Update app.py

app.py

@@ -2,7 +2,6 @@ import streamlit as st
 import os
 from PIL import Image
 import numpy as np
-import pickle
 from chatbot import Chatbot  # Assuming you have a chatbot module
 
 # Function to save uploaded file
@@ -19,64 +18,69 @@ def save_uploaded_file(uploaded_file):
 
 # Function to show dashboard content
 def show_dashboard():
-    st.header("Fashion Recommender System")
+    st.title("Fashion Recommender System")
+    st.write("Welcome to our Fashion Recommender System! Upload an image and get personalized product recommendations based on your image and queries.")
+
     chatbot = Chatbot()
     chatbot.load_data()
 
-    # File upload section
-    uploaded_file = st.file_uploader("Choose an image")
-    if uploaded_file is not None:
+    # Load and set up the ResNet model
+    uploaded_file = st.file_uploader("Upload an Image", type=['jpg', 'jpeg', 'png'])
+    
+    if uploaded_file:
         if save_uploaded_file(uploaded_file):
-            # Display the uploaded image
+            st.sidebar.header("Uploaded Image")
             display_image = Image.open(uploaded_file)
-            st.image(display_image)
-
+            st.sidebar.image(display_image, caption='Uploaded Image', use_column_width=True)
+            
             # Generate image caption
             image_path = os.path.join("uploads", uploaded_file.name)
             caption = chatbot.generate_image_caption(image_path)
-            st.write("Generated Caption:", caption)
-
+            st.write("### Generated Caption")
+            st.write(caption)
+            
             # Use caption to get product recommendations
             _, recommended_products = chatbot.generate_response(caption)
 
-            # Display recommended products
+            st.write("### Recommended Products")
             col1, col2, col3, col4, col5 = st.columns(5)
-            with col1:
-                st.image(chatbot.images[recommended_products[0]['corpus_id']])
-            with col2:
-                st.image(chatbot.images[recommended_products[1]['corpus_id']])
-            with col3:
-                st.image(chatbot.images[recommended_products[2]['corpus_id']])
-            with col4:
-                st.image(chatbot.images[recommended_products[3]['corpus_id']])
-            with col5:
-                st.image(chatbot.images[recommended_products[4]['corpus_id']])
-
+            for i, idx in enumerate(recommended_products[:5]):
+                with col1 if i == 0 else col2 if i == 1 else col3 if i == 2 else col4 if i == 3 else col5:
+                    product_image = chatbot.images[idx['corpus_id']]
+                    st.image(product_image, caption=f"Product {i+1}", use_column_width=True)
         else:
-            st.header("Some error occurred in file upload")
+            st.error("Error in uploading the file.")
 
     # Chatbot section
-    user_question = st.text_input("Ask a question:")
+    st.write("### Chat with our Fashion Assistant")
+    user_question = st.text_input("Ask a question about fashion:")
     if user_question:
         bot_response, recommended_products = chatbot.generate_response(user_question)
-        st.write("Chatbot:", bot_response)
+        st.write("**Chatbot Response:**")
+        st.write(bot_response)
 
-        # Display recommended products
+        # Display recommended products based on the user question
+        st.write("**Recommended Products:**")
         for result in recommended_products:
             pid = result['corpus_id']
             product_info = chatbot.product_data[pid]
-            st.write("Product Name:", product_info['productDisplayName'])
-            st.write("Category:", product_info['masterCategory'])
-            st.write("Article Type:", product_info['articleType'])
-            st.write("Usage:", product_info['usage'])
-            st.write("Season:", product_info['season'])
-            st.write("Gender:", product_info['gender'])
-            st.image(chatbot.images[pid])
+            st.write(f"**Product Name:** {product_info['productDisplayName']}")
+            st.write(f"**Category:** {product_info['masterCategory']}")
+            st.write(f"**Article Type:** {product_info['articleType']}")
+            st.write(f"**Usage:** {product_info['usage']}")
+            st.write(f"**Season:** {product_info['season']}")
+            st.write(f"**Gender:** {product_info['gender']}")
+            st.image(chatbot.images[pid], use_column_width=True)
 
 # Main Streamlit app
 def main():
-    # Give title to the app
-    st.title("Fashion Recommender System")
+    # Set page configuration
+    st.set_page_config(
+        page_title="Fashion Recommender System",
+        page_icon=":dress:",
+        layout="wide",
+        initial_sidebar_state="expanded"
+    )
 
     # Show dashboard content directly
     show_dashboard()