v0.61.0
Browse filesSee https://github.com/qualcomm/ai-hub-models/releases/v0.61.0 for changelog.
- README.md +52 -112
- release_assets.json +4 -27
README.md
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---
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library_name: pytorch
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license:
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tags:
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- real_time
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- android
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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.
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This is based on the implementation of DnCNN found [here](https://github.com/cszn/KAIR).
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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/blob/v0.
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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 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.
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| QNN_DLC | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.60.0/dncnn-qnn_dlc-w8a8.zip)
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.60.0/dncnn-tflite-float.zip)
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| TFLITE | w8a8 | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.60.0/dncnn-tflite-w8a8.zip)
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For more device-specific assets and performance metrics, visit **[DnCNN on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/dncnn)**.
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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/blob/v0.
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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 [DnCNN on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.
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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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| DnCNN | ONNX | float | Snapdragon® X2 Elite | 4.
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| DnCNN | ONNX | float | Snapdragon® X Elite | 7.
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| DnCNN | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 5.
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| DnCNN | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 13.
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 16.
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.
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| DnCNN | ONNX | float | Qualcomm® QCS8450 | 13.
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 14.
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 7.
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 4.
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| DnCNN | ONNX | float | Snapdragon® 8 Elite Mobile | 4.
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| DnCNN | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN | QNN_DLC | float | Snapdragon®
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| DnCNN | QNN_DLC | float | Snapdragon®
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN |
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| DnCNN | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.05 ms | 0 - 149 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Snapdragon® X2 Elite | 1.176 ms | 0 - 0 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Snapdragon® X Elite | 2.007 ms | 0 - 0 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.323 ms | 0 - 46 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Gen 1 Mobile | 2.514 ms | 0 - 51 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 9.419 ms | 0 - 2 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 2.183 ms | 0 - 2 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 7.581 ms | 0 - 28 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 1.777 ms | 0 - 3 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® SA8775P | 1.999 ms | 0 - 30 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® SA8650P | 1.999 ms | 0 - 30 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® SA8255P | 1.999 ms | 0 - 30 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® QCS8450 | 2.514 ms | 0 - 51 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 2.02 ms | 2 - 4 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ IQ-X7181 | 2.007 ms | 0 - 0 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 38.849 ms | 0 - 140 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.256 ms | 0 - 140 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 1.221 ms | 0 - 28 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® SA7255P | 7.581 ms | 0 - 28 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Qualcomm® SA8295P | 4.226 ms | 0 - 26 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Elite Mobile | 1.221 ms | 0 - 28 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.805 ms | 0 - 28 MB | NPU
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| DnCNN | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.256 ms | 0 - 140 MB | NPU
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| DnCNN | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 5.2 ms | 0 - 179 MB | NPU
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| DnCNN | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 14.005 ms | 0 - 180 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 16.242 ms | 0 - 5 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 56.39 ms | 0 - 142 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.928 ms | 0 - 2 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® SA8775P | 14.161 ms | 0 - 144 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® SA8650P | 14.161 ms | 0 - 144 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® SA8255P | 14.161 ms | 0 - 144 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® QCS8450 | 14.005 ms | 0 - 180 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 14.318 ms | 0 - 4 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 4.163 ms | 0 - 147 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® SA7255P | 56.39 ms | 0 - 142 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® SA8295P | 15.612 ms | 0 - 141 MB | NPU
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| DnCNN | TFLITE | float | Snapdragon® 8 Elite Mobile | 4.163 ms | 0 - 147 MB | NPU
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| DnCNN | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.173 ms | 0 - 146 MB | NPU
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| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 1.302 ms | 0 - 47 MB | NPU
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| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Gen 1 Mobile | 2.343 ms | 0 - 52 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS6490 | 9.451 ms | 0 - 3 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 2.14 ms | 0 - 3 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-8275 | 7.522 ms | 0 - 29 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 1.711 ms | 0 - 72 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® SA8775P | 1.98 ms | 0 - 30 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® SA8650P | 1.98 ms | 0 - 30 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® SA8255P | 1.98 ms | 0 - 30 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® QCS8450 | 2.343 ms | 0 - 52 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ IQ-9075 | 1.819 ms | 0 - 3 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-6690 | 38.909 ms | 0 - 141 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-7790 | 3.215 ms | 0 - 141 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® Dragonwing™ Q-8750 | 1.19 ms | 0 - 30 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® SA7255P | 7.522 ms | 0 - 29 MB | NPU
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| DnCNN | TFLITE | w8a8 | Qualcomm® SA8295P | 4.183 ms | 0 - 26 MB | NPU
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| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Elite Mobile | 1.19 ms | 0 - 30 MB | NPU
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| DnCNN | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.771 ms | 0 - 30 MB | NPU
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| DnCNN | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 3.215 ms | 0 - 141 MB | NPU
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## License
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* The license for the original implementation of DnCNN can be found
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---
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library_name: pytorch
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license: mit
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tags:
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- real_time
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- android
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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.
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This is based on the implementation of DnCNN found [here](https://github.com/cszn/KAIR).
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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/blob/v0.61.0/src/qai_hub_models/models/dncnn) 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 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.61.0/dncnn-onnx-float.zip)
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| QNN_DLC | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.61.0/dncnn-qnn_dlc-float.zip)
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| TFLITE | float | Universal | QAIRT 2.45 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.61.0/dncnn-tflite-float.zip)
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For more device-specific assets and performance metrics, visit **[DnCNN on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/dncnn)**.
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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/blob/v0.61.0/src/qai_hub_models/models/dncnn) 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 [DnCNN on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.61.0/src/qai_hub_models/models/dncnn) 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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| DnCNN | ONNX | float | Snapdragon® X2 Elite | 4.046 ms | 1 - 1 MB | NPU
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| DnCNN | ONNX | float | Snapdragon® X Elite | 7.16 ms | 0 - 0 MB | NPU
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| DnCNN | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 5.158 ms | 1 - 180 MB | NPU
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| DnCNN | ONNX | float | Snapdragon® 8 Gen 1 Mobile | 13.764 ms | 1 - 179 MB | NPU
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 16.04 ms | 1 - 4 MB | NPU
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.891 ms | 1 - 3 MB | NPU
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| DnCNN | ONNX | float | Qualcomm® QCS8450 | 13.764 ms | 1 - 179 MB | NPU
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 14.495 ms | 1 - 4 MB | NPU
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ IQ-X7181 | 7.16 ms | 0 - 0 MB | NPU
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| DnCNN | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 4.124 ms | 0 - 144 MB | NPU
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| DnCNN | ONNX | float | Snapdragon® 8 Elite Mobile | 4.124 ms | 0 - 144 MB | NPU
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| DnCNN | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.212 ms | 0 - 144 MB | NPU
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| DnCNN | QNN_DLC | float | Snapdragon® X2 Elite | 4.153 ms | 0 - 0 MB | NPU
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| DnCNN | QNN_DLC | float | Snapdragon® X Elite | 7.233 ms | 0 - 0 MB | NPU
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| DnCNN | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 5.047 ms | 0 - 176 MB | NPU
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| DnCNN | QNN_DLC | float | Snapdragon® 8 Gen 1 Mobile | 13.519 ms | 0 - 178 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 15.832 ms | 0 - 3 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-8275 | 55.996 ms | 0 - 141 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.676 ms | 0 - 2 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® SA8775P | 13.879 ms | 0 - 143 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® SA8650P | 13.879 ms | 0 - 143 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® SA8255P | 13.879 ms | 0 - 143 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® QCS8450 | 13.519 ms | 0 - 178 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-9075 | 14.14 ms | 2 - 4 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ IQ-X7181 | 7.233 ms | 0 - 0 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® Dragonwing™ Q-8750 | 4.035 ms | 0 - 144 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® SA7255P | 55.996 ms | 0 - 141 MB | NPU
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| DnCNN | QNN_DLC | float | Qualcomm® SA8295P | 15.289 ms | 0 - 139 MB | NPU
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| DnCNN | QNN_DLC | float | Snapdragon® 8 Elite Mobile | 4.035 ms | 0 - 144 MB | NPU
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| DnCNN | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.027 ms | 0 - 148 MB | NPU
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| DnCNN | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 5.197 ms | 0 - 179 MB | NPU
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| DnCNN | TFLITE | float | Snapdragon® 8 Gen 1 Mobile | 13.906 ms | 0 - 178 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 15.918 ms | 0 - 5 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 56.399 ms | 0 - 142 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 6.929 ms | 0 - 11 MB | NPU
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| DnCNN | TFLITE | float | Qualcomm® SA8775P | 14.161 ms | 0 - 145 MB | NPU
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+
| DnCNN | TFLITE | float | Qualcomm® SA8650P | 14.161 ms | 0 - 145 MB | NPU
|
| 100 |
+
| DnCNN | TFLITE | float | Qualcomm® SA8255P | 14.161 ms | 0 - 145 MB | NPU
|
| 101 |
+
| DnCNN | TFLITE | float | Qualcomm® QCS8450 | 13.906 ms | 0 - 178 MB | NPU
|
| 102 |
+
| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 14.024 ms | 0 - 4 MB | NPU
|
| 103 |
+
| DnCNN | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 4.13 ms | 0 - 142 MB | NPU
|
| 104 |
+
| DnCNN | TFLITE | float | Qualcomm® SA7255P | 56.399 ms | 0 - 142 MB | NPU
|
| 105 |
+
| DnCNN | TFLITE | float | Qualcomm® SA8295P | 15.603 ms | 0 - 141 MB | NPU
|
| 106 |
+
| DnCNN | TFLITE | float | Snapdragon® 8 Elite Mobile | 4.13 ms | 0 - 142 MB | NPU
|
| 107 |
+
| DnCNN | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 3.137 ms | 0 - 147 MB | NPU
|
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|
| 108 |
|
| 109 |
## License
|
| 110 |
* The license for the original implementation of DnCNN can be found
|
release_assets.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"version": "0.
|
| 3 |
"precisions": {
|
| 4 |
"float": {
|
| 5 |
"universal_assets": {
|
|
@@ -8,42 +8,19 @@
|
|
| 8 |
"qairt": "2.45.0.260326154327",
|
| 9 |
"onnx_runtime": "1.27.1"
|
| 10 |
},
|
| 11 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.
|
| 12 |
},
|
| 13 |
"qnn_dlc": {
|
| 14 |
"tool_versions": {
|
| 15 |
"qairt": "2.45.0.260326154327"
|
| 16 |
},
|
| 17 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.
|
| 18 |
},
|
| 19 |
"tflite": {
|
| 20 |
"tool_versions": {
|
| 21 |
"qairt": "2.45.0.260326154327"
|
| 22 |
},
|
| 23 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.
|
| 24 |
-
}
|
| 25 |
-
}
|
| 26 |
-
},
|
| 27 |
-
"w8a8": {
|
| 28 |
-
"universal_assets": {
|
| 29 |
-
"onnx": {
|
| 30 |
-
"tool_versions": {
|
| 31 |
-
"qairt": "2.45.0.260326154327",
|
| 32 |
-
"onnx_runtime": "1.27.1"
|
| 33 |
-
},
|
| 34 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.60.0/dncnn-onnx-w8a8.zip"
|
| 35 |
-
},
|
| 36 |
-
"qnn_dlc": {
|
| 37 |
-
"tool_versions": {
|
| 38 |
-
"qairt": "2.45.0.260326154327"
|
| 39 |
-
},
|
| 40 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.60.0/dncnn-qnn_dlc-w8a8.zip"
|
| 41 |
-
},
|
| 42 |
-
"tflite": {
|
| 43 |
-
"tool_versions": {
|
| 44 |
-
"qairt": "2.45.0.260326154327"
|
| 45 |
-
},
|
| 46 |
-
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.60.0/dncnn-tflite-w8a8.zip"
|
| 47 |
}
|
| 48 |
}
|
| 49 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"version": "0.61.0",
|
| 3 |
"precisions": {
|
| 4 |
"float": {
|
| 5 |
"universal_assets": {
|
|
|
|
| 8 |
"qairt": "2.45.0.260326154327",
|
| 9 |
"onnx_runtime": "1.27.1"
|
| 10 |
},
|
| 11 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.61.0/dncnn-onnx-float.zip"
|
| 12 |
},
|
| 13 |
"qnn_dlc": {
|
| 14 |
"tool_versions": {
|
| 15 |
"qairt": "2.45.0.260326154327"
|
| 16 |
},
|
| 17 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.61.0/dncnn-qnn_dlc-float.zip"
|
| 18 |
},
|
| 19 |
"tflite": {
|
| 20 |
"tool_versions": {
|
| 21 |
"qairt": "2.45.0.260326154327"
|
| 22 |
},
|
| 23 |
+
"download_url": "https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/dncnn/releases/v0.61.0/dncnn-tflite-float.zip"
|
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|
| 24 |
}
|
| 25 |
}
|
| 26 |
}
|