import streamlit as st
import os.path

os.system("mkdir _input")
os.system("mkdir _output")
os.system("mkdir _outputf")
os.system("ls")
if not os.path.isfile("./_input/imagem-0001.png"):
    os.system("ffmpeg -i vivi.mp4   -compression_level 10 -pred mixed -pix_fmt rgb24 -sws_flags +accurate_rnd+full_chroma_int -s 1080x1920 -r 0.12 ./_input/imagem-%4d.png")

os.system("ls ./_input") 
if 'myVar' not in globals():
    myVar=""
   # os.system("pip install git+https://github.com/TencentARC/GFPGAN.git")
os.system("python3 inference_gfpgan.py -i _input -o _output -v 1.3 -s 4")
import cv2

import random


os.system("ls ./_output")
os.system("echo ----")
os.system("ls ./_output/cmp")
os.system("echo ----")
os.system("ls ./_output/restored_imgs")
os.system("echo ----")




def inference():
    random.randint(0, 9)
    input_img = cv2.imread("./_output/cmp/imagem-000"+str(random.randint(1, 4))+"_0000.png" , cv2.IMREAD_COLOR)
    input_img= cv2.cvtColor(input_img,cv2.COLOR_BGR2RGB) 
    st.image(input_img)
   
    #return Image.fromarray(restored_faces[0][:,:,::-1])
    

title = "Melhoria de imagens"

os.system("ls")
description = "Sistema para automação。"

article = "<p style='text-align: center'><a href='https://huggingface.co/spaces/akhaliq/GFPGAN/' target='_blank'>clone from akhaliq@huggingface with little change</a> | <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>GFPGAN Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
st.button('Comparacao',on_click=inference)