Update app.py

app.py

@@ -14,6 +14,7 @@ import numpy as np
 import torchvision.transforms as T
 from PIL import Image,ImageOps,ImageFilter
 from io import BytesIO
+import os
 
 
 
@@ -71,11 +72,9 @@ urllib.request.urlretrieve(MODEL_URL, "popd.pkl")
 path = Path(".")
 learn=load_learner(path, 'popd.pkl')
 
-
-uploaded_file = st.file_uploader("Choose an image...")
-if uploaded_file is not None:
-  img_fast = open_image(uploaded_file)
-  a = PIL.Image.open(uploaded_file).convert('RGB')
+def predict(image):
+  img_fast = open_image(image)
+  a = PIL.Image.open(image).convert('RGB')
   p,img_hr,b = learn.predict(img_fast)
   x = np.minimum(np.maximum(image2np(img_hr.data*255), 0), 255).astype(np.uint8)
   img = PIL.Image.fromarray(x).convert('RGB')
@@ -113,4 +112,34 @@ if uploaded_file is not None:
         for ne in neigh:
           queue.append(ne)
 
-  st.image(img, caption='PoP ArT')
+  return st.image(img, caption='PoP ArT')
+ 
+SIDEBAR_OPTION_DEMO_IMAGE = "Select a Demo Image"
+SIDEBAR_OPTION_UPLOAD_IMAGE = "Upload an Image"
+  
+SIDEBAR_OPTIONS = [SIDEBAR_OPTION_DEMO_IMAGE, SIDEBAR_OPTION_UPLOAD_IMAGE]
+
+
+app_mode = st.sidebar.selectbox("Please select from the following", SIDEBAR_OPTIONS)
+
+if app_mode == SIDEBAR_OPTION_DEMO_IMAGE:
+  st.sidebar.write(" ------ ")
+  directory = os.path.join(Images)
+  photos = []
+  for file in os.listdir(directory):
+    filepath = os.path.join(directory, file)
+    if imghdr.what(filepath) is not None:
+      photos.append(file)
+  photos.sort()
+  option = st.sidebar.selectbox('Please select a sample image, then click Magic Time button', photos)
+  pressed = st.sidebar.button('PoP')
+  if pressed:
+     st.empty()
+     t.sidebar.write('Please wait for the magic to happen! This may take up to a minute.')
+     pic = os.path.join(directory, option)
+     predict(pic)
+
+elif app_mode == SIDEBAR_OPTION_UPLOAD_IMAGE:
+  uploaded_file = st.file_uploader("Choose an image...")
+  if uploaded_file is not None:
+    predict(uploaded_file)