README.md

---
license: bsd-3-clause-clear
language:
- en
pipeline_tag: image-to-image
tags:
- Real-ESRGAN
- SR
- Int8
---


# Real-ESRGAN

This version of Real-ESRGAN has been converted to run on the Axera NPU using **w8a8** quantization.

This model has been optimized with the following LoRA: 

Compatible with Pulsar2 version: 3.4

## Convert tools links:

For those who are interested in model conversion, you can try to export axmodel through 

- [The repo of original](https://github.com/xinntao/Real-ESRGAN)

- [The repo of AXera Platform](https://github.com/AXERA-TECH/realesrgan.axera), which you can get the detial of guide

- [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://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
- AX630C
  - [爱芯派2](https://axera-pi-2-docs-cn.readthedocs.io/zh-cn/latest/index.html)
  - [Module-LLM](https://docs.m5stack.com/zh_CN/module/Module-LLM)
  - [LLM630 Compute Kit](https://docs.m5stack.com/zh_CN/core/LLM630%20Compute%20Kit)
  
 
|Chips| 64x64 -> 256x256 | 256x256 -> 1024x1024 |
|--|--|--|
|AX650| 15 ms | 440 ms |
|AX630C| 76 ms | 2030 ms |

## How to use

Download all files from this repository to the device

```
(axcl) axera@raspberrypi:~/samples/realesrgan.axera $ tree -L 2
.
├── ax630c
│   ├── realesrgan-x4-256.axmodel
│   └── realesrgan-x4.axmodel
├── ax650
│   ├── realesrgan-x4-256.axmodel
│   └── realesrgan-x4.axmodel
├── config.json
├── main.py
├── onnx
│   ├── realesrgan-x4-256.onnx
│   └── realesrgan-x4.onnx
├── output_test_256.jpg
├── out_test-256.jpg
└── test_256.jpeg

3 directories, 11 file

```

### python env requirement

#### pyaxengine

https://github.com/AXERA-TECH/pyaxengine

```
wget https://github.com/AXERA-TECH/pyaxengine/releases/download/0.1.3rc0/axengine-0.1.3-py3-none-any.whl
pip install axengine-0.1.3-py3-none-any.whl
```

#### others

```
pip install argparse numpy opencv-python
```

## Inference with AX630C Host, such as Module-LLM, LLM630 Compute Kit

```
root@ax630c:/mnt/qtang/realesrgan.axera# python3 main.py --input test_256.jpeg --output test_256_20e.jpeg --model ax630/realesrgan-x4-256.axmodel
[INFO] Available providers:  ['AxEngineExecutionProvider']
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Chip type: ChipType.MC20E
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Engine version: 2.7.2a
[INFO] Model type: 1 (full core)
[INFO] Compiler version: 3.4 3dfd5692
input.1 [1, 256, 256, 3] uint8
1895 [1, 1024, 1024, 3] float32
Original Image Shape: (243, 243, 3)
Preprocessed Image Shape: (1, 256, 256, 3)
Inference Time: 2066.72 ms
Output Shape: (1, 1024, 1024, 3)
Final Output Image Shape: (1024, 1024, 3)
root@ax630c:/mnt/qtang/realesrgan.axera# 
```

## Inference with M.2 Accelerator card

[What is M.2 Accelerator card?](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html), Show this DEMO based on Raspberry PI 5.

```
(axcl) axera@raspberrypi:~/samples/realesrgan.axera $ python main.py --input test_256.jpeg --output output_test_256.jpg --model realesrgan-x4-256.axmodel
[INFO] Available providers:  ['AXCLRTExecutionProvider']
[INFO] Using provider: AXCLRTExecutionProvider
[INFO] SOC Name: AX650N
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Compiler version: 3.4 3dfd5692
input.1 [1, 256, 256, 3] uint8
<cdata 'char *' 0x262e54e0> [1, 1024, 1024, 3] float32
Original Image Shape: (243, 243, 3)
Preprocessed Image Shape: (1, 256, 256, 3)
Inference Time: 455.81 ms
Output Shape: (1, 1024, 1024, 3)
Final Output Image Shape: (1024, 1024, 3)
(axcl) axera@raspberrypi:~/samples/realesrgan.axera $
```

**Input**
![](./test_256.jpeg)

**Output**
![](./output_test_256.jpg)