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library_name: pytorch
license: other
tags:
- android
pipeline_tag: image-to-image
---

# NAFNet-DeNoise: Optimized for Qualcomm Devices
NAFNET is designed for lightweight real-time denoising of images.
This is based on the implementation of NAFNet-DeNoise found [here](https://github.com/megvii-research/NAFNet.git).
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/v0.59.0/src/qai_hub_models/models/nafnet_denoise) 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 |
|---|---|---|---|---|
| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/nafnet_denoise/releases/v0.59.0/nafnet_denoise-onnx-float.zip)
| ONNX | w8a16 | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/nafnet_denoise/releases/v0.59.0/nafnet_denoise-onnx-w8a16.zip)
| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/nafnet_denoise/releases/v0.59.0/nafnet_denoise-qnn_dlc-float.zip)
| QNN_DLC | w8a16 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/nafnet_denoise/releases/v0.59.0/nafnet_denoise-qnn_dlc-w8a16.zip)
| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/nafnet_denoise/releases/v0.59.0/nafnet_denoise-tflite-float.zip)
For more device-specific assets and performance metrics, visit **[NAFNet-DeNoise on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/nafnet_denoise)**.
### Option 2: Export with Custom Configurations
Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/nafnet_denoise) 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 [NAFNet-DeNoise on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.59.0/src/qai_hub_models/models/nafnet_denoise) for usage instructions.
## Model Details
**Model Type:** Model_use_case.image_editing
**Model Stats:**
- Model checkpoint: NAFNet-SIDD-width64
- Input resolution: 256x256
- Number of parameters: 115.98M
- Model size (float): 463.93 MB
## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| NAFNet-DeNoise | ONNX | float | Snapdragon® X2 Elite | 14.988 ms | 4 - 4 MB | NPU
| NAFNet-DeNoise | ONNX | float | Snapdragon® X Elite | 33.919 ms | 228 - 228 MB | NPU
| NAFNet-DeNoise | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 27.636 ms | 2 - 851 MB | NPU
| NAFNet-DeNoise | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 61.4 ms | 3 - 722 MB | NPU
| NAFNet-DeNoise | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 34.841 ms | 0 - 258 MB | NPU
| NAFNet-DeNoise | ONNX | float | Qualcomm® QCS8450 | 61.4 ms | 3 - 722 MB | NPU
| NAFNet-DeNoise | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 43.039 ms | 2 - 5 MB | NPU
| NAFNet-DeNoise | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 33.919 ms | 228 - 228 MB | NPU
| NAFNet-DeNoise | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 19.714 ms | 2 - 498 MB | NPU
| NAFNet-DeNoise | ONNX | float | Snapdragon® 8 Elite Mobile | 19.714 ms | 2 - 498 MB | NPU
| NAFNet-DeNoise | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 14.475 ms | 0 - 535 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Snapdragon® X2 Elite | 14.577 ms | 1 - 1 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Snapdragon® X Elite | 33.188 ms | 120 - 120 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Snapdragon® 8 Gen 3 Mobile | 24.378 ms | 1 - 697 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Snapdragon® 8 Gen 1 Mobile | 53.664 ms | 2 - 710 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 144.383 ms | 1 - 4 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 32.729 ms | 0 - 130 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Qualcomm® QCS8450 | 53.664 ms | 2 - 710 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 32.725 ms | 1 - 4 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 33.188 ms | 120 - 120 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 19.222 ms | 1 - 566 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Snapdragon® 8 Elite Mobile | 19.222 ms | 1 - 566 MB | NPU
| NAFNet-DeNoise | ONNX | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 13.027 ms | 0 - 684 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Snapdragon® X2 Elite | 15.695 ms | 1 - 1 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Snapdragon® X Elite | 35.856 ms | 1 - 1 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 28.778 ms | 1 - 892 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 60.876 ms | 0 - 728 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8275 | 136.431 ms | 1 - 546 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 38.207 ms | 1 - 19 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® SA8775P | 43.544 ms | 1 - 559 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® SA8650P | 43.544 ms | 1 - 559 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® SA8255P | 43.544 ms | 1 - 559 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® QCS8450 | 60.876 ms | 0 - 728 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 48.478 ms | 1 - 4 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 35.856 ms | 1 - 1 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 20.539 ms | 1 - 542 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® SA7255P | 136.431 ms | 1 - 546 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Qualcomm® SA8295P | 48.018 ms | 1 - 399 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 20.539 ms | 1 - 542 MB | NPU
| NAFNet-DeNoise | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 14.726 ms | 0 - 621 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Snapdragon® X2 Elite | 15.063 ms | 0 - 0 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Snapdragon® X Elite | 33.124 ms | 0 - 0 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Snapdragon® 8 Gen 3 Mobile | 22.473 ms | 0 - 687 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Snapdragon® 8 Gen 1 Mobile | 57.732 ms | 0 - 719 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS6490 | 141.888 ms | 0 - 3 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8275 | 65.077 ms | 1 - 576 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 31.599 ms | 0 - 3 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® SA8775P | 31.638 ms | 1 - 576 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® SA8650P | 31.638 ms | 1 - 576 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® SA8255P | 31.638 ms | 1 - 576 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® QCS8450 | 57.732 ms | 0 - 719 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-9075 | 32.191 ms | 2 - 5 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ IQ-X7181 | 33.124 ms | 0 - 0 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-6690 | 354.702 ms | 0 - 954 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-7790 | 39.185 ms | 0 - 813 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® Dragonwing™ Q-8750 | 21.24 ms | 0 - 584 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® SA7255P | 65.077 ms | 1 - 576 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Qualcomm® SA8295P | 40.513 ms | 0 - 574 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Snapdragon® 8 Elite Mobile | 21.24 ms | 0 - 584 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Snapdragon® 8 Elite Gen 5 Mobile | 13.267 ms | 0 - 706 MB | NPU
| NAFNet-DeNoise | QNN_DLC | w8a16 | Snapdragon® 7 Gen 4 Mobile | 39.185 ms | 0 - 813 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 28.866 ms | 1 - 1125 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 64.27 ms | 1 - 962 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® Dragonwing™ QCS8275 | 136.679 ms | 1 - 765 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 38.107 ms | 1 - 4 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® SA8775P | 43.637 ms | 1 - 777 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® SA8650P | 43.637 ms | 1 - 777 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® SA8255P | 43.637 ms | 1 - 777 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® QCS8450 | 64.27 ms | 1 - 962 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 44.226 ms | 1 - 233 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 20.402 ms | 1 - 764 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® SA7255P | 136.679 ms | 1 - 765 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Qualcomm® SA8295P | 50.795 ms | 1 - 629 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Snapdragon® 8 Elite Mobile | 20.402 ms | 1 - 764 MB | NPU
| NAFNet-DeNoise | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 14.787 ms | 1 - 849 MB | NPU
## License
* The license for the original implementation of NAFNet-DeNoise can be found
[here](https://github.com/megvii-research/NAFNet/blob/main/LICENSE).
## References
* [Simple Baselines for Image Restoration](https://arxiv.org/abs/2204.04676)
* [Source Model Implementation](https://github.com/megvii-research/NAFNet.git)
## 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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