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--- |
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license: other |
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license_name: aimet-model-zoo |
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license_link: https://github.com/quic/aimet-model-zoo/blob/develop/LICENSE.pdf |
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pipeline_tag: image-to-image |
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tags: |
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- AIoT |
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- QNN |
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--- |
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## QuickSRNetLarge: Super Resolution |
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QuickSRNet is a lightweight real-time image super-resolution model optimized for mobile and edge devices, efficiently enhancing image resolution under low computational resources. It employs a streamlined residual architecture with shallow feature reuse and efficient channel attention, minimizing parameters while improving detail reconstruction (e.g., edge sharpening and texture recovery). Supporting 2x/4x upscaling, its dynamic upsampling module adaptively balances speed and quality, achieving PSNR/SSIM metrics close to complex models (e.g., EDSR) with significantly faster inference. Ideal for real-time video enhancement, mobile image processing, and IoT devices, it delivers an efficient solution for resource-constrained environments. |
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### Source model |
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- Input shape: 1x3x128x128 |
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- Number of parameters: 425.67KB |
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- Model size: 1.67M |
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- Output shape: 1x3x512x512 |
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The source model can be found [here](https://github.com/quic/aimet-model-zoo/tree/develop/aimet_zoo_torch/quicksrnet) |
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## Performance Reference |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## Inference & Model Conversion |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## License |
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- Source Model: [AIMET-MODEL-ZOO](https://github.com/quic/aimet-model-zoo/blob/develop/LICENSE.pdf) |
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- Deployable Model: [AIMET-MODEL-ZOO](https://github.com/quic/aimet-model-zoo/blob/develop/LICENSE.pdf) |
