https://github.com/marty1885/rknn-superresolution
Superresolution running on Rockchip NPU (RK3588, etc..)
https://github.com/marty1885/rknn-superresolution
npu rk3588 rknn rockchip super-resolution
Last synced: 2 months ago
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Superresolution running on Rockchip NPU (RK3588, etc..)
- Host: GitHub
- URL: https://github.com/marty1885/rknn-superresolution
- Owner: marty1885
- License: isc
- Created: 2023-07-15T12:36:25.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2024-07-07T06:08:40.000Z (over 1 year ago)
- Last Synced: 2025-03-28T03:22:36.055Z (6 months ago)
- Topics: npu, rk3588, rknn, rockchip, super-resolution
- Language: Python
- Homepage:
- Size: 5.86 KB
- Stars: 13
- Watchers: 2
- Forks: 1
- Open Issues: 2
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Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# RKNN Superresolution
Demo code to run image superresolution on Rockchip NPU
## How to use
1. Download `super-resolution-10.onnx` from the [ONNX model zoo](https://github.com/onnx/models/tree/bec48b6a70e5e9042c0badbaafefe4454e072d08/validated/vision/super_resolution/sub_pixel_cnn_2016/model)
* [https://github.com/onnx/models/blob/main/validated/vision/super_resolution/sub_pixel_cnn_2016/model/super-resolution-10.onnx](https://github.com/onnx/models/blob/bec48b6a70e5e9042c0badbaafefe4454e072d08/validated/vision/super_resolution/sub_pixel_cnn_2016/model/super-resolution-10.onnx)
2. Run `convert.py` on a PC with RKNN installed
* Modify the `target_platform` variable to sute your board
3. Move the generated `super-resolution-10.rknn` to your dev board
4. Prepare any image, name it `test.jpg` on your board. Run `infer.py`
5. `out.jpg` is your output