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Real-ESRGAN

This document explains how to run the Real-ESRGAN example application on a host device equipped with the Radxa AICore AX-M1.

Precompiled model quantization methods: w8a8

Download Example Application Repository​

Use huggingfcae-cli to download the example application repository.

Host
pip3 install -U "huggingface_hub[cli]"
huggingface-cli download AXERA-TECH/Real-ESRGAN --local-dir ./Real-ESRGAN
cd Real-ESRGAN

Example Usage​

Install Python Dependencies​

Host
pip3 install https://github.com/AXERA-TECH/pyaxengine/releases/download/0.1.3.rc1/axengine-0.1.3-py3-none-any.whl
pip3 install argparse numpy opencv-python

Model Inference​

Host
python3 main.py --input test_256.jpeg  --output test_256_20e.jpeg --model ax650/realesrgan-x4-256.axmodel
(.venv) rock@rock-5b-plus:~/ssd/axera/Real-ESRGAN$ python3 main.py --input test_256.jpeg  --output test_256_20e.jpeg --model ax650/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
1895 [1, 1024, 1024, 3] float32
Original Image Shape: (243, 243, 3)
Preprocessed Image Shape: (1, 256, 256, 3)
Inference Time: 465.12 ms
Output Shape: (1, 1024, 1024, 3)
Final Output Image Shape: (1024, 1024, 3)

real-esrgan demo input

real-esrgan demo output