File size: 2,645 Bytes
e40c95c
1106a9f
 
 
e40c95c
 
 
 
 
 
1106a9f
7aacbb3
 
4db9c56
 
1106a9f
 
 
 
 
 
 
 
e40c95c
 
 
273d6eb
24f9520
2683afa
 
1106a9f
e40c95c
7aacbb3
 
e40c95c
7aacbb3
 
 
 
 
 
 
 
 
 
 
f1d72e1
7aacbb3
f1d72e1
3923e8c
4a4d2f6
e40c95c
7aacbb3
 
 
78eae8c
cf58652
78eae8c
e40c95c
 
1106a9f
 
 
e40c95c
 
 
78eae8c
1106a9f
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
import os
os.system("pip install gradio==2.9b23")
#https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/13985
#os.system("python -m pip install torch==2.0.1 torchvision==0.15.2")
import random
import gradio as gr
from PIL import Image
import torch
from random import randint
import sys
from subprocess import call
import psutil




torch.hub.download_url_to_file('http://people.csail.mit.edu/billf/project%20pages/sresCode/Markov%20Random%20Fields%20for%20Super-Resolution_files/100075_lowres.jpg', 'bear.jpg')
  
    
def run_cmd(command):
    try:
        print(command)
        call(command, shell=True)
    except KeyboardInterrupt:
        print("Process interrupted")
        sys.exit(1)
run_cmd("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth -P .")
run_cmd("pip install basicsr")
run_cmd("pip freeze")

os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth -P .")


def inference(img,mode):
    _id = randint(1, 10000)
    INPUT_DIR = "./tmp/input_image" + str(_id) + "/"
    OUTPUT_DIR = "./tmp/output_image" + str(_id) + "/"
    run_cmd("rm -rf " + INPUT_DIR)
    run_cmd("rm -rf " + OUTPUT_DIR)
    run_cmd("mkdir -p " + INPUT_DIR)
    run_cmd("mkdir -p " + OUTPUT_DIR)
    basewidth = 256
    wpercent = (basewidth/float(img.size[0]))
    hsize = int((float(img.size[1])*float(wpercent)))
    #img = img.resize((basewidth,hsize), Image.LANCZOS)
    img.save(INPUT_DIR + "1.png", "PNG")
    if mode == "base":
        run_cmd("python inference_realesrgan.py -n RealESRGAN_x4plus -i "+ INPUT_DIR + " -o " + OUTPUT_DIR)
    else:
        run_cmd("python inference_realesrgan.py -n RealESRGAN_x4plus_anime_6B -i "+ INPUT_DIR + " -o " + OUTPUT_DIR)
    return os.path.join(OUTPUT_DIR, "1_out.png")



        
title = "Real-ESRGAN"
description = "Gradio demo for Real-ESRGAN. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2107.10833'>Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data</a> | <a href='https://github.com/xinntao/Real-ESRGAN'>Github Repo</a></p>"

gr.Interface(
    inference, 
    [gr.inputs.Image(type="pil", label="Input"),gr.inputs.Radio(["base","anime"], type="value", default="base", label="model type")], 
    gr.outputs.Image(type="file", label="Output"),
    title=title,
    description=description,
    article=article,
    examples=[
    #['bear.jpg','base'],
    #['anime.png','anime']
    ]).launch()