File size: 4,127 Bytes
a20719a 006270c 21a2ce4 6123f94 07a6275 92ed922 7b94e89 96c8c19 07a6275 27f73fa 7b94e89 b6c06f2 1b3ea2c 07a6275 7b94e89 6a2fa62 7b94e89 6a2fa62 642303e 07a6275 7b94e89 642303e 7b94e89 07a6275 642303e 07a6275 7b94e89 642303e 07a6275 7b94e89 07a6275 642303e 7b94e89 642303e 7b94e89 812e077 07a6275 642303e 7b94e89 642303e 7b94e89 642303e b6c06f2 642303e 96c8c19 18e65bf 1306203 |
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 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 |
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")
col1, col2 = st.columns(2)
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
@st.experimental_memo
def chamada():
percent_complete=0
my_bar = st.progress(0)
percent_complete= percent_complete+ 10
with col1:
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
with col1:
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)
with col1:
st.image(input_img)
os.system("ls ./_input")
if 'myVar' not in globals():
myVar=""
st.write("melhorando faces")
with col2:
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")
with col1:
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
with col1:
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" )
with col1:
st.write("preparando para download do video")
percent_complete= percent_complete+ 30
my_bar.progress(percent_complete )
with col2:
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)
with col2
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])
load = st.checkbox("load")
if load:
chamada()
#st.button('Imagem',on_click=inference)
exec=True
|