Update app.py

app.py

@@ -25,7 +25,6 @@ def load_spacy_model(model_name="en_core_web_md"):
         return spacy.load(model_name)
 
 
-
 nlp = load_spacy_model()
 
 IMAGE_SIZE = (224, 224)
@@ -63,9 +62,9 @@ def most_frequent_locations(text: str):
         # Format the output to show location names along with their counts
         common_locations_str = ', '.join([f"{loc[0]} ({loc[1]} occurrences)" for loc in most_common_locations])
 
-        return f"Most Mentioned Locations: {common_locations_str}"
+        return f"Most Mentioned Locations: {common_locations_str}", [loc[0] for loc in most_common_locations]
     else:
-        return "No locations found"
+        return "No locations found", []
 
 
 # Transform image for model prediction
@@ -78,6 +77,17 @@ def transform_image(image: Image) -> torch.Tensor:
     return transform(image).unsqueeze(0)
 
 
+def check_location_match(location_query, most_common_locations):
+    name = location_query['name']
+    admin1 = location_query['admin1']
+    cc = location_query['cc']
+
+    for loc in most_common_locations:
+        if name in loc and admin1 in loc and cc in loc:
+            return True
+    return False
+
+
 # Fetch city GeoJSON data
 def get_city_geojson(location_name: str) -> dict:
     geolocator = Nominatim(user_agent="predictGeolocforImage")
@@ -119,6 +129,7 @@ def predict_location(image: Image, model: Geolocalizer) -> tuple:
             st.error(f"Failed to predict the location: {e}")
             return None
 
+
 # Display map in Streamlit
 def display_map(city_geojson: dict, gps_degrees: list) -> None:
     map_view = pdk.Deck(
@@ -175,10 +186,8 @@ def scrape_webpage(url: str) -> tuple:
 
 
 def main():
-
     st.title('Welcome to Geolocation Guesstimation Demo 👋')
 
-
     # Define page navigation using the sidebar
     page = st.sidebar.selectbox(
         "Choose your action:",
@@ -188,16 +197,16 @@ def main():
 
     st.sidebar.success("Select a demo above.")
     st.sidebar.info(
-    """
-    - Web App URL: <https://yunusserhat-guesstimatelocation.hf.space/>
-    """)
+        """
+        - Web App URL: <https://yunusserhat-guesstimatelocation.hf.space/>
+        """)
 
     st.sidebar.title("Contact")
     st.sidebar.info(
-    """
-    Yunus Serhat Bıçakçı at [yunusserhat.com](https://yunusserhat.com) | [GitHub](https://github.com/yunusserhat) | [Twitter](https://twitter.com/yunusserhat) | [LinkedIn](https://www.linkedin.com/in/yunusserhat)
-    """)
-    
+        """
+        Yunus Serhat Bıçakçı at [yunusserhat.com](https://yunusserhat.com) | [GitHub](https://github.com/yunusserhat) | [Twitter](https://twitter.com/yunusserhat) | [LinkedIn](https://www.linkedin.com/in/yunusserhat)
+        """)
+
     if page == "Home":
         st.write("Welcome to the Geolocation Predictor. Please select an action from the sidebar dropdown.")
 
@@ -256,13 +265,15 @@ def social_media_page():
                         if result:
                             gps_degrees, location_query, city_geojson, processing_time = result
                             location_name = f"{location_query['name']}, {location_query['admin1']}, {location_query['cc']}"
-                            st.write(f"City: {location_query['name']}, Region: {location_query['admin1']}, Country: {location_query['cc']}")
+                            st.write(
+                                f"City: {location_query['name']}, Region: {location_query['admin1']}, Country: {location_query['cc']}")
                             if city_geojson:
                                 display_map(city_geojson, gps_degrees)
                                 st.write(f"Processing Time (seconds): {processing_time}")
                             # Check for match and notify
-                            if location_query['name'] in most_common_locations:
-                                st.success(f"The predicted location {location_query['name']} matches the most frequently mentioned location!")
+                            if check_location_match(location_query, most_common_locations):
+                                st.success(
+                                    f"The predicted location {location_name} matches one of the most frequently mentioned locations!")
                 else:
                     st.error(f"Failed to fetch image at URL {media_url}: HTTP {response.status_code}")
 
@@ -271,20 +282,35 @@ def web_page_url_page():
     st.header("Web Page Analyser")
     web_page_url = st.text_input("Enter a web page URL to scrape:", key='web_page_url_input')
     if web_page_url:
-        text, images = scrape_webpage(web_page_url)  # Assume this function is defined elsewhere
+        text, images = scrape_webpage(web_page_url)
         if text:
-            st.subheader("Extracted Text First 500 Chracter:")
+            st.subheader("Extracted Text First 500 Characters:")
             st.write(text[:500])
-            most_used_location = most_frequent_locations(text)
+            most_used_location, most_common_locations = most_frequent_locations(text)
             st.subheader("Most Frequent Location")
             st.write(most_used_location)
-            show_images = st.checkbox('Show Images', key='show_images')
-            if show_images:
-                st.subheader("Images Found")
-                for image_url in images:
-                    display_image(image_url)  # Assumes a function to display images with error handling
-        else:
-            st.write("No data found or unable to parse the webpage.")
+            if images:
+                selected_image_url = st.selectbox("Select an image to predict location:", images)
+                if selected_image_url:
+                    response = requests.get(selected_image_url)
+                    if response.status_code == 200:
+                        image = Image.open(BytesIO(response.content)).convert('RGB')
+                        st.image(image, caption=f'Selected Image from URL: {selected_image_url}', use_column_width=True)
+                        model = load_geoloc_model()
+                        if model:
+                            result = predict_location(image, model)
+                            if result:
+                                gps_degrees, location_query, city_geojson, processing_time = result
+                                location_name = f"{location_query['name']}, {location_query['admin1']}, {location_query['cc']}"
+                                st.write(
+                                    f"City: {location_query['name']}, Region: {location_query['admin1']}, Country: {location_query['cc']}")
+                                if city_geojson:
+                                    display_map(city_geojson, gps_degrees)
+                                    st.write(f"Processing Time (seconds): {processing_time}")
+                                # Check for match and notify
+                                if check_location_match(location_query, most_common_locations):
+                                    st.success(
+                                        f"The predicted location {location_name} matches one of the most frequently mentioned locations!")
 
 
 if __name__ == '__main__':