Hugging Face's logo

qualcomm
/
NAFNet-DeNoise

Image-to-Image
PyTorch
android
Model card Files
xet
 Community

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. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up 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 2.42, ONNX Runtime 1.25.0 Download
ONNX w8a16 Universal QAIRT 2.42, ONNX Runtime 1.25.0 Download
QNN_DLC float Universal QAIRT 2.45 Download
QNN_DLC w8a16 Universal QAIRT 2.45 Download
TFLITE float Universal QAIRT 2.45 Download

For more device-specific assets and performance metrics, visit NAFNet-DeNoise on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models 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 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® 8 Elite Gen 5 Mobile 15.267 ms 2 - 568 MB NPU
NAFNet-DeNoise ONNX float Snapdragon® X2 Elite 15.346 ms 180 - 180 MB NPU
NAFNet-DeNoise ONNX float Snapdragon® X Elite 33.92 ms 227 - 227 MB NPU
NAFNet-DeNoise ONNX float Snapdragon® 8 Gen 3 Mobile 27.542 ms 2 - 879 MB NPU
NAFNet-DeNoise ONNX float Qualcomm® QCS8550 (Proxy) 34.799 ms 0 - 273 MB NPU
NAFNet-DeNoise ONNX float Snapdragon® 8 Elite For Galaxy Mobile 20.561 ms 2 - 508 MB NPU
NAFNet-DeNoise ONNX float Qualcomm® QCS9075 46.169 ms 2 - 47 MB NPU
NAFNet-DeNoise ONNX float Qualcomm® QCS8750 20.561 ms 2 - 508 MB NPU
NAFNet-DeNoise ONNX float Qualcomm® QCS7181 33.92 ms 227 - 227 MB NPU
NAFNet-DeNoise ONNX w8a16 Snapdragon® 8 Elite Gen 5 Mobile 15.899 ms 1 - 715 MB NPU
NAFNet-DeNoise ONNX w8a16 Snapdragon® X Elite 40.406 ms 148 - 148 MB NPU
NAFNet-DeNoise ONNX w8a16 Snapdragon® 8 Gen 3 Mobile 28.566 ms 1 - 737 MB NPU
NAFNet-DeNoise ONNX w8a16 Qualcomm® QCS6490 4731.65 ms 397 - 425 MB CPU
NAFNet-DeNoise ONNX w8a16 Qualcomm® QCS8550 (Proxy) 39.492 ms 0 - 501 MB NPU
NAFNet-DeNoise ONNX w8a16 Qualcomm® QCM6690 2302.284 ms 397 - 420 MB CPU
NAFNet-DeNoise ONNX w8a16 Snapdragon® 7 Gen 4 Mobile 2033.157 ms 375 - 396 MB CPU
NAFNet-DeNoise ONNX w8a16 Snapdragon® 8 Elite For Galaxy Mobile 22.928 ms 1 - 583 MB NPU
NAFNet-DeNoise ONNX w8a16 Qualcomm® QCS9075 51.312 ms 1 - 46 MB NPU
NAFNet-DeNoise ONNX w8a16 Qualcomm® QCS7790 2033.157 ms 375 - 396 MB CPU
NAFNet-DeNoise ONNX w8a16 Qualcomm® QCS8750 22.928 ms 1 - 583 MB NPU
NAFNet-DeNoise ONNX w8a16 Qualcomm® QCS7181 40.406 ms 148 - 148 MB NPU
NAFNet-DeNoise QNN_DLC float Snapdragon® 8 Elite Gen 5 Mobile 14.647 ms 1 - 614 MB NPU
NAFNet-DeNoise QNN_DLC float Snapdragon® X2 Elite 15.716 ms 1 - 1 MB NPU
NAFNet-DeNoise QNN_DLC float Snapdragon® X Elite 35.805 ms 1 - 1 MB NPU
NAFNet-DeNoise QNN_DLC float Snapdragon® 8 Gen 3 Mobile 28.197 ms 0 - 888 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® QCS8275 136.377 ms 1 - 545 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® QCS8550 (Proxy) 37.385 ms 1 - 564 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® SA8775P 43.49 ms 1 - 558 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® SA8650P 43.49 ms 1 - 558 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® SA8255P 43.49 ms 1 - 558 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® QCS8450 (Proxy) 61.64 ms 1 - 729 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® SA7255P 136.377 ms 1 - 545 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® SA8295P 47.971 ms 1 - 399 MB NPU
NAFNet-DeNoise QNN_DLC float Snapdragon® 8 Elite For Galaxy Mobile 20.0 ms 1 - 543 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® QCS9075 46.091 ms 1 - 4 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® QCS8750 20.0 ms 1 - 543 MB NPU
NAFNet-DeNoise QNN_DLC float Qualcomm® QCS7181 35.805 ms 1 - 1 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Snapdragon® 8 Elite Gen 5 Mobile 13.139 ms 0 - 699 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Snapdragon® X2 Elite 15.128 ms 0 - 0 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Snapdragon® X Elite 33.213 ms 0 - 0 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Snapdragon® 8 Gen 3 Mobile 22.718 ms 0 - 688 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® QCS8275 65.079 ms 1 - 577 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® QCS8550 (Proxy) 31.918 ms 0 - 211 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® SA8775P 31.626 ms 1 - 577 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® SA8650P 31.626 ms 1 - 577 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® SA8255P 31.626 ms 1 - 577 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® QCM6690 367.326 ms 0 - 953 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® SA7255P 65.079 ms 1 - 577 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Snapdragon® 7 Gen 4 Mobile 39.568 ms 0 - 816 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Snapdragon® 8 Elite For Galaxy Mobile 20.863 ms 0 - 584 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® QCS9075 45.973 ms 0 - 3 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® QCS7790 39.568 ms 0 - 816 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® QCS8750 20.863 ms 0 - 584 MB NPU
NAFNet-DeNoise QNN_DLC w8a16 Qualcomm® QCS7181 33.213 ms 0 - 0 MB NPU
NAFNet-DeNoise TFLITE float Snapdragon® 8 Elite Gen 5 Mobile 14.822 ms 1 - 841 MB NPU
NAFNet-DeNoise TFLITE float Snapdragon® 8 Gen 3 Mobile 28.805 ms 1 - 1128 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® QCS8275 136.992 ms 1 - 765 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® QCS8550 (Proxy) 36.384 ms 1 - 4 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® SA8775P 43.655 ms 1 - 777 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® SA8650P 43.655 ms 1 - 777 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® SA8255P 43.655 ms 1 - 777 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® QCS8450 (Proxy) 64.25 ms 1 - 962 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® SA7255P 136.992 ms 1 - 765 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® SA8295P 50.824 ms 1 - 629 MB NPU
NAFNet-DeNoise TFLITE float Snapdragon® 8 Elite For Galaxy Mobile 20.348 ms 1 - 764 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® QCS9075 46.141 ms 1 - 232 MB NPU
NAFNet-DeNoise TFLITE float Qualcomm® QCS8750 20.348 ms 1 - 764 MB NPU

License

  • The license for the original implementation of NAFNet-DeNoise can be found here.

References

Community

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
Image-to-Image
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Paper for qualcomm/NAFNet-DeNoise