app.py

import streamlit as st
import base64
import os.path
import cv2
import random
       

os.system("mkdir _input")
os.system("mkdir _output")
os.system("mkdir _outputf")
os.system("ls")


title = "Melhoria de imagens"
st.title(title)
os.system("ls")
description = "Sistema para automação。"
st.header(description)
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>"
#-s 720x1280 

load = st.checkbox("load")

if load:
          percent_complete=0
          my_bar = st.progress(0)   
          percent_complete= percent_complete+ 10
          my_bar.progress(percent_complete )    
       #exec=True 
          st.write("ffmpeg separando imagens")
       #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 1480x2560  -r 30 ./_input/imagem-%4d.png")
          percent_complete= percent_complete+ 30
          my_bar.progress(percent_complete )   
          st.write("testando imagem")
          input_img = cv2.imread("./_input/imagem-0002.png" , cv2.IMREAD_COLOR)
          input_img= cv2.cvtColor(input_img,cv2.COLOR_BGR2RGB) 
          
          st.image(input_img)
          
          os.system("ls ./_input") 
          if 'myVar' not in globals():
              myVar=""
          st.write("melhorando faces")
          with st.spinner('Wait for it...'):
             # 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 2")
          
          percent_complete= percent_complete+ 30
          my_bar.progress(percent_complete )   
         
          os.system("ls ./_output")
          os.system("echo ----")
          os.system("ls ./_output/cmp")
          os.system("echo ----")
          os.system("ls ./_output/restored_imgs")
          os.system("echo ----")
#          s 1480x2560
          st.write("recompilando video")
          #ffmpeg -r 60 -f image2 -s 1920x1080 -i _output/restored_imgs/imagem-%4d.png   -pix_fmt yuv420p ./videoSaida/output.mp4
          os.system("ffmpeg -y -r 30 -f image2  -i _output/restored_imgs/imagem-%4d.png   -pix_fmt yuv420p ./videoSaida/output.mp4")
          os.system("ls ./videoSaida")
          #st.video("./videoSaida/output.mp4" )
          st.write("preparando para download do video")
          percent_complete= percent_complete+ 30
          my_bar.progress(percent_complete ) 
          with open("./videoSaida/output.mp4", "rb") as file:
              st.video(file)

              btn = st.download_button(
          
                      label="Download video",
          
                      data=file,
          
                      file_name="output.png",
          
                      mime="video/mp4"
          
                    )
          #st.download_button("download video", data, file_name='output.mp4', mime='video/mp4',)
          #stremio
          #input_img = cv2.imread("./_output/cmp/imagem-0001_0000.png" , cv2.IMREAD_COLOR)
          #input_img = cv2.imread("./_output/cmp/imagem-0001_0000.png" , cv2.IMREAD_COLOR)
      
          st.write("demonstrando imagem restaurada")
          input_img = cv2.imread("./_output/restored_imgs/imagem-0002.png" , cv2.IMREAD_COLOR)
          input_img= cv2.cvtColor(input_img,cv2.COLOR_BGR2RGB) 
          
          st.image(input_img)
          exec=False
       #return Image.fromarray(restored_faces[0][:,:,::-1])
       
   
#st.button('Imagem',on_click=inference)
exec=True