RefVSR / app.py
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import os
import sys
import gradio as gr
from PIL import Image
## environment settup
os.system("git clone https://github.com/codeslake/RefVSR.git")
os.chdir("RefVSR")
os.system("./install/install_cudnn113.sh")
os.system("wget https://upload.wikimedia.org/wikipedia/commons/thumb/e/ec/Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg/800px-Mona_Lisa%2C_by_Leonardo_da_Vinci%2C_from_C2RMF_retouched.jpg -O mona.jpg")
os.mkdir("RefVSR")
os.system("wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1TFgihdn8Ml_536F2VXbmkXuGEHcEHOYz' -O ckpt/RefVSR_small_MFID_8K.pytorch")
sys.path.append("RefVSR")
## RefVSR
LR_path = "test/test/HR/UW/0000"
Ref_path = "test/test/HR/W/0000"
Ref_path_T = "test/test/HR/W/0000"
os.mkdirs(LR_path)
os.mkdirs(Ref_path)
def resize(width,img):
basewidth = width
wpercent = (basewidth/float(img.size[0]))
hsize = int((float(img.size[1])*float(wpercent)))
img = img.resize((basewidth,hsize), Image.ANTIALIAS)
return img
def inference(LR, Ref):
LR = resize(256, LR)
Ref = resize(256, Ref)
LR.save(os.path.join(LR_path, '0000.png'))
Ref.save(os.path.join(Ref_path, '0000.png'))
Ref.save(os.path.join(Ref_path_T, '0000.png'))
# os.system("python inference_realbasicvsr.py configs/realbasicvsr_x4.py RealBasicVSR_x4.pth test/ results/demo_000")
os.system("python -B run.py \
--mode amp_RefVSR_small_MFID_8K \
--config config_RefVSR_small_MFID_8K \
--data RealMCVSR \
--ckpt_abs_name ckpt/RefVSR_small_MFID_8K.pytorch \
--data_offset ./test \
--output_offset ./result \
--qualitative_only \
--cpu \
--is_gradio")
return "results/0000.png"
title="RefVSR"
description="Demo application for Reference-based Video Super-Resolution. To use it, simply upload your image or click on 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/2203.14537' target='_blank'>Reference-based Video Super-Resolution</a> | <a href='https://github.com/codeslake/RefVSR' target='_blank'>Github Repo</a></p>"
examples=[['mona.jpg']]
gr.Interface(inference,gr.inputs.Image(type="pil"),gr.outputs.Image(type="file"),title=title,description=description,article=article,examples=examples).launch(enable_queue=True)