P Proxy | TFLITE | 2.853 ms | 0 - 59 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | SA8650 (Proxy) | SA8650P Proxy | QNN | 2.739 ms | 1 - 3 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | SA8775P ADP | SA8775P | TFLITE | 5.47 ms | 0 - 34 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | SA8775P ADP | SA8775P | QNN | 5.442 ms | 1 - 10 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | QCS8450 (Proxy) | QCS8450 Proxy | TFLITE | 3.772 ms | 0 - 33 MB | FP16 | NPU | [HRNetPose.tflite](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.tflite) |
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| HRNetPose | QCS8450 (Proxy) | QCS8450 Proxy | QNN | 3.786 ms | 1 - 29 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 2.957 ms | 1 - 1 MB | FP16 | NPU | Use Export Script |
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| HRNetPose | Snapdragon X Elite CRD | Snapdragon® X Elite | ONNX | 2.937 ms | 57 - 57 MB | FP16 | NPU | [HRNetPose.onnx](https://huggingface.co/qualcomm/HRNetPose/blob/main/HRNetPose.onnx) |
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## Installation
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Install the package via pip:
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```bash
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pip install "qai-hub-models[hrnet-pose]"
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```
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## Configure Qualcomm® AI Hub to run this model on a cloud-hosted device
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Sign-in to [Qualcomm® AI Hub](https://app.aihub.qualcomm.com/) with your
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torch_model = Model.from_pretrained()
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# Device
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device = hub.Device("Samsung Galaxy S24")
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# Trace model
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input_shape = torch_model.get_input_spec()
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## License
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* The license for the original implementation of HRNetPose can be found
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[here](https://github.com/quic/aimet-model-zoo/blob/develop/LICENSE.pdf).
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* The license for the compiled assets for on-device deployment can be found [here](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/Qualcomm+AI+Hub+Proprietary+License.pdf)
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