Add legend and histogram

app.py

@@ -467,7 +467,7 @@ def get_histogram(index_name, image, geometry, bins):
         return np.array([0] * (len(bins) - 1)), bins
 
 def generate_comparison_maps(geometry_json, selected_index, selected_years, evi_vars, date_start_str, date_end_str, progress=gr.Progress()):
-    """Generates side-by-side maps for a selected index and two selected years with a classified legend."""
+    """Generates side-by-side maps for a selected index and two selected years with a custom HTML legend."""
     if not geometry_json or not selected_index or not selected_years:
         return "Please process a file and select an index and years first.", "", ""
     if len(selected_years) != 2:
@@ -508,16 +508,12 @@ def generate_comparison_maps(geometry_json, selected_index, selected_years, evi_
                 print(f"Could not find a suitable Wayback basemap for {year}: {e}")
                 wayback_url = None
                 wayback_title = "Default Satellite"
-        # --- End Wayback Logic ---
-
+        
         collection = (
             ee.ImageCollection("COPERNICUS/S2_SR_HARMONIZED")
             .filterDate(start_date, end_date)
             .filterBounds(ee_geometry)
-            .select(
-                ["B2", "B3", "B4", "B8"],
-                ["Blue", "Green", "Red", "NIR"]
-            )
+            .select(["B2", "B3", "B4", "B8"], ["Blue", "Green", "Red", "NIR"])
             .map(lambda img: add_indices(img, 'NIR', 'Red', 'Blue', 'Green', evi_vars))
         )
 
@@ -526,59 +522,64 @@ def generate_comparison_maps(geometry_json, selected_index, selected_years, evi_
             continue
 
         mosaic = collection.qualityMosaic(selected_index)
-
-        # Create the base map
         m = gee_folium.Map(zoom_start=14)
         if wayback_url:
             m.add_tile_layer(wayback_url, name=wayback_title, attribution="Esri")
         else:
             m.add_basemap("SATELLITE")
 
-        # --- START: New Legend and Layer Logic ---
+        # --- START: MODIFIED LEGEND AND LAYER LOGIC ---
         if selected_index in ["NDVI", "RandomForest", "GujVDI", "CI", "EVI", "EVI2"]:
-            # Define bins for classification
             bins = [0, 0.2, 0.4, 0.6, 0.8, 1]
-            histogram, bin_edges = get_histogram(selected_index, mosaic.select(selected_index), ee_geometry, bins)
+            histogram, _ = get_histogram(selected_index, mosaic.select(selected_index), ee_geometry, bins)
             
             total_pix = np.sum(histogram)
-            # Format histogram values as percentages, handle division by zero
+            formatted_histogram = ["0.00"] * len(histogram)
             if total_pix > 0:
                 formatted_histogram = [f"{h*100/total_pix:.2f}" for h in histogram]
-            else:
-                formatted_histogram = ["0.00"] * len(histogram)
-
-            # Add the classified legend to the map
-            m.add_legend(
-                title=f"{selected_index} Classification ({year})",
-                legend_dict={
-                    "0-0.2: Open/Sparse Vegetation ({}%)".format(formatted_histogram[0]): "#FF0000",
-                    "0.2-0.4: Low Vegetation ({}%)".format(formatted_histogram[1]): "#FFFF00",
-                    "0.4-0.6: Moderate Vegetation ({}%)".format(formatted_histogram[2]): "#FFA500",
-                    "0.6-0.8: Dense Vegetation ({}%)".format(formatted_histogram[3]): "#00FE00",
-                    "0.8-1: Very Dense Vegetation ({}%)".format(formatted_histogram[4]): "#00A400",
-                },
-                position="bottomright",
-                draggable=False,
-            )
             
             # Define visualization parameters for the classified layer
             ind_vis_params = {
-                "min": 0,
-                "max": 1,
+                "min": 0, "max": 1,
                 "palette": ["#FF0000", "#FFFF00", "#FFA500", "#00FE00", "#00A400"],
             }
-            # Add the classified raster layer to the map
             m.addLayer(mosaic.select(selected_index).clip(ee_geometry), ind_vis_params, f"{selected_index} Classified Layer ({year})")
-        
-        else:  # Fallback for indices without a classified legend (original behavior)
-            vis_params = {
-                "min": 0.0, "max": 1.0,
-                "palette": ['FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901', '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01', '012E01', '011D01', '011301']
+
+            legend_items = {
+                f"0-0.2: Open/Sparse Vegetation ({formatted_histogram[0]}%)": "#FF0000",
+                f"0.2-0.4: Low Vegetation ({formatted_histogram[1]}%)": "#FFFF00",
+                f"0.4-0.6: Moderate Vegetation ({formatted_histogram[2]}%)": "#FFA500",
+                f"0.6-0.8: Dense Vegetation ({formatted_histogram[3]}%)": "#00FE00",
+                f"0.8-1: Very Dense Vegetation ({formatted_histogram[4]}%)": "#00A400",
             }
+
+            legend_html = f'''
+            <div style="
+                position: fixed; 
+                bottom: 20px; 
+                right: 10px; 
+                z-index:9999; 
+                font-size:14px;
+                background-color: rgba(255, 255, 255, 0.85);
+                border:2px solid grey; 
+                padding: 10px;
+                border-radius: 6px;
+                ">
+                <b>{selected_index} Classification ({year})</b>
+                <ul style="list-style-type: none; padding-left: 0; margin: 5px 0 0 0;">
+            '''
+            for text, color in legend_items.items():
+                legend_html += f'<li><i style="background:{color}; width:20px; height:15px; display:inline-block; margin-right:5px; vertical-align:middle; border: 1px solid black;"></i> {text}</li>'
+            legend_html += "</ul></div>"
+            
+            # Add the raw HTML to the map
+            m.get_root().html.add_child(folium.Element(legend_html))
+        
+        else:  # Fallback for indices without a color bar
+            vis_params = {"min": 0.0, "max": 1.0, "palette": ['FFFFFF', 'CE7E45', 'DF923D', 'F1B555', 'FCD163', '99B718', '74A901', '66A000', '529400', '3E8601', '207401', '056201', '004C00', '023B01', '012E01', '011D01', '011301']}
             clipped_image = mosaic.select(selected_index).clip(ee_geometry)
             m.addLayer(clipped_image, vis_params, f"{selected_index} {year}")
             m.add_colorbar(vis_params=vis_params, label=f"{selected_index} Value")
-        # --- END: New Legend and Layer Logic ---
 
         folium.GeoJson(geometry_gdf, name="Geometry", style_function=lambda x: {"color": "yellow", "fillOpacity": 0, "weight": 2.5}).add_to(m)
         m.fit_bounds(map_bounds, padding=(10, 10))
@@ -590,7 +591,7 @@ def generate_comparison_maps(geometry_json, selected_index, selected_years, evi_
 
     return f"Comparison generated for {selected_years[0]} and {selected_years[1]}.", maps_html[0], maps_html[1]
 
-# --- Gradio Interface (unchanged) ---
+# --- Gradio Interface ---
 theme = gr.themes.Soft(primary_hue="teal", secondary_hue="orange").set(
     background_fill_primary="white"
 )