remove load dataset button - automatic loading

app.py

@@ -1,5 +1,11 @@
+
+
+Share
+
+
+You said:
 import streamlit as st
-from helper import (
+from helper3 import (
     load_dataset, search, get_file_paths,
     get_cordinates, get_images_from_s3_to_display,
     get_images_with_bounding_boxes_from_s3, load_dataset_with_limit
@@ -13,7 +19,7 @@ AWS_ACCESS_KEY_ID = os.getenv("AWS_ACCESS_KEY_ID")
 AWS_SECRET_ACCESS_KEY = os.getenv("AWS_SECRET_ACCESS_KEY")
 
 # Predefined list of datasets
-datasets = ["MajorTom-Germany", "MajorTom-Netherlands", "WayveScenes"]
+datasets = ["WayveScenes", "MajorTom-Germany", "MajorTom-Netherlands"]
 folder_path_dict = {
     "WayveScenes": "WayveScenes/",
     "MajorTom-Germany": "MajorTOM-DE/",
@@ -40,6 +46,7 @@ example_queries = {
     "MajorTom-UK": "Airports, Golf Courses, Wind Mills, Solar Panels "
 }
 
+
 # AWS S3 bucket name
 bucket_name = "datasets-quasara-io"
 
@@ -83,34 +90,40 @@ def main():
     df, total_rows = load_dataset_with_limit(dataset_name, st.session_state.dataset_number, st.session_state.search_in_small_objects, limit=1)
     dataset_limit = st.slider("Size of Dataset to be searched from", min_value=0, max_value=min(total_rows, 80000), value=int(min(total_rows, 80000)/2))
     st.text(f'The smaller the dataset the faster the search will work.')
-    st.text('Please click Load Dataset to finalize selection for search')
     
+    # Load dataset with limit only if not already loaded
     
-    #Loading Dataset
-    loading_dataset_text = st.empty()
-    loading_dataset_text.text("Loading Dataset...")
-    loading_dataset_bar = st.progress(0)
+    try:
+        loading_dataset_text = st.empty()
+        loading_dataset_text.text("Loading Dataset...")
+        loading_dataset_bar = st.progress(0)
+        
+        
+        # Simulate dataset loading progress
+        for i in range(0, 100, 25):
+            time.sleep(0.2)  # Simulate work being done
+            loading_dataset_bar.progress(i + 25)
+
+        # Load dataset
+        df, total_rows = load_dataset_with_limit(dataset_name, st.session_state.dataset_number, st.session_state.search_in_small_objects, limit=dataset_limit)
+        
+        # Store loaded dataset in session state
+        st.session_state.df = df
+        loading_dataset_bar.progress(100)
+        loading_dataset_text.text("Dataset loaded successfully!")
+        st.success(f"Dataset loaded successfully with {len(df)} rows.")
+            
+            
+    except Exception as e:
+        st.error(f"Failed to load dataset: {e}")
     
-    # Simulate dataset loading progress
-    for i in range(0, 100, 25):
-        time.sleep(0.2)  # Simulate work being done
-        loading_dataset_bar.progress(i + 25)
-
-    # Load dataset
-    df, total_rows = load_dataset_with_limit(dataset_name, st.session_state.dataset_number, st.session_state.search_in_small_objects, limit=dataset_limit)
     
-    # Store loaded dataset in session state
-    st.session_state.df = df
-    loading_dataset_bar.progress(100)
-    loading_dataset_text.text("Dataset loaded successfully!")
-    st.success(f"Dataset loaded successfully with {len(df)} rows.")
-            
-    # After dataset is loaded, show search options
+    # Input search query
     query = st.text_input("Enter your search query")
     st.text(f"Example Queries for your Dataset: {example_queries[dataset_name]}")
     # Number of results to display
-    limit = st.number_input("Number of results to display", min_value=1, max_value=100, value=10)
-            
+    limit = st.number_input("Number of results to display", min_value=1, max_value=10, value=10)
+    
     # Search button
     if st.button("Search"):
         # Validate input
@@ -136,35 +149,23 @@ def main():
                     top_k_paths = get_file_paths(df, results)
                     search_type = 'Main'
 
-                    # Complete the search progress
-                    search_progress_bar.progress(100)
-                    search_loading_text.text(f"Search completed among {dataset_limit} rows for {dataset_name} in {search_type} {st.session_state.dataset_number}")
-
-                    # Load Images with Bounding Boxes if applicable
-                    if st.session_state.search_in_small_objects and top_k_paths and top_k_cordinates:
-                        get_images_with_bounding_boxes_from_s3(bucket_name, top_k_paths, top_k_cordinates, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
-                    elif not st.session_state.search_in_small_objects and top_k_paths:
-                        st.write(f"Displaying top {len(top_k_paths)} results for query '{query}':")
-                        get_images_from_s3_to_display(bucket_name, top_k_paths, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
-                            
-                    else:
-                        st.write("No results found.")
-
-            except Exception as e:
-                if 'None' in e:
-                    st.warning("Please Click Load Dataset")
+                # Complete the search progress
+                search_progress_bar.progress(100)
+                search_loading_text.text(f"Search completed among {dataset_limit} rows for {dataset_name} in {search_type} {st.session_state.dataset_number}")
+
+                # Load Images with Bounding Boxes if applicable
+                if st.session_state.search_in_small_objects and top_k_paths and top_k_cordinates:
+                    get_images_with_bounding_boxes_from_s3(bucket_name, top_k_paths, top_k_cordinates, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
+                elif not st.session_state.search_in_small_objects and top_k_paths:
+                    st.write(f"Displaying top {len(top_k_paths)} results for query '{query}':")
+                    get_images_from_s3_to_display(bucket_name, top_k_paths, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, folder_path)
+                    
                 else:
-                    st.error(f"Search failed: {e}")
-
-
-            
-
-if __name__ == "__main__":
-    main()
-
-            
+                    st.write("No results found.")
 
 
+            except Exception as e:
+                st.error(f"Search failed: {e}")
 
 if __name__ == "__main__":
-    main()
+    main()