Revert "adding bounds"

This reverts commit 1ade128161eac699c3fc6997e813d39d86174c2a.

app.py

@@ -6,7 +6,7 @@ from PIL import Image, ImageDraw
 import gradio as gr
 from openai import OpenAI
 from geopy.geocoders import Nominatim
-from staticmap import StaticMap, CircleMarker, Line, Polygon
+from staticmap import StaticMap, CircleMarker, Polygon
 from diffusers import ControlNetModel, StableDiffusionControlNetInpaintPipeline
 import spaces
 
@@ -110,19 +110,19 @@ def generate_geojson(response):
 @spaces.GPU
 def generate_static_map(geojson_data, bounds=None):
     # Create a static map object with specified dimensions
-    m = StaticMap(500, 500)
+    m = StaticMap(600, 600)
     
-    # if bounds:
-    #     # If bounds are provided, set the center of the map
-    #     center_lat = (bounds[0][0] + bounds[1][0]) / 2
-    #     center_lng = (bounds[0][1] + bounds[1][1]) / 2
-    #     zoom = 10  # Adjust zoom level as needed
-    #     m.set_center(center_lat, center_lng, zoom)
+    if bounds:
+        # If bounds are provided, set the center of the map
+        center_lat = (bounds[0][0] + bounds[1][0]) / 2
+        center_lng = (bounds[0][1] + bounds[1][1]) / 2
+        zoom = 10  # Adjust zoom level as needed
+        m.set_center(center_lat, center_lng, zoom)
     
     # Check if there are no features to avoid an empty map
     if not geojson_data["features"]:
         # Add a small invisible marker to prevent rendering error
-        m.add_marker(Line(bounds, '#FFFFFF', 0))  # White marker with size 0
+        m.add_marker(CircleMarker((0.0, 0.0), '#FFFFFF', 0))  # White marker with size 0
 
     # Process each feature in the GeoJSON
     for feature in geojson_data["features"]:
@@ -209,7 +209,7 @@ def handle_query(query):
         "type": "FeatureCollection",
         "features": []  # Empty map contains no features
     }
-    empty_map_image = generate_static_map(empty_geojson, bounds=bounds)  # Empty map with the same bounds
+    empty_map_image = generate_static_map(empty_geojson)  # Empty map with the same bounds
 
     # Create the mask
     difference = np.abs(np.array(map_image.convert("RGB")) - np.array(empty_map_image.convert("RGB")))