metadata

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
The repo of AXera Platform, which you can get the detial of guide
Pulsar2 Link, How to Convert ONNX to axmodel

Support Platform

AX650
- M4N-Dock(爱芯派Pro)
- M.2 Accelerator card
AX630C

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?, 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

Output