update app.py

app.py

@@ -3,23 +3,49 @@ import rasterio
 import numpy as np
 import matplotlib.pyplot as plt
 import plotly.graph_objs as go
+import logging
+
+# Configure logging for better debugging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 def process_dem(dem_path):
-    # --- OPEN DEM ---
-    with rasterio.open(dem_path.name) as src:
-        dem = src.read(1).astype(float)
+    """
+    Analyzes a DEM file to generate a 2D slope risk map and a 3D interactive plot.
+    """
+    if dem_path is None:
+        return None, None
+        
+    try:
+        # --- OPEN DEM ---
+        logger.info(f"Processing file: {dem_path.name}")
+        with rasterio.open(dem_path.name) as src:
+            dem = src.read(1).astype(float)
+            profile = src.profile
+            logger.info("Successfully opened DEM file.")
+    except rasterio.errors.RasterioIOError as e:
+        logger.error(f"Rasterio error: Failed to open or read the DEM file. Error: {e}")
+        # Return an error message to be displayed by Gradio
+        raise gr.Error("Failed to process the DEM file. Please ensure it is a valid GeoTIFF (.tif) file.")
+    except Exception as e:
+        logger.error(f"An unexpected error occurred during file processing: {e}")
+        raise gr.Error(f"An unexpected error occurred: {e}")
 
     nrows, ncols = dem.shape
     Z = dem
 
     # --- COMPUTE SLOPE ---
-    # Assuming square pixels (ok for visualization)
     dy, dx = np.gradient(Z)
     slope = np.sqrt(dx**2 + dy**2)
 
     # --- RISK MASK ---
-    threshold = np.percentile(slope, 95)  # Top 5% steepest slopes
-    risk_mask = slope > threshold
+    try:
+        threshold = np.percentile(slope, 95)  # Top 5% steepest slopes
+        risk_mask = slope > threshold
+    except IndexError:
+        # Handle case where slope array is empty or too small
+        logger.warning("Slope array is empty, skipping percentile calculation.")
+        risk_mask = np.zeros_like(slope, dtype=bool)
 
     # --- 2D RISK MAP ---
     fig2d, ax = plt.subplots(figsize=(8, 6))
@@ -32,16 +58,16 @@ def process_dem(dem_path):
     risk_map_path = "risk_map.png"
     plt.savefig(risk_map_path, dpi=150, bbox_inches="tight")
     plt.close(fig2d)
+    logger.info("Generated 2D risk map.")
 
     # --- INTERACTIVE 3D DEM (Plotly) ---
     step = max(1, nrows // 200)
-
     fig3d = go.Figure()
 
     # Base DEM surface
     fig3d.add_trace(go.Surface(
         z=Z[::step, ::step],
-        colorscale="Earth",  # similar to matplotlib 'terrain'
+        colorscale="Earth",
         showscale=True,
         opacity=0.9,
         contours=dict(z=dict(show=True, usecolormap=True, highlightcolor="black", project_z=True))
@@ -65,10 +91,10 @@ def process_dem(dem_path):
             aspectmode="data"
         )
     )
+    logger.info("Generated 3D Plotly figure.")
 
     return risk_map_path, fig3d
 
-
 # --- GRADIO APP ---
 demo = gr.Interface(
     fn=process_dem,
@@ -78,8 +104,7 @@ demo = gr.Interface(
         gr.Plot(label="Interactive 3D DEM (with Contours & Risk Zones)")
     ],
     title="3D DEM & Landslide Risk Visualizer",
-    description="Upload a GeoTIFF DEM file to see a 2D slope risk map and an interactive 3D DEM with contours & steep slope zones highlighted."
-)
+    description="Upload a GeoTIFF DEM file to see a 2D slope risk map and an interactive 3D DEM with contours & steep slope zones highlighted.")
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()