File size: 9,204 Bytes
79f470b f8da907 79f470b a71ce34 79f470b c95eb37 e815d88 79f470b c95eb37 e46f486 c95eb37 8e8123f 79f470b 3bcc01a 8e8123f 79f470b 83eb19d 79f470b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 |
---
library_name: pytorch
license: other
tags:
- android
pipeline_tag: image-to-image
---

# QuickSRNetSmall: Optimized for Qualcomm Devices
QuickSRNet Small is designed for upscaling images on mobile platforms to sharpen in real-time.
This is based on the implementation of QuickSRNetSmall found [here](https://github.com/quic/aimet-model-zoo/tree/develop/aimet_zoo_torch/quicksrnet).
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/quicksrnetsmall) 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 2.37, ONNX Runtime 1.23.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/quicksrnetsmall/releases/v0.46.0/quicksrnetsmall-onnx-float.zip)
| QNN_DLC | float | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/quicksrnetsmall/releases/v0.46.0/quicksrnetsmall-qnn_dlc-float.zip)
| QNN_DLC | w8a8 | Universal | QAIRT 2.42 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/quicksrnetsmall/releases/v0.46.0/quicksrnetsmall-qnn_dlc-w8a8.zip)
| TFLITE | float | Universal | QAIRT 2.42, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/quicksrnetsmall/releases/v0.46.0/quicksrnetsmall-tflite-float.zip)
| TFLITE | w8a8 | Universal | QAIRT 2.42, TFLite 2.17.0 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/quicksrnetsmall/releases/v0.46.0/quicksrnetsmall-tflite-w8a8.zip)
For more device-specific assets and performance metrics, visit **[QuickSRNetSmall on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/quicksrnetsmall)**.
### Option 2: Export with Custom Configurations
Use the [Qualcomm® AI Hub Models](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/quicksrnetsmall) 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 [QuickSRNetSmall on GitHub](https://github.com/quic/ai-hub-models/blob/main/qai_hub_models/models/quicksrnetsmall) for usage instructions.
## Model Details
**Model Type:** Model_use_case.super_resolution
**Model Stats:**
- Model checkpoint: quicksrnet_small_3x_checkpoint
- Input resolution: 128x128
- Number of parameters: 33.3K
- Model size (float): 133 KB
- Model size (w8a8): 41.7 KB
## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| QuickSRNetSmall | ONNX | float | Snapdragon® X Elite | 1.049 ms | 8 - 8 MB | NPU
| QuickSRNetSmall | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 0.809 ms | 0 - 97 MB | NPU
| QuickSRNetSmall | ONNX | float | Qualcomm® QCS8550 (Proxy) | 1.138 ms | 0 - 44 MB | NPU
| QuickSRNetSmall | ONNX | float | Qualcomm® QCS9075 | 1.436 ms | 6 - 9 MB | NPU
| QuickSRNetSmall | ONNX | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.594 ms | 0 - 91 MB | NPU
| QuickSRNetSmall | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.512 ms | 0 - 89 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Snapdragon® X Elite | 0.842 ms | 0 - 0 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Snapdragon® 8 Gen 3 Mobile | 0.452 ms | 0 - 28 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Qualcomm® QCS8275 (Proxy) | 1.85 ms | 0 - 21 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Qualcomm® QCS8550 (Proxy) | 0.742 ms | 0 - 1 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Qualcomm® SA8775P | 1.082 ms | 0 - 22 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Qualcomm® QCS9075 | 1.102 ms | 0 - 5 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Qualcomm® QCS8450 (Proxy) | 1.04 ms | 0 - 29 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Qualcomm® SA7255P | 1.85 ms | 0 - 21 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Qualcomm® SA8295P | 1.383 ms | 0 - 17 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.359 ms | 0 - 24 MB | NPU
| QuickSRNetSmall | QNN_DLC | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.326 ms | 0 - 24 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Snapdragon® X Elite | 0.426 ms | 0 - 0 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.214 ms | 0 - 24 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® QCS6490 | 1.279 ms | 0 - 2 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® QCS8275 (Proxy) | 0.774 ms | 0 - 19 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.319 ms | 0 - 1 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® SA8775P | 0.516 ms | 0 - 19 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® QCS9075 | 0.497 ms | 0 - 2 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® QCM6690 | 1.208 ms | 0 - 16 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.463 ms | 0 - 25 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® SA7255P | 0.774 ms | 0 - 19 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Qualcomm® SA8295P | 0.703 ms | 0 - 15 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.174 ms | 0 - 21 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.351 ms | 0 - 16 MB | NPU
| QuickSRNetSmall | QNN_DLC | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.145 ms | 0 - 20 MB | NPU
| QuickSRNetSmall | TFLITE | float | Snapdragon® 8 Gen 3 Mobile | 0.628 ms | 0 - 28 MB | NPU
| QuickSRNetSmall | TFLITE | float | Qualcomm® QCS8275 (Proxy) | 2.389 ms | 0 - 21 MB | NPU
| QuickSRNetSmall | TFLITE | float | Qualcomm® QCS8550 (Proxy) | 1.003 ms | 0 - 1 MB | NPU
| QuickSRNetSmall | TFLITE | float | Qualcomm® SA8775P | 1.419 ms | 0 - 21 MB | NPU
| QuickSRNetSmall | TFLITE | float | Qualcomm® QCS9075 | 1.27 ms | 3 - 8 MB | NPU
| QuickSRNetSmall | TFLITE | float | Qualcomm® QCS8450 (Proxy) | 1.318 ms | 1 - 30 MB | NPU
| QuickSRNetSmall | TFLITE | float | Qualcomm® SA7255P | 2.389 ms | 0 - 21 MB | NPU
| QuickSRNetSmall | TFLITE | float | Qualcomm® SA8295P | 1.652 ms | 0 - 17 MB | NPU
| QuickSRNetSmall | TFLITE | float | Snapdragon® 8 Elite For Galaxy Mobile | 0.46 ms | 0 - 20 MB | NPU
| QuickSRNetSmall | TFLITE | float | Snapdragon® 8 Elite Gen 5 Mobile | 0.397 ms | 0 - 23 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Snapdragon® 8 Gen 3 Mobile | 0.27 ms | 0 - 25 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® QCS6490 | 1.042 ms | 0 - 2 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® QCS8275 (Proxy) | 0.89 ms | 0 - 19 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® QCS8550 (Proxy) | 0.398 ms | 0 - 1 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® SA8775P | 0.594 ms | 0 - 20 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® QCS9075 | 0.521 ms | 0 - 3 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® QCM6690 | 1.5 ms | 0 - 16 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® QCS8450 (Proxy) | 0.466 ms | 0 - 26 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® SA7255P | 0.89 ms | 0 - 19 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Qualcomm® SA8295P | 0.806 ms | 0 - 15 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Snapdragon® 8 Elite For Galaxy Mobile | 0.197 ms | 0 - 21 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Snapdragon® 7 Gen 4 Mobile | 0.415 ms | 0 - 17 MB | NPU
| QuickSRNetSmall | TFLITE | w8a8 | Snapdragon® 8 Elite Gen 5 Mobile | 0.162 ms | 0 - 20 MB | NPU
## License
* The license for the original implementation of QuickSRNetSmall can be found
[here](https://github.com/quic/aimet-model-zoo/blob/develop/LICENSE.pdf).
## References
* [QuickSRNet: Plain Single-Image Super-Resolution Architecture for Faster Inference on Mobile Platforms](https://arxiv.org/abs/2303.04336)
* [Source Model Implementation](https://github.com/quic/aimet-model-zoo/tree/develop/aimet_zoo_torch/quicksrnet)
## 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).
|