v0.49.1
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.49.1 for changelog.
README.md
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PSPNet (Pyramid Scene Parsing Network) is a semantic segmentation model that captures global context information by applying pyramid pooling modules. It is designed to improve scene understanding by aggregating contextual features at multiple scales.
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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/
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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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| Runtime | Precision | Chipset | SDK Versions | Download |
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| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.
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| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.
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| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.
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| QNN_DLC | w8a8 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.
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| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.
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| TFLITE | w8a8 | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.
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For more device-specific assets and performance metrics, visit **[PSPNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/pspnet)**.
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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/
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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 [PSPNet on GitHub](https://github.com/qualcomm/ai-hub-models/
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## Model Details
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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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| PSPNet | ONNX | float | Snapdragon®
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| PSPNet | ONNX | float | Snapdragon®
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| PSPNet | ONNX | float | Snapdragon®
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| PSPNet | ONNX | float |
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| PSPNet | ONNX | float |
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| PSPNet | ONNX | float | Snapdragon® 8 Elite
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| PSPNet | ONNX | w8a8 | Snapdragon®
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| PSPNet | ONNX | w8a8 | Snapdragon®
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| PSPNet | ONNX | w8a8 | Snapdragon®
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| PSPNet | ONNX | w8a8 |
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| PSPNet | ONNX | w8a8 | Qualcomm®
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| PSPNet | ONNX | w8a8 | Qualcomm®
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| PSPNet | ONNX | w8a8 | Qualcomm®
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| PSPNet | ONNX | w8a8 |
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| PSPNet | ONNX | w8a8 | Snapdragon®
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| PSPNet | ONNX | w8a8 | Snapdragon®
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| PSPNet | QNN_DLC | float | Snapdragon®
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| PSPNet | QNN_DLC | float | Snapdragon®
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| PSPNet | QNN_DLC | float | Snapdragon®
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| PSPNet | QNN_DLC | float |
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| PSPNet | QNN_DLC | float | Qualcomm®
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| PSPNet | QNN_DLC | float | Qualcomm®
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| PSPNet | QNN_DLC | float |
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| PSPNet | QNN_DLC | float | Snapdragon® 8 Elite
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| PSPNet | QNN_DLC | w8a8 | Snapdragon®
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| PSPNet | QNN_DLC | w8a8 | Snapdragon®
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| PSPNet | QNN_DLC | w8a8 | Snapdragon®
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| PSPNet | QNN_DLC | w8a8 |
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| PSPNet | QNN_DLC | w8a8 | Qualcomm®
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| PSPNet | QNN_DLC | w8a8 | Qualcomm®
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| PSPNet | QNN_DLC | w8a8 | Qualcomm®
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| PSPNet | QNN_DLC | w8a8 |
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| PSPNet | QNN_DLC | w8a8 | Snapdragon®
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| PSPNet | QNN_DLC | w8a8 | Snapdragon®
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| PSPNet | TFLITE | float | Snapdragon® 8 Gen
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| PSPNet | TFLITE | float |
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| PSPNet | TFLITE | float | Qualcomm®
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| PSPNet | TFLITE | float | Qualcomm®
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| PSPNet | TFLITE | float |
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| PSPNet | TFLITE | float | Snapdragon® 8 Elite
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| PSPNet | TFLITE | w8a8 | Snapdragon® 8 Gen
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| PSPNet | TFLITE | w8a8 |
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| PSPNet | TFLITE | w8a8 | Qualcomm®
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| PSPNet | TFLITE | w8a8 | Qualcomm®
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| PSPNet | TFLITE | w8a8 | Qualcomm®
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| PSPNet | TFLITE | w8a8 |
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| PSPNet | TFLITE | w8a8 | Snapdragon®
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| PSPNet | TFLITE | w8a8 | Snapdragon®
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## License
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* The license for the original implementation of PSPNet can be found
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PSPNet (Pyramid Scene Parsing Network) is a semantic segmentation model that captures global context information by applying pyramid pooling modules. It is designed to improve scene understanding by aggregating contextual features at multiple scales.
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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/tree/v0.49.1/qai_hub_models/models/pspnet) 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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| Runtime | Precision | Chipset | SDK Versions | Download |
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|---|---|---|---|---|
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| ONNX | float | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.49.1/pspnet-onnx-float.zip)
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| ONNX | w8a8 | Universal | QAIRT 2.42, ONNX Runtime 1.24.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.49.1/pspnet-onnx-w8a8.zip)
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| QNN_DLC | float | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.49.1/pspnet-qnn_dlc-float.zip)
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| QNN_DLC | w8a8 | Universal | QAIRT 2.43 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.49.1/pspnet-qnn_dlc-w8a8.zip)
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| TFLITE | float | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.49.1/pspnet-tflite-float.zip)
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| TFLITE | w8a8 | Universal | QAIRT 2.43, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pspnet/releases/v0.49.1/pspnet-tflite-w8a8.zip)
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For more device-specific assets and performance metrics, visit **[PSPNet on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/pspnet)**.
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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/tree/v0.49.1/qai_hub_models/models/pspnet) 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 [PSPNet on GitHub](https://github.com/qualcomm/ai-hub-models/tree/v0.49.1/qai_hub_models/models/pspnet) for usage instructions.
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## Model Details
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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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| PSPNet | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 323.654 ms | 233 - 1001 MB | NPU
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| PSPNet | ONNX | float | Snapdragon® X2 Elite | 427.869 ms | 266 - 266 MB | NPU
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| PSPNet | ONNX | float | Snapdragon® X Elite | 695.005 ms | 529 - 529 MB | NPU
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| PSPNet | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 506.756 ms | 136 - 1053 MB | NPU
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| PSPNet | ONNX | float | Qualcomm® QCS8550 (Proxy) | 602.812 ms | 195 - 199 MB | NPU
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| PSPNet | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 333.199 ms | 246 - 1003 MB | NPU
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| PSPNet | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 16.884 ms | 72 - 340 MB | NPU
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| PSPNet | ONNX | w8a8 | Snapdragon® X2 Elite | 15.251 ms | 131 - 131 MB | NPU
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| PSPNet | ONNX | w8a8 | Snapdragon® X Elite | 28.661 ms | 133 - 133 MB | NPU
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| PSPNet | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 22.334 ms | 72 - 494 MB | NPU
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| PSPNet | ONNX | w8a8 | Qualcomm® QCS6490 | 3318.926 ms | 196 - 276 MB | CPU
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| PSPNet | ONNX | w8a8 | Qualcomm® QCS8550 (Proxy) | 29.465 ms | 64 - 576 MB | NPU
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| PSPNet | ONNX | w8a8 | Qualcomm® QCS9075 | 34.444 ms | 70 - 74 MB | NPU
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| PSPNet | ONNX | w8a8 | Qualcomm® QCM6690 | 3277.178 ms | 95 - 110 MB | CPU
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| PSPNet | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 19.038 ms | 72 - 343 MB | NPU
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| PSPNet | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 2589.577 ms | 50 - 62 MB | CPU
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| PSPNet | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 269.084 ms | 3 - 741 MB | NPU
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| PSPNet | QNN_DLC | float | Snapdragon® X2 Elite | 229.121 ms | 3 - 3 MB | NPU
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| PSPNet | QNN_DLC | float | Snapdragon® X Elite | 545.535 ms | 3 - 3 MB | NPU
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| PSPNet | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 623.685 ms | 0 - 874 MB | NPU
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| PSPNet | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 1863.358 ms | 2 - 722 MB | NPU
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| PSPNet | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 608.77 ms | 3 - 5 MB | NPU
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| PSPNet | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 1689.881 ms | 0 - 431 MB | NPU
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| PSPNet | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 301.937 ms | 0 - 718 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 16.214 ms | 1 - 239 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 14.344 ms | 1 - 1 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Snapdragon® X Elite | 26.117 ms | 1 - 1 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 20.679 ms | 1 - 365 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 63.897 ms | 1 - 263 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 27.013 ms | 0 - 9 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 31.865 ms | 0 - 34 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 36.677 ms | 1 - 358 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 18.068 ms | 1 - 234 MB | NPU
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| PSPNet | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 91.895 ms | 1 - 458 MB | NPU
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| PSPNet | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 326.397 ms | 128 - 965 MB | NPU
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| PSPNet | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 528.08 ms | 0 - 1049 MB | NPU
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| PSPNet | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 1688.514 ms | 124 - 958 MB | NPU
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| PSPNet | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 619.017 ms | 128 - 131 MB | NPU
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| PSPNet | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 1563.118 ms | 125 - 698 MB | NPU
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| PSPNet | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 974.903 ms | 128 - 884 MB | NPU
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| PSPNet | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 17.665 ms | 32 - 284 MB | NPU
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| PSPNet | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 26.587 ms | 30 - 427 MB | NPU
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| PSPNet | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 74.606 ms | 32 - 304 MB | NPU
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| PSPNet | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 34.862 ms | 32 - 35 MB | NPU
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| PSPNet | TFLITE | w8a8 | Qualcomm® QCS9075 | 38.16 ms | 32 - 131 MB | NPU
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| PSPNet | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 55.328 ms | 32 - 417 MB | NPU
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| PSPNet | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 22.633 ms | 32 - 286 MB | NPU
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| PSPNet | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 356.021 ms | 384 - 904 MB | NPU
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## License
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* The license for the original implementation of PSPNet can be found
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