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import os | |
import random | |
import gradio as gr | |
from PIL import Image | |
import torch | |
from random import randint | |
import sys | |
from subprocess import call | |
torch.hub.download_url_to_file('https://i.imgur.com/tXrot31.jpg', 'cpu.jpg') | |
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") | |
#run_cmd("python setup.py develop") | |
def inference(img): | |
_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 " + INPUT_DIR) | |
run_cmd("mkdir " + OUTPUT_DIR) | |
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(INPUT_DIR + "1.jpg", "JPEG") | |
run_cmd("python inference_realesrgan.py --model_path RealESRGAN_x4plus.pth --input "+ INPUT_DIR + " --output " + OUTPUT_DIR + " --netscale 4 --outscale 3.5") | |
return os.path.join(OUTPUT_DIR, "1_out.jpg") | |
inferences_running = 0 | |
def throttled_inference(image): | |
global inferences_running | |
current = inferences_running | |
if current >= 5: | |
print(f"Rejected inference when we already had {current} running") | |
return "cpu.jpg" | |
print(f"Inference starting when we already had {current} running") | |
inferences_running += 1 | |
try: | |
return inference(image) | |
finally: | |
print("Inference finished") | |
inferences_running -= 1 | |
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." | |
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( | |
throttled_inference, | |
[gr.inputs.Image(type="pil", label="Input")], | |
gr.outputs.Image(type="file", label="Output"), | |
title=title, | |
description=description, | |
article=article, | |
examples=[ | |
['bear.jpg'] | |
] | |
).launch(debug=True) |