#6 plot reference shoreline in detection images

src/coastsat/SDS_download.py

@@ -818,6 +818,11 @@ def retrieve_images(
                         ) as f:
                             for key in metadict.keys():
                                 f.write("%s\t%s\n" % (key, metadict[key]))
+
+                        if im_fn.get("ms", "unknown") != "unknown":
+                            logger.info(
+                                f"Successfully downloaded image id {im_meta.get('id','unknown')} as {im_fn.get('ms')}"
+                            )
                 except Exception as e:
                     logger.error(
                         f"Could not save metasdata for {im_meta.get('id','unknown')} that failed.\n{e}"
@@ -1513,7 +1518,7 @@ def filter_S2_collection(im_list):
         return im_list
     else:
         idx_max = np.argmax([np.sum(utm_zones == _) for _ in np.unique(utm_zones)])
-        utm_zone_selected =  np.unique(utm_zones)[idx_max]
+        utm_zone_selected = np.unique(utm_zones)[idx_max]
         # find the images that were acquired at the same time but have different utm zones
         idx_all = np.arange(0, len(im_list), 1)
         idx_covered = np.ones(len(im_list)).astype(bool)

src/coastsat/SDS_shoreline.py

@@ -334,6 +334,7 @@ def extract_shorelines(
                         settings,
                         date,
                         satname,
+                        im_ref_buffer,
                     )
                     # if the user decides to skip the image, continue and do not save the mapped shoreline
                     if skip_image:
@@ -877,7 +878,16 @@ def process_shoreline(contours, cloud_mask, im_nodata, georef, image_epsg, setti
 
 
 def show_detection(
-    im_ms, cloud_mask, im_labels, shoreline, image_epsg, georef, settings, date, satname
+    im_ms,
+    cloud_mask,
+    im_labels,
+    shoreline,
+    image_epsg,
+    georef,
+    settings,
+    date,
+    satname,
+    im_ref_buffer=None,
 ):
     """
     Shows the detected shoreline to the user for visual quality control.
@@ -998,8 +1008,18 @@ def show_detection(
     ax1.axis("off")
     ax1.set_title(sitename, fontweight="bold", fontsize=16)
 
+    # color map for the reference shoreline buffer
+    masked_cmap = plt.cm.get_cmap("Greys")
+    # masked_cmap.set_bad(color="gray", alpha=0)
+    # Create a masked array where False values are masked
+    masked_array = None
+    if im_ref_buffer is not None:
+        masked_array = np.ma.masked_where(im_ref_buffer == False, im_ref_buffer)
+
     # create image 2 (classification)
     ax2.imshow(im_class)
+    if masked_array is not None:
+        ax2.imshow(masked_array, cmap=masked_cmap, alpha=0.37)
     ax2.plot(sl_pix[:, 0], sl_pix[:, 1], "k.", markersize=3)
     ax2.axis("off")
     orange_patch = mpatches.Patch(color=colours[0, :], label="sand")
@@ -1015,6 +1035,8 @@ def show_detection(
 
     # create image 3 (MNDWI)
     ax3.imshow(im_mwi, cmap="bwr")
+    if masked_array is not None:
+        ax3.imshow(masked_array, cmap=masked_cmap, alpha=0.37)
     ax3.plot(sl_pix[:, 0], sl_pix[:, 1], "k.", markersize=3)
     ax3.axis("off")
     ax3.set_title(satname, fontweight="bold", fontsize=16)