app.py

import os
import gradio as gr
from PIL import Image


os.system(
    'wget https://github.com/FanChiMao/SRMNet/releases/download/0.0/real_denoising_SRMNet.pth -P experiments/pretrained_models')


def inference(img):
    os.system('mkdir test')
    #basewidth = 256
    #wpercent = (basewidth / float(img.size[0]))
    #hsize = int((float(img.size[1]) * float(wpercent)))
    #img = img.resize((basewidth, hsize), Image.ANTIALIAS)
    img.save("test/1.png", "PNG")
    os.system(
        'python main_test_SRMNet.py --input_dir test --weights experiments/pretrained_models/real_denoising_SRMNet.pth')
    return 'result/1.png'


title = "<span style='color: #191970;'>Aiconvert.online</span>"
description = ""
article = ""

examples = [['Noise.png'], ['Noise2.png']]
gr.Interface(
    inference,
    [gr.inputs.Image(type="pil", label="Input")],
    gr.outputs.Image(type="filepath", label="Output"),
    title=title,
    description=description,
    article=article,
    css=".gradio-container {background-color: #FFE4C4} footer{display:none !important;}",
    allow_flagging=False,
    allow_screenshot=False,
    examples=examples
).launch(debug=True)