Update app.py

app.py

@@ -25,13 +25,13 @@ import skimage
 from skimage.transform import resize
 import random
 import os
-from io import BytesIO
+from io import BytesIO,StringIO
 import h5py
 
 
 page_names = ["Blurred or Not Blurred Prediction","Occluded or Not Occluded Prediction"]
 page = st.sidebar.radio('Navigation',page_names)
-st.write("Welcome to the Project")
+#st.write("Welcome to the Project")
 
 if page == "Blurred or Not Blurred Prediction":
     st.title("""
@@ -89,7 +89,7 @@ if page == "Blurred or Not Blurred Prediction":
         st.subheader(string)
 else:
     st.title("Prediction of Occluded or not Occluded ")
-    plt. figure(figsize=(10,9))
+    #plt. figure(figsize=(10,9))
     def occ_predict(img_content):
         im = []
         image=cv2.imread(img_content)
@@ -113,7 +113,7 @@ else:
     f = st.file_uploader('Upload an Image',type=(["jpeg","jpg","png"]))
     #st.write(f)
     #st.subheader("Prediction of Occluded or Not Occluded")
-    images1 = ["Occulded.jpg","img1.png","img2.png","img3.png","img4.png"]
+    images1 = ["/img1.png","img2.png","img3.png","img4.png"]
     with st.sidebar:
         st.write("choose an image")
         st.image(images1)
@@ -124,7 +124,7 @@ else:
         image1= Image.open(f)
         st.image(image1,use_column_width = True)
         image_path = f.name
-        predicted_label,variance_score = occ_predict(image_path)
+        predicted_label,variance_score = occ_predict(f)
         #st.header(predicted_label)
         #st.header(str(round(variance_score,2)))
         string1 = "The image is," + predicted_label + " with the score value of  " + str(round(variance_score,2))