visualizzazione mappa corretta, controllare misure e rotazioni

config.py

@@ -150,7 +150,7 @@ MAP_SERVICE_PROVIDER = "osm"  # Name of the service to use (must match map_servi
 # MAP_API_KEY = None # Add this if using a service that requires a key (e.g., Google)
 MAP_CACHE_DIRECTORY = "map_cache"  # Root directory for cached tiles
 ENABLE_ONLINE_MAP_FETCHING = True  # Allow downloading tiles if not in cache
-DEFAULT_MAP_ZOOM_LEVEL = 12  # Initial zoom level for the test map (adjust as needed)
+DEFAULT_MAP_ZOOM_LEVEL = 14  # Initial zoom level for the test map (adjust as needed) 12 original, 13 little more big, 
 # Color for placeholder tiles when offline/download fails (RGB tuple)
 OFFLINE_MAP_PLACEHOLDER_COLOR = (200, 200, 200)  # Light grey
 MAX_MAP_DISPLAY_WIDTH = 1024
@@ -158,8 +158,12 @@ MAX_MAP_DISPLAY_HEIGHT = 1024
 
 
 # SAR Georeferencing Defaults (Now explicitly used for map testing if ENABLE_MAP_OVERLAY is True)
-SAR_CENTER_LAT = 40.7128  # Example: New York City Latitude (Degrees)
+# SAR Georeferencing Defaults
-SAR_CENTER_LON = -74.0060  # Example: New York City Longitude (Degrees)
+# NOTE: Setting LAT/LON to 0.0 signals the MapIntegrationManager *NOT*
+#       to display an initial default map area on startup.
+#       The map will only appear after the first valid GeoInfo is received.
+SAR_CENTER_LAT = 0.0 #40.7128  # Example: New York City Latitude (Degrees)
+SAR_CENTER_LON = 0.0 #-74.0060  # Example: New York City Longitude (Degrees)
 SAR_IMAGE_SIZE_KM = (
     50.0  # Example: Width/Height of the area to show on the map in Kilometers
 )

map_integration.py

@@ -14,7 +14,7 @@ import logging
 import threading
 import queue # For type hinting
 import math
-from typing import Optional, Dict, Any, Tuple
+from typing import Optional, Dict, Any, Tuple, List
 
 # Third-party imports
 import numpy as np
@@ -31,6 +31,8 @@ try:
 except ImportError:
     pyproj = None
     
+import cv2
+
 # Local application imports
 import config
 from app_state import AppState
@@ -143,79 +145,105 @@ class MapIntegrationManager:
 
 
     def _display_initial_map_area_thread(self):
-        """
+            """
-        (Runs in background thread) Calculates the initial map area based on default
+            (Runs in background thread) Calculates the initial map area based on default
-        config settings and queues the result for display on the main thread.
+            config settings and queues the result for display on the main thread,
-        Moved from App._display_initial_map_area.
+            *unless* the default coordinates in config are set to (0,0) which signals
-        """
+            to skip the initial display.
-        log_prefix = f"{self._log_prefix} InitialMap"
+            """
-        # Check dependencies initialized in __init__
+            log_prefix = f"{self._log_prefix} InitialMap"
-        if not (self._map_tile_manager and self._map_display_window):
-             # This check might be redundant if __init__ raises exceptions, but keep for safety
-             logging.error(f"{log_prefix} Map components not initialized. Aborting thread.")
-             # Queue None to signal failure to the main thread?
-             put_queue(self._tkinter_queue, ('SHOW_MAP', None), "tkinter", self._app)
-             return
-        # Check shutdown flag early
-        if self._app_state.shutting_down:
-             logging.info(f"{log_prefix} Shutdown detected. Aborting.")
-             return
 
-        logging.info(f"{log_prefix} Calculating initial map area...")
+            # Check if default lat/lon are set to 0.0 to prevent initial display
-        map_image_pil: Optional[Image.Image] = None
+            if config.SAR_CENTER_LAT == 0.0 and config.SAR_CENTER_LON == 0.0:
-        try:
+                # ... (codice per saltare e aggiornare lo stato, come prima) ...
-            # Use default center/size from config for the initial view
+                # ... (assicurati che questa parte sia corretta come nella risposta precedente) ...
-            bbox = get_bounding_box_from_center_size(
+                logging.info(f"{log_prefix} Initial map display skipped based on config defaults (0,0). Waiting for valid GeoInfo.")
-                config.SAR_CENTER_LAT, config.SAR_CENTER_LON, config.SAR_IMAGE_SIZE_KM
+                if not self._app_state.shutting_down:
-            )
+                    status_msg = "Status Unavailable" # Default
-            if bbox is None:
+                    try:
-                raise MapCalculationError("Failed to calculate initial bounding box.")
+                        if self._app_state.test_mode_active:
+                             status_msg = "Ready (Test Mode)"
+                        elif config.USE_LOCAL_IMAGES:
+                             status_msg = "Ready (Local Mode)"
+                        else:
+                            socket_ok = False
+                            listening_info = "Error: No Network Socket"
+                            if hasattr(self._app, 'udp_socket') and self._app.udp_socket:
+                                if hasattr(self._app, 'local_ip') and hasattr(self._app, 'local_port'):
+                                    listening_info = f"Listening UDP {self._app.local_ip}:{self._app.local_port}"
+                                    socket_ok = True
+                                else:
+                                    listening_info = "Listening UDP (IP/Port Unknown)"
+                                    socket_ok = True
+                            status_msg = listening_info
+                        status_msg += " | Map Ready (Waiting for GeoData)"
+                    except Exception as e:
+                        logging.exception(f"{log_prefix} Unexpected error determining status message:")
+                        status_msg = "Error Getting Status | Map Ready (Waiting for GeoData)"
+                    self._app.set_status(status_msg)
+                return # Esce dal thread
 
-            zoom = config.DEFAULT_MAP_ZOOM_LEVEL
+            # Se le coordinate di default *non* sono (0,0), procedi
-            tile_ranges = get_tile_ranges_for_bbox(bbox, zoom)
+            logging.info(f"{log_prefix} Calculating initial map area based on non-zero config defaults...")
-            if tile_ranges is None:
-                raise MapCalculationError("Failed to calculate initial tile ranges.")
 
-            # --- Check shutdown again before potentially long tile stitching ---
+            # Check dependencies
+            if not (self._map_tile_manager and self._map_display_window):
+                 logging.error(f"{log_prefix} Map components not initialized. Aborting thread.")
+                 put_queue(self._tkinter_queue, ('SHOW_MAP', None), "tkinter", self._app)
+                 return
             if self._app_state.shutting_down:
-                logging.info(f"{log_prefix} Shutdown detected before stitching.")
+                 logging.info(f"{log_prefix} Shutdown detected. Aborting.")
-                return
+                 return
 
-            logging.info(f"{log_prefix} Stitching initial map tiles (Zoom: {zoom}, X: {tile_ranges[0]}, Y: {tile_ranges[1]})...")
+            map_image_pil: Optional[Image.Image] = None
-            map_image_pil = self._map_tile_manager.stitch_map_image(
+            try:
-                zoom, tile_ranges[0], tile_ranges[1]
+                # --- MODIFICA QUI: Definisci 'zoom' PRIMA di usarlo ---
-            ) # stitch_map_image uses placeholders internally if needed
+                zoom = config.DEFAULT_MAP_ZOOM_LEVEL
+                logging.debug(f"{log_prefix} Using default zoom level: {zoom}")
+                # --- FINE MODIFICA ---
 
-            # --- Check shutdown again after stitching ---
+                # Usa default center/size da config
-            if self._app_state.shutting_down:
+                bbox = get_bounding_box_from_center_size(
-                logging.info(f"{log_prefix} Shutdown detected after stitching.")
+                    config.SAR_CENTER_LAT, config.SAR_CENTER_LON, config.SAR_IMAGE_SIZE_KM
-                # Don't queue result if shutting down
+                )
-                return
+                if bbox is None:
+                    raise MapCalculationError("Failed to calculate initial bounding box.")
 
-            if map_image_pil:
+                # Calcola i tile ranges USANDO la variabile zoom definita sopra
-                logging.info(f"{log_prefix} Initial map area stitched successfully.")
+                tile_ranges = get_tile_ranges_for_bbox(bbox, zoom)
-            else:
+                if tile_ranges is None:
-                # This case should be less likely if stitch_map_image uses placeholders
+                    raise MapCalculationError("Failed to calculate initial tile ranges.")
-                logging.error(f"{log_prefix} Failed to stitch initial map area (returned None even with placeholders).")
 
-        except ImportError as e:
+                if self._app_state.shutting_down:
-             # Should be caught by __init__, but handle defensively
+                    logging.info(f"{log_prefix} Shutdown detected before stitching.")
-             logging.critical(f"{log_prefix} Missing library during map calculation: {e}")
+                    return
-             map_image_pil = None # Ensure None is queued on error
+
-        except MapCalculationError as e:
+                # Ora puoi usare 'zoom' nel messaggio di log
-             logging.error(f"{log_prefix} Calculation error: {e}")
+                logging.info(f"{log_prefix} Stitching initial map tiles (Zoom: {zoom}, X: {tile_ranges[0]}, Y: {tile_ranges[1]})...")
-             map_image_pil = None # Ensure None is queued on error
+                map_image_pil = self._map_tile_manager.stitch_map_image(
-        except Exception as e:
+                    zoom, tile_ranges[0], tile_ranges[1]
-             logging.exception(f"{log_prefix} Unexpected error calculating initial map:")
+                )
-             map_image_pil = None # Ensure None is queued on error
+
-        finally:
+                if self._app_state.shutting_down:
-            # Always queue the result (PIL image or None) for the main thread to handle display
+                    logging.info(f"{log_prefix} Shutdown detected after stitching.")
-            # Check shutdown one last time before queueing
+                    return
-            if not self._app_state.shutting_down:
+
-                logging.debug(f"{log_prefix} Queueing SHOW_MAP command for main thread.")
+                if map_image_pil:
-                # The payload is the PIL image (or None)
+                    logging.info(f"{log_prefix} Initial map area stitched successfully.")
-                put_queue(self._tkinter_queue, ('SHOW_MAP', map_image_pil), "tkinter", self._app)
+                else:
-            logging.debug(f"{log_prefix} Initial map display thread finished.")
+                    logging.error(f"{log_prefix} Failed to stitch initial map area.")
+
+            except (ImportError, MapCalculationError) as e:
+                 logging.error(f"{log_prefix} Calculation error: {e}")
+                 map_image_pil = None
+            except Exception as e:
+                 logging.exception(f"{log_prefix} Unexpected error calculating initial map:")
+                 map_image_pil = None
+            finally:
+                if not self._app_state.shutting_down:
+                    logging.debug(f"{log_prefix} Queueing SHOW_MAP command for initial map.")
+                    put_queue(self._tkinter_queue, ('SHOW_MAP', map_image_pil), "tkinter", self._app)
+                logging.debug(f"{log_prefix} Initial map display thread finished.")
 
 
     def update_map_overlay(self, sar_normalized_uint8: np.ndarray, geo_info_radians: Dict[str, Any]):
@@ -276,8 +304,12 @@ class MapIntegrationManager:
             # Calculate size in KM, using default from config as fallback
             if scale_x > 0 and width_px > 0:
                  size_km = (scale_x * width_px) / 1000.0
+                 logging.info(f"{log_prefix} Calculated approximate size based on scale_x * width_px: {size_km:.2f} km")
             else:
-                 logging.warning(f"{log_prefix} Using default SAR size for map due to invalid scale/width in GeoInfo.")
+                 logging.error(
+                     f"{log_prefix} Invalid scale_x ({scale_x}) or width_px ({width_px}) in received GeoInfo. "
+                     f"Cannot determine map size from data. Using fallback default size: {config.SAR_IMAGE_SIZE_KM} km."
+                 )
                  size_km = config.SAR_IMAGE_SIZE_KM
             # Get zoom level from config
             zoom = config.DEFAULT_MAP_ZOOM_LEVEL
@@ -433,5 +465,222 @@ class MapIntegrationManager:
 
         logging.info(f"{log_prefix} Map integration shutdown complete.")
         
+    def _calculate_sar_corners_geo(
+        self, geo_info: Dict[str, Any]
+    ) -> Optional[List[Tuple[float, float]]]:
+        """
+        Calculates the geographic coordinates (latitude, longitude in degrees)
+        of the four corners of the SAR image based on its georeferencing info.
+
+        Args:
+            geo_info (Dict[str, Any]): The georeferencing dictionary from AppState.
+                                       Expects keys like 'lat', 'lon', 'orientation' (radians),
+                                       'ref_x', 'ref_y', 'scale_x', 'scale_y', 'width_px', 'height_px'.
+
+        Returns:
+            Optional[List[Tuple[float, float]]]: A list of four (lon, lat) tuples in degrees
+                                                 representing the corners (e.g., TL, TR, BR, BL),
+                                                 or None on error.
+        """
+        log_prefix = f"{self._log_prefix} SAR Corners Geo"
+        logging.debug(f"{log_prefix} Calculating SAR corner geographic coordinates...")
+
+        if not self._geod:
+             logging.error(f"{log_prefix} Geodetic calculator (pyproj.Geod) not initialized.")
+             return None
+
+        try:
+            # Extract necessary info (ensure keys exist and values are valid)
+            center_lat_rad = geo_info['lat']
+            center_lon_rad = geo_info['lon']
+            orient_rad = geo_info['orientation']
+            ref_x = geo_info['ref_x']
+            ref_y = geo_info['ref_y']
+            scale_x = geo_info['scale_x'] # meters/pixel
+            scale_y = geo_info['scale_y'] # meters/pixel
+            width = geo_info['width_px']
+            height = geo_info['height_px']
+
+            if not (scale_x > 0 and scale_y > 0 and width > 0 and height > 0):
+                 logging.error(f"{log_prefix} Invalid scale or dimensions in geo_info.")
+                 return None
+
+            # 1. Calculate pixel coordinates of corners relative to the reference pixel (ref_x, ref_y)
+            #    Origin (0,0) is top-left. Y increases downwards in pixel space.
+            corners_pixel = [
+                (0 - ref_x, ref_y - 0),           # Top-Left (dx, dy relative to ref, y inverted)
+                (width - 1 - ref_x, ref_y - 0),   # Top-Right
+                (width - 1 - ref_x, ref_y - (height - 1)), # Bottom-Right
+                (0 - ref_x, ref_y - (height - 1)) # Bottom-Left
+            ]
+
+            # 2. Convert pixel offsets to meter offsets
+            corners_meters = [
+                (dx * scale_x, dy * scale_y) for dx, dy in corners_pixel
+            ] # (delta_meters_east, delta_meters_north)
+
+            # 3. Apply inverse rotation to meter offsets if necessary
+            #    The map needs the *geographic* corners, so we need to find where
+            #    the image corners land geographically. We start from the geo center
+            #    and calculate the destination point by applying the *rotated* meter offsets.
+            corners_meters_rotated = []
+            if abs(orient_rad) > 1e-6: # Apply rotation if significant
+                 cos_o = math.cos(orient_rad)
+                 sin_o = math.sin(orient_rad)
+                 for dx_m, dy_m in corners_meters:
+                      # Rotate the offset vector (dx_m, dy_m) by orient_rad
+                      rot_dx = dx_m * cos_o - dy_m * sin_o
+                      rot_dy = dx_m * sin_o + dy_m * cos_o
+                      corners_meters_rotated.append((rot_dx, rot_dy))
+                 logging.debug(f"{log_prefix} Applied rotation ({math.degrees(orient_rad):.2f} deg) to meter offsets.")
+            else:
+                 corners_meters_rotated = corners_meters # No rotation needed
+                 logging.debug(f"{log_prefix} Skipping rotation for meter offsets (angle near zero).")
+
+
+            # 4. Calculate geographic coordinates of corners using pyproj.Geod.fwd
+            #    This requires calculating distance and azimuth from the center to each rotated meter offset.
+            sar_corners_geo_deg = []
+            for dx_m_rot, dy_m_rot in corners_meters_rotated:
+                # Calculate distance from center (0,0) in rotated meter space
+                distance_m = math.sqrt(dx_m_rot**2 + dy_m_rot**2)
+                # Calculate azimuth from center (North=0, East=90)
+                # atan2(dx, dy) gives angle relative to North axis
+                azimuth_rad = math.atan2(dx_m_rot, dy_m_rot)
+                azimuth_deg = math.degrees(azimuth_rad)
+
+                # Use geod.fwd from the known center lat/lon (radians needed for input?)
+                # pyproj fwd expects degrees for lon, lat, az
+                center_lon_deg = math.degrees(center_lon_rad)
+                center_lat_deg = math.degrees(center_lat_rad)
+
+                # Calculate the destination point
+                endlon, endlat, _ = self._geod.fwd(center_lon_deg, center_lat_deg, azimuth_deg, distance_m)
+
+                # Append (lon, lat) tuple in degrees
+                sar_corners_geo_deg.append((endlon, endlat))
+                logging.debug(f"{log_prefix} Calculated corner: Dist={distance_m:.1f}m, Az={azimuth_deg:.2f}deg -> Lon={endlon:.6f}, Lat={endlat:.6f}")
+
+            if len(sar_corners_geo_deg) != 4:
+                 logging.error(f"{log_prefix} Failed to calculate all 4 corner coordinates.")
+                 return None
+
+            logging.info(f"{log_prefix} Successfully calculated 4 SAR corner geographic coordinates.")
+            return sar_corners_geo_deg
+
+        except KeyError as ke:
+             logging.error(f"{log_prefix} Missing required key in geo_info: {ke}")
+             return None
+        except Exception as e:
+             logging.exception(f"{log_prefix} Error calculating SAR corner coordinates:")
+             return None
+
+    # --- NUOVA FUNZIONE HELPER (SCHELETRO/PLACEHOLDER) ---
+    def _geo_coords_to_map_pixels(
+        self,
+        coords_deg: List[Tuple[float, float]],
+        map_bounds: mercantile.LngLatBbox,
+        map_tile_ranges: Tuple[Tuple[int, int], Tuple[int, int]],
+        zoom: int,
+        stitched_map_shape: Tuple[int, int] # (height, width)
+    ) -> Optional[List[Tuple[int, int]]]:
+        """
+        Converts a list of geographic coordinates (lon, lat degrees) to pixel
+        coordinates (x, y) relative to the top-left corner of the stitched map image.
+
+        Args:
+            coords_deg (List[Tuple[float, float]]): List of (longitude, latitude) tuples in degrees.
+            map_bounds (mercantile.LngLatBbox): Geographic bounds of the *top-left tile* used for stitching.
+                                                Used as the reference for pixel conversion.
+            map_tile_ranges (Tuple[Tuple[int, int], Tuple[int, int]]): ((min_x, max_x), (min_y, max_y)) tile indices.
+            zoom (int): The zoom level of the map tiles.
+            stitched_map_shape (Tuple[int, int]): The shape (height, width) of the stitched map image in pixels.
+
+        Returns:
+            Optional[List[Tuple[int, int]]]: List of (x, y) pixel coordinates corresponding
+                                             to the input geographic coordinates, relative to the
+                                             top-left of the stitched map image. Returns None on error.
+        """
+        log_prefix = f"{self._log_prefix} Geo to Pixel"
+        logging.debug(f"{log_prefix} Converting {len(coords_deg)} geo coordinates to map pixels...")
+
+        if mercantile is None:
+             logging.error(f"{log_prefix} Mercantile library not available.")
+             return None
+        if not stitched_map_shape or stitched_map_shape[0] <= 0 or stitched_map_shape[1] <= 0:
+             logging.error(f"{log_prefix} Invalid stitched map shape: {stitched_map_shape}")
+             return None
+
+        pixel_coords = []
+        map_height_px, map_width_px = stitched_map_shape
+        # Tile size from config or service? Assume 256 for mercantile functions
+        tile_size = self._map_service.tile_size if self._map_service else 256
+
+        try:
+            # Get the coordinates of the top-left corner of the entire stitched map in the world pixel space (at the given zoom)
+            # This is the top-left corner of the top-left tile (min_x, min_y)
+            min_tile_x = map_tile_ranges[0][0]
+            min_tile_y = map_tile_ranges[1][0]
+            # mercantile.xy_bounds(tile) gives bounds in projected meters, not pixels
+            # We need the pixel coordinates using mercantile.xy() perhaps?
+
+            # Let's try converting each geographic point to its world pixel coordinate at the given zoom
+            # and then find its position relative to the top-left corner of our stitched map area.
+
+            # Calculate the world pixel coordinate (at zoom level) of the top-left corner of our stitched map area
+            # This corresponds to the top-left of tile (min_tile_x, min_tile_y)
+            tl_tile_bounds = mercantile.xy_bounds(min_tile_x, min_tile_y, zoom)
+            # mercantile.xy() converts lon/lat to projected meters (Web Mercator)
+            # We need a function to convert lon/lat directly to *tile pixel coordinates* or *world pixel coordinates*
+            # mercantile doesn't seem to offer this directly. We might need to implement the math:
+            # https://developers.google.com/maps/documentation/javascript/examples/map-coordinates
+
+            # --- Alternative Approach using mercantile.xy and relating to tile bounds ---
+            # 1. Find the projected meter coordinates (Web Mercator) of the top-left corner of the stitched area.
+            tl_tile_mercator_bounds = mercantile.xy_bounds(min_tile_x, min_tile_y, zoom)
+            map_origin_x_mercator = tl_tile_mercator_bounds.left
+            map_origin_y_mercator = tl_tile_mercator_bounds.top # Top has higher Y in Mercator
+
+            # 2. Calculate the total span of the stitched map in Mercator meters
+            max_tile_x = map_tile_ranges[0][1]
+            max_tile_y = map_tile_ranges[1][1]
+            br_tile_mercator_bounds = mercantile.xy_bounds(max_tile_x, max_tile_y, zoom)
+            map_total_width_mercator = br_tile_mercator_bounds.right - map_origin_x_mercator
+            map_total_height_mercator = map_origin_y_mercator - br_tile_mercator_bounds.bottom # Top Y > Bottom Y
+
+            if map_total_width_mercator <= 0 or map_total_height_mercator <=0:
+                 logging.error(f"{log_prefix} Invalid map span in Mercator coordinates calculated.")
+                 return None
+
+            # 3. For each input geographic coordinate:
+            for lon, lat in coords_deg:
+                # a. Convert geo coord to Mercator meters
+                point_x_mercator, point_y_mercator = mercantile.xy(lon, lat)
+
+                # b. Calculate the coordinate relative to the map's top-left origin in Mercator meters
+                relative_x_mercator = point_x_mercator - map_origin_x_mercator
+                relative_y_mercator = map_origin_y_mercator - point_y_mercator # Invert Y difference
+
+                # c. Scale the relative Mercator coordinates to pixel coordinates based on the total map span and pixel dimensions
+                pixel_x = int(round((relative_x_mercator / map_total_width_mercator) * map_width_px))
+                pixel_y = int(round((relative_y_mercator / map_total_height_mercator) * map_height_px))
+
+                # Clamp pixel coordinates to be within the stitched map bounds
+                pixel_x_clamped = max(0, min(pixel_x, map_width_px - 1))
+                pixel_y_clamped = max(0, min(pixel_y, map_height_px - 1))
+
+                if pixel_x != pixel_x_clamped or pixel_y != pixel_y_clamped:
+                     logging.warning(f"{log_prefix} Clamped pixel coords for ({lon:.4f},{lat:.4f}): ({pixel_x},{pixel_y}) -> ({pixel_x_clamped},{pixel_y_clamped})")
+
+                pixel_coords.append((pixel_x_clamped, pixel_y_clamped))
+                logging.debug(f"{log_prefix} Converted ({lon:.4f},{lat:.4f}) -> MercatorRel({relative_x_mercator:.1f},{relative_y_mercator:.1f}) -> Pixel({pixel_x_clamped},{pixel_y_clamped})")
+
+            logging.info(f"{log_prefix} Successfully converted {len(pixel_coords)} coordinates to map pixels.")
+            return pixel_coords
+
+        except Exception as e:
+            logging.exception(f"{log_prefix} Error converting geo coordinates to map pixels:")
+            return None
+
 
 # --- END OF FILE map_integration.py ---

receiver.py

@@ -644,7 +644,8 @@ class UdpReceiver:
     def reassemble_sar_image(self, image_leader, image_data, log_prefix):
         """
         Extracts SAR metadata and pixel data (normalized uint8) from buffer.
-        Handles corrected radian interpretation for orientation.
+        Interprets ORIENTATION, LATITUDE, and LONGITUDE as RADIANS directly from the buffer
+        based on TN-IMGSER specification.
 
         Args:
             image_leader (ImageLeaderData): Parsed leader structure.
@@ -660,7 +661,7 @@ class UdpReceiver:
         image_key_log = f"SAR(FCNT={fcounter})"  # For specific logs within this func
 
         try:
-            # 1. Extract and validate HeaderData - DEBUG for details
+            # 1. Extract and validate HeaderData
             hdr_d = image_leader.HEADER_DATA
             dx, dy, bpp = int(hdr_d.DX), int(hdr_d.DY), int(hdr_d.BPP)
             stride_pixels, pal_type = int(hdr_d.STRIDE), int(hdr_d.PALTYPE)
@@ -674,7 +675,6 @@ class UdpReceiver:
                 or stride_pixels < dx
                 or pal_type != 0
             ):
-                # ERROR for invalid metadata
                 logging.error(
                     f"{log_prefix} {image_key_log}: Invalid SAR metadata. Cannot reassemble."
                 )
@@ -683,21 +683,18 @@ class UdpReceiver:
             pixel_dtype = np.uint8 if bpp == 1 else np.uint16
             pixel_bytes = bpp
 
-            # 2. Calculate pixel offset - DEBUG for offset calc
+            # 2. Calculate pixel offset
-            pixel_data_offset = self._calculate_pixel_data_offset(
+            pixel_data_offset = self._calculate_pixel_data_offset(image_leader)
-                image_leader
-            )  # Logs internally
             logging.debug(
                 f"{log_prefix} {image_key_log}: Using pixel data offset: {pixel_data_offset}"
             )
 
-            # 3. Validate offset and buffer size - DEBUG for validation steps
+            # 3. Validate offset and buffer size
             available_data_length = len(image_data)
             logging.debug(
                 f"{log_prefix} {image_key_log}: Validating offset ({pixel_data_offset}) vs buffer size ({available_data_length})."
             )
             if pixel_data_offset >= available_data_length:
-                # ERROR if offset invalid
                 logging.error(
                     f"{log_prefix} {image_key_log}: Pixel offset >= buffer size. Cannot extract pixel data."
                 )
@@ -705,14 +702,13 @@ class UdpReceiver:
             minimum_required_core_bytes = dy * dx * pixel_bytes
             actual_pixel_bytes_available = available_data_length - pixel_data_offset
             if actual_pixel_bytes_available < minimum_required_core_bytes:
-                # ERROR if insufficient data
                 logging.error(
                     f"{log_prefix} {image_key_log}: Insufficient pixel data in buffer (Need min {minimum_required_core_bytes}, Found {actual_pixel_bytes_available})."
                 )
                 return None
             logging.debug(f"{log_prefix} {image_key_log}: Buffer size validated.")
 
-            # 4. Create NumPy view - DEBUG for view creation attempt
+            # 4. Create NumPy view
             try:
                 stride_bytes = stride_pixels * pixel_bytes
                 logging.debug(
@@ -729,7 +725,6 @@ class UdpReceiver:
                     f"{log_prefix} {image_key_log}: NumPy view created successfully."
                 )
             except ValueError as ve:
-                # ERROR for view creation failure
                 logging.error(
                     f"{log_prefix} {image_key_log}: Failed to create SAR NumPy view (Shape/stride/offset mismatch?): {ve}"
                 )
@@ -742,15 +737,14 @@ class UdpReceiver:
                 )
                 return None
 
-            # 6. Normalize image view to uint8 - DEBUG for normalization step
+            # 6. Normalize image view to uint8
             logging.debug(
                 f"{log_prefix} {image_key_log}: Normalizing SAR view to uint8..."
             )
             normalized_image_uint8 = normalize_image(
                 sar_image_view, target_type=np.uint8
-            )  # Logs internally
+            )
             if normalized_image_uint8 is None:
-                # ERROR for normalization failure
                 logging.error(
                     f"{log_prefix} {image_key_log}: SAR normalization to uint8 failed."
                 )
@@ -759,27 +753,26 @@ class UdpReceiver:
                 f"{log_prefix} {image_key_log}: Normalization complete (Shape: {normalized_image_uint8.shape})."
             )
 
-            # 7. Extract and Convert Geo Info (RADIANS) - Use specific prefix
+            # --- MODIFICATION START: Correct reading of GeoData fields as Radians ---
+            # 7. Extract and Validate Geo Info (RADIANS)
             geo_log_prefix = "[Geo extract]"
-            geo_info_radians = {"valid": False}
+            geo_info_radians = {"valid": False}  # Initialize as invalid
             try:
                 geo_d = image_leader.GEO_DATA
                 logging.debug(
-                    f"{geo_log_prefix} {image_key_log}: Extracting and interpreting GeoData (Orientation as RADIANS)..."
+                    f"{geo_log_prefix} {image_key_log}: Extracting GeoData (interpreting ORIENTATION, LATITUDE, LONGITUDE as RADIANS)..."
                 )
 
-                # Read orientation directly as RADIANS (corrected)
+                # Read ORIENTATION, LATITUDE, LONGITUDE directly as RADIANS
-                orient_rad_raw = float(geo_d.ORIENTATION)
+                # (Assuming they are stored as float representing radians in the buffer)
-                # Read lat/lon as DEGREES (from structure assumption) and convert
+                lat_rad = float(geo_d.LATITUDE)
-                lat_deg_raw = float(geo_d.LATITUDE)
+                lon_rad = float(geo_d.LONGITUDE)
-                lon_deg_raw = float(geo_d.LONGITUDE)
+                orient_rad = float(geo_d.ORIENTATION)
-                lat_rad = math.radians(lat_deg_raw)
-                lon_rad = math.radians(lon_deg_raw)
 
-                # Store RADIANS internally
+                # Store RADIANS directly in the dictionary
                 geo_info_radians["lat"] = lat_rad
                 geo_info_radians["lon"] = lon_rad
-                geo_info_radians["orientation"] = orient_rad_raw
+                geo_info_radians["orientation"] = orient_rad
                 geo_info_radians["ref_x"] = int(geo_d.REF_X)
                 geo_info_radians["ref_y"] = int(geo_d.REF_Y)
                 geo_info_radians["scale_x"] = float(geo_d.SCALE_X)
@@ -787,45 +780,54 @@ class UdpReceiver:
                 geo_info_radians["width_px"] = dx
                 geo_info_radians["height_px"] = dy
 
-                # Validate scale - DEBUG for validation result
+                # Validate scale and basic lat/lon/orient ranges (radians)
-                if geo_info_radians["scale_x"] > 0 and geo_info_radians["scale_y"] > 0:
+                # Basic range check: lat [-pi/2, pi/2], lon [-pi, pi]
+                is_scale_valid = (
+                    geo_info_radians["scale_x"] > 0 and geo_info_radians["scale_y"] > 0
+                )
+                is_lat_valid = -math.pi / 2 <= lat_rad <= math.pi / 2
+                is_lon_valid = -math.pi <= lon_rad <= math.pi
+                # Orientation check can be less strict, maybe check finite?
+                is_orient_valid = math.isfinite(orient_rad)
+
+                if is_scale_valid and is_lat_valid and is_lon_valid and is_orient_valid:
                     geo_info_radians["valid"] = True
-                    # Log extracted values (DEBUG controlled by DEBUG_RECEIVER_GEO)
+                    # Log extracted values (convert to degrees *only for logging* if needed)
-                    orient_deg_for_log = math.degrees(orient_rad_raw)
+                    lat_deg_log = math.degrees(lat_rad)
+                    lon_deg_log = math.degrees(lon_rad)
+                    orient_deg_log = math.degrees(orient_rad)
                     logging.debug(
                         f"{geo_log_prefix} {image_key_log}: GeoInfo Extracted: Valid={geo_info_radians['valid']}, "
-                        f"Lat={lat_deg_raw:.4f}deg({lat_rad:.6f}rad), Lon={lon_deg_raw:.4f}deg({lon_rad:.6f}rad), "
+                        f"Lat={lat_deg_log:.4f}deg({lat_rad:.6f}rad), Lon={lon_deg_log:.4f}deg({lon_rad:.6f}rad), "
-                        f"Orient={orient_deg_for_log:.2f}deg({orient_rad_raw:.6f}rad), "
+                        f"Orient={orient_deg_log:.2f}deg({orient_rad:.6f}rad), "
                         f"Ref=({geo_info_radians['ref_x']},{geo_info_radians['ref_y']}), "
                         f"Scale=({geo_info_radians['scale_x']:.3f},{geo_info_radians['scale_y']:.3f}), "
                         f"Size=({dx},{dy})"
                     )
                 else:
-                    # WARNING for invalid scale marking Geo invalid
                     logging.warning(
-                        f"{geo_log_prefix} {image_key_log}: Invalid scale values found (ScaleX={geo_info_radians['scale_x']}, ScaleY={geo_info_radians['scale_y']}). GeoInfo marked invalid."
+                        f"{geo_log_prefix} {image_key_log}: Invalid geo values found (ScaleValid={is_scale_valid}, LatValid={is_lat_valid}, LonValid={is_lon_valid}, OrientValid={is_orient_valid}). GeoInfo marked invalid."
                     )
-                    geo_info_radians["valid"] = False
+                    geo_info_radians["valid"] = False # Ensure marked invalid
 
             except OverflowError as oe:
-                # ERROR for math errors
                 logging.error(
                     f"{geo_log_prefix} {image_key_log}: Math OverflowError during GeoData conversion: {oe}. GeoInfo marked invalid."
                 )
                 geo_info_radians = {"valid": False}
             except Exception as e:
-                # Keep EXCEPTION for other geo errors
                 logging.exception(
                     f"{geo_log_prefix} {image_key_log}: Failed during GeoData extraction/conversion: {e}"
                 )
                 geo_info_radians = {"valid": False}
+            # --- MODIFICATION END ---
 
-            # 8. Return results - DEBUG for successful exit
+            # 8. Return results
             logging.debug(f"{log_prefix} Exiting reassemble_sar_image successfully.")
+            # Return a *copy* of the normalized image and the geo info dict
             return normalized_image_uint8.copy(), geo_info_radians
 
         except Exception as e:
-            # Keep EXCEPTION for unexpected errors in reassembly
             logging.exception(
                 f"{log_prefix} {image_key_log}: Unexpected error during SAR reassembly: {e}"
             )