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license: mit
language:
- en
pipeline_tag: image-to-image
tags:
- Low-light-Enhancement
- ImageEnhancement
---
# LowLightImageEnhancement
This is a collection of Low-light Enhancement algorithms, models have been converted to run on the Axera NPU using **w8a8** quantization.
This model has been optimized with the following LoRA:
Compatible with Pulsar2 version: 6.0 115775d3
## Convert tools links:
For those who are interested in model conversion, you can try to export axmodel through
- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html)
## Support Platform
- AX650
- [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
- [M.2 Accelerator card](https://docs.m5stack.com/en/ai_hardware/LLM-8850_Card)
## 性能基准测试 (Performance Benchmark)
| Model | Input Size | Inference Time |
|-------|-----------|----------------|
| Zero-DCE | 256×256 | 2.6ms |
| Zero-DCE++ | 512×512 | 12.7ms |
| SCI | 600×400 | 1.2ms |
| RetinexFormer | 224×224 | 35ms |
## How to use
Download all files from this repository to the device
```
模型文件组织方式如下：
.
|-- model_convert
| |-- SCI.json
| `-- axmodel
| `-- SCI_TPAMI_600_400.axmodel
|-- pic
| |-- 00001.png
| |-- 00051.png
| |-- 00079.png
| |-- 00091.png
| |-- 2062.jpg
| |-- 2064.jpg
| |-- 3008.jpg
| |-- 3018.jpg
| |-- 3020.jpg
| `-- NPE_71.png
|-- python
| |-- axmodel_infer.py
| `-- onnx_infer.py
`-- res
`-- axmodel_res.png
```
### Inference
图片推理，执行命令`python3 axmodel_infer.py`:
```
(base) root@ax650:~/SCI# python3 axmodel_infer.py
[INFO] Available providers: ['AxEngineExecutionProvider', 'AXCLRTExecutionProvider']
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Chip type: ChipType.MC50
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Engine version: 2.12.0s
[INFO] Model type: 2 (triple core)
[INFO] Compiler version: 6.0-dirty 115775d3-dirty
Saved comparison → ./axmodel_res.png
Input: (600, 400) → model input: (600,400) → restored: (600, 400)
```
推理结果样例：
|