DnCNN: Optimized for Qualcomm Devices
DnCNN is a 17-layer denoising convolutional neural network that uses residual learning to remove Gaussian noise (sigma=25) from grayscale images. The network predicts the noise residual and subtracts it from the input to produce a clean image.
This is based on the implementation of DnCNN 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 2.50, ONNX Runtime 1.27.1 | Download |
| ONNX | w8a8 | Universal | QAIRT 2.50, ONNX Runtime 1.27.1 | Download |
| QNN_DLC | float | Universal | QAIRT 2.50 | Download |
| QNN_DLC | w8a8 | Universal | QAIRT 2.50 | Download |
| TFLITE | float | Universal | QAIRT 2.50 | Download |
| TFLITE | w8a8 | Universal | QAIRT 2.50 | Download |
For more device-specific assets and performance metrics, visit DnCNN 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 DnCNN on GitHub for usage instructions.
Model Details
Model Type: Model_use_case.image_editing
Model Stats:
- Input resolution: 256x256
- Model checkpoint: dncnn_25
- Model size (float): 2.12 MB
- Model size (w8a8): 581 KB
- Number of parameters: 555K
Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit |
|---|---|---|---|---|---|---|
| DnCNN | ONNX | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 3.176 ms | 0 - 137 MB | NPU |
| DnCNN | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 4.146 ms | 0 - 135 MB | NPU |
| DnCNN | ONNX | float | Snapdragon® X2 Elite | 4.004 ms | 1 - 1 MB | NPU |
| DnCNN | ONNX | float | Snapdragon® X Elite | 7.172 ms | 0 - 0 MB | NPU |
| DnCNN | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 5.157 ms | 1 - 170 MB | NPU |
| DnCNN | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 13.062 ms | 1 - 176 MB | NPU |
| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 16.066 ms | 1 - 5 MB | NPU |
| DnCNN | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.919 ms | 1 - 3 MB | NPU |
| DnCNN | ONNX | float | Qualcomm® QCS8450 | 13.062 ms | 1 - 176 MB | NPU |
| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 14.355 ms | 1 - 4 MB | NPU |
| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 7.172 ms | 0 - 0 MB | NPU |
| DnCNN | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 4.146 ms | 0 - 135 MB | NPU |
| DnCNN | ONNX | w8a8 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 0.81 ms | 0 - 35 MB | NPU |
| DnCNN | ONNX | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.212 ms | 0 - 34 MB | NPU |
| DnCNN | ONNX | w8a8 | Snapdragon® X2 Elite | 1.036 ms | 1 - 1 MB | NPU |
| DnCNN | ONNX | w8a8 | Snapdragon® X Elite | 1.872 ms | 0 - 0 MB | NPU |
| DnCNN | ONNX | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.327 ms | 0 - 52 MB | NPU |
| DnCNN | ONNX | w8a8 | Snapdragon® 8 Gen 1 Mobile | 2.39 ms | 0 - 58 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 7.84 ms | 0 - 3 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 2.196 ms | 0 - 4 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 1.793 ms | 0 - 2 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® QCS8450 | 2.39 ms | 0 - 58 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 1.893 ms | 0 - 3 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 1.872 ms | 0 - 0 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 38.886 ms | 0 - 141 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.281 ms | 0 - 139 MB | NPU |
| DnCNN | ONNX | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 1.212 ms | 0 - 34 MB | NPU |
| DnCNN | ONNX | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.281 ms | 0 - 139 MB | NPU |
| DnCNN | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 3.042 ms | 0 - 140 MB | NPU |
| DnCNN | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 4.04 ms | 0 - 136 MB | NPU |
| DnCNN | QNN_DLC | float | Snapdragon® X2 Elite | 4.182 ms | 0 - 0 MB | NPU |
| DnCNN | QNN_DLC | float | Snapdragon® X Elite | 7.29 ms | 0 - 0 MB | NPU |
| DnCNN | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 5.065 ms | 0 - 170 MB | NPU |
| DnCNN | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 12.988 ms | 0 - 174 MB | NPU |
| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 15.833 ms | 0 - 4 MB | NPU |
| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.797 ms | 0 - 2 MB | NPU |
| DnCNN | QNN_DLC | float | Qualcomm® QCS8450 | 12.988 ms | 0 - 174 MB | NPU |
| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 14.094 ms | 0 - 3 MB | NPU |
| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 7.29 ms | 0 - 0 MB | NPU |
| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 4.04 ms | 0 - 136 MB | NPU |
| DnCNN | QNN_DLC | float | Qualcomm® SA8295P | 15.205 ms | 0 - 136 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 0.81 ms | 0 - 33 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.206 ms | 0 - 31 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 1.195 ms | 0 - 0 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Snapdragon® X Elite | 1.99 ms | 0 - 0 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.317 ms | 0 - 50 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Gen 1 Mobile | 2.358 ms | 0 - 55 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 7.514 ms | 0 - 2 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 2.178 ms | 0 - 3 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 1.791 ms | 0 - 1 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® QCS8450 | 2.358 ms | 0 - 55 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 1.875 ms | 0 - 2 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 1.99 ms | 0 - 0 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 38.762 ms | 0 - 138 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.27 ms | 0 - 136 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 1.206 ms | 0 - 31 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Qualcomm® SA8295P | 4.099 ms | 0 - 30 MB | NPU |
| DnCNN | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.27 ms | 0 - 136 MB | NPU |
| DnCNN | TFLITE | float | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 3.069 ms | 0 - 141 MB | NPU |
| DnCNN | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 4.035 ms | 0 - 142 MB | NPU |
| DnCNN | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 5.092 ms | 0 - 170 MB | NPU |
| DnCNN | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 12.976 ms | 0 - 173 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 15.819 ms | 0 - 5 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.712 ms | 0 - 2 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® SA8775P | 13.85 ms | 0 - 141 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® SA8650P | 13.85 ms | 0 - 141 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® SA8255P | 13.85 ms | 0 - 141 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® QCS8450 | 12.976 ms | 0 - 173 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 13.67 ms | 0 - 4 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 4.035 ms | 0 - 142 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® SA7255P | 55.989 ms | 0 - 138 MB | NPU |
| DnCNN | TFLITE | float | Qualcomm® SA8295P | 15.339 ms | 0 - 137 MB | NPU |
| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 For Galaxy Mobile | 0.773 ms | 0 - 32 MB | NPU |
| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 1.185 ms | 0 - 36 MB | NPU |
| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.296 ms | 0 - 50 MB | NPU |
| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Gen 1 Mobile | 2.328 ms | 0 - 56 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 7.549 ms | 0 - 3 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 2.13 ms | 0 - 4 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 1.71 ms | 0 - 17 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® SA8775P | 1.956 ms | 0 - 34 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® SA8650P | 1.956 ms | 0 - 34 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® SA8255P | 1.956 ms | 0 - 34 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® QCS8450 | 2.328 ms | 0 - 56 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 1.816 ms | 0 - 3 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 38.741 ms | 0 - 138 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.218 ms | 0 - 137 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 1.185 ms | 0 - 36 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® SA7255P | 7.502 ms | 0 - 33 MB | NPU |
| DnCNN | TFLITE | w8a8 | Qualcomm® SA8295P | 4.071 ms | 0 - 30 MB | NPU |
| DnCNN | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.218 ms | 0 - 137 MB | NPU |
License
- The license for the original implementation of DnCNN can be found here.
References
- Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
- Source Model Implementation
Community
- Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
- For questions or feedback please reach out to us.
