Update app.py

app.py

@@ -73,60 +73,64 @@ def main():
     unsafe_allow_html=True
     )
 
-    uploaded_image = st.file_uploader("Upload Image", type=['png', 'jpg', 'jpeg'])
-
-    # Check if the image is uploaded by the user
-    if uploaded_image is not None:
-        # Convert the uploaded image to an array using the read_image function
-        image = read_image(uploaded_image)
-    
-        # Display the uploaded image
-        st.image(image, caption='Uploaded Image', use_column_width=True)
     
-        # Find similar images
-        similar_images, length = find_similar_images(image)
+
+    image_columns = st.columns(5)
 
     # Define the desired width and height for the resized images
     image_width = 150
     image_height = 150
-    
+
     # Calculate the number of columns based on the available width
     num_columns = 5
-    
+
     # Calculate the number of rows required
     images_per_page = 50
-    num_rows = (images_per_page + num_columns - 1) // num_columns
-
-    # Calculate the total number of pages required
-    total_pages = (length + images_per_page - 1) // images_per_page
 
     # Create a row for the page selector and images
     col1, col2 = st.columns([2, 3])
 
     # Page selector
     with col1:
-        tabs = st.radio(" ", range(1, total_pages + 1))
-
-    # Calculate the range of images to display for the selected page
-    start_index = (tabs - 1) * images_per_page
-    end_index = min(start_index + images_per_page, len(csv_data))
-
-   
-
-    # Loop through each row in the CSV data for the selected page
-    for index in range(start_index, end_index):
-        img_id = df.loc[index, 'seller_img_id']
-        img_path = df.loc[index, 'img_path']
-        product_id = df.loc[index, 'product_id']
-                
-        # Construct the full path to the image
-        full_img_path = img_path
-                
-        # Open and resize the image to the desired dimensions
-        image = read_image(full_img_path)
-        resized_image = image.resize((image_width, image_height))
-                
-        # Determine the column to place the image in
-        col_index = index % num_columns
-        with image_columns[col_index]:
-            st.image(resized_image, caption=f'Product ID: {product_id}\nImage ID: {img_id}', width=image_width)
+        tabs = st.radio(" ", range(1, 11))  # Adjust range as per the requirement
+
+    with col2:
+        # Check if the image is uploaded by the user
+        uploaded_image = st.file_uploader("Upload Image", type=['png', 'jpg', 'jpeg'])
+
+        if uploaded_image is not None:
+            # Convert the uploaded image to an array using the read_image function
+            image = read_image(uploaded_image)
+
+            # Display the uploaded image
+            st.image(image, caption='Uploaded Image', use_column_width=True)
+
+            # Find similar images
+            similar_images, length = find_similar_images(image, df)
+
+            # Calculate the total number of pages required
+            total_pages = (length + images_per_page - 1) // images_per_page
+
+            # Calculate the range of images to display for the selected page
+            start_index = (tabs - 1) * images_per_page
+            end_index = min(start_index + images_per_page, length)
+
+            # Loop through each row in the CSV data for the selected page
+            for index in range(start_index, end_index):
+                img_id = df.loc[index, 'seller_img_id']
+                img_path = df.loc[index, 'img_path']
+                product_id = df.loc[index, 'product_id']
+
+                # Construct the full path to the image
+                full_img_path = img_path
+
+                # Open and resize the image to the desired dimensions
+                image = read_image(full_img_path)
+                resized_image = cv2.resize(image, (image_width, image_height))
+
+                # Determine the column to place the image in
+                col_index = index % num_columns
+                st.image(resized_image, caption=f'Product ID: {product_id}\nImage ID: {img_id}', width=image_width)
+
+if __name__ == '__main__':
+    main()