Update app.py

app.py

@@ -1,9 +1,9 @@
 try:
     import detectron2
 except:
-    import os 
     os.system('pip install git+https://github.com/facebookresearch/detectron2.git')
 
+import os
 import streamlit as st
 from PIL import Image
 from matplotlib.pyplot import axis
@@ -186,13 +186,24 @@ def inference(image):
     return img1, img2, img3, parts_list_damages
 
 def main():
+    st.set_page_config(layout="wide")
+    c1, c2 = st.columns((1, 1))
+    c2.markdown("<br><br><br><br><br><br><br><br><br><br><br><br>", unsafe_allow_html=True)
+
+    tab1, tab2, tab3, tab4 = c2.tabs(["Image of damages", "Image of scratches", "Image of parts", "Information about damages parts"])
+
+    # Replace '20px' with your desired font size
+    font_size = '20px'
+
     hide_streamlit_style = """
                 <style>
                 #MainMenu {visibility: hidden;}
                 footer {visibility: hidden;}
                 </style>
                 """
+
     st.markdown(hide_streamlit_style, unsafe_allow_html=True)
+    c1.title('ITACA Insurance Core AI Module')
 
     with st.sidebar:
         image = Image.open('itaca_logo.png')
@@ -205,41 +216,49 @@ def main():
                                 "key"],
                         default_index=0
                         )
-
-        # Additional section below the option menu
-        # st.markdown("---")  # Add a separator line
-        # st.header("Settings")
-        
-    st.title('ITACA Insurance Core AI Module')
-
+  
     if page == "Damage Detection":
-        st.header('Car Parts Damage Detection')
+        c1.header('Car Parts Damage Detection')
 
-        st.write(
+        c1.write(
             """
             """
         )
 
-        uploaded_file = st.file_uploader("Upload an image:")
+        # Display the list of CSV files
+        directory = "./"
+        all_files = os.listdir(directory)
+        # Filter files to only include JPG files
+        jpg_files = [file for file in all_files if file.endswith((".jpg"))]
+
+        # Select an image file from the list
+        selected_jpg = c1.selectbox("Select a JPG file from the list", ["None"] + jpg_files)
+
+        uploaded_file = c1.file_uploader("Upload an image:")
 
         # Check if a file has been uploaded
         if uploaded_file is not None:
             # Load and display the image
             image = Image.open(uploaded_file)
-            st.image(image, caption="Uploaded image")
- 
+            c1.image(image, width=600, caption="Uploaded image")
+
+        elif selected_jpg != 'None':
+            image = Image.open(selected_jpg)
+            c1.image(image, width=600, caption="Uploaded image")
+
         else:
-            st.write("Please upload an image.")
+            c1.write("Please upload an image.")
 
-        if st.button("Prediction"):
+        if c1.button("Prediction"):
             with st.spinner("Loading..."):
-                # Call the inference function with the uploaded image
                 imagen1, imagen2, imagen3, partes = inference(image)
         
-                st.image(imagen1, caption="crash image1")
-                st.image(imagen2, caption="crash image2")
-                st.image(imagen3, caption="crash image3")
-                st.table(partes)
+                c2.markdown("<br><br><br><br><br><br><br><br><br><br><br><br><br><br>", unsafe_allow_html=True)
+
+                tab1.image(imagen1, width=600)
+                tab2.image(imagen2, width=600)
+                tab3.image(imagen3, width=600)
+                tab4.table(partes)
 
     elif page == "Under Construction":
         st.header('Under Construction')