Update app.py

app.py

@@ -9,7 +9,7 @@ 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)
@@ -18,34 +18,37 @@ 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(suppress_st_warnings=True)
+@st.experimental_memo
 def chamada():
           percent_complete=0
           my_bar = st.progress(0)   
           percent_complete= percent_complete+ 10
-          my_bar.progress(percent_complete )    
+          with col1:
+           my_bar.progress(percent_complete )    
        #exec=True 
-          st.write("ffmpeg separando imagens")
+           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")
+          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) 
-          
-          st.image(input_img)
+          with col1:
+           st.image(input_img)
           
           os.system("ls ./_input") 
           if 'myVar' not in globals():
               myVar=""
           st.write("melhorando faces")
-          with st.spinner('Wait for it...'):
+          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")
-          
-          percent_complete= percent_complete+ 30
-          my_bar.progress(percent_complete )   
+          with col1:
+           percent_complete= percent_complete+ 30
+           my_bar.progress(percent_complete )   
          
           os.system("ls ./_output")
           os.system("echo ----")
@@ -54,14 +57,17 @@ def chamada():
           os.system("ls ./_output/restored_imgs")
           os.system("echo ----")
 #          s 1480x2560
-          st.write("recompilando video")
+          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" )
-          st.write("preparando para download do video")
-          percent_complete= percent_complete+ 30
-          my_bar.progress(percent_complete ) 
+          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)
 
@@ -80,12 +86,12 @@ def chamada():
           #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) 
+          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)
+           st.image(input_img)
           exec=False
        #return Image.fromarray(restored_faces[0][:,:,::-1])
 load = st.checkbox("load")