add flashing and flashing_end_point

handcrafted_solution.py

@@ -399,7 +399,29 @@ def get_vertices_and_edges_from_two_segmentations(ade_seg_np, gest_seg_np, edge_
                 apex_map[uu+ss[0], vv+ss[1]] = (255,0,0)
                 apex_map_on_ade[uu+ss[0], vv+ss[1]] = (255,0,0)
                 apex_map_on_gest[uu+ss[0], vv+ss[1]] = (255,0,0)
+    
+    flashing_end_color = np.array(gestalt_color_mapping['flashing_end_point'])    
+    flashing_end_mask = cv2.inRange(gest_seg_np,  flashing_end_color-color_th/2, flashing_end_color+color_th/2) # this color is sensitive
+    if flashing_end_color.sum() > 0:
+        output = cv2.connectedComponentsWithStats(flashing_end_mask, 8, cv2.CV_32S)
+        (numLabels, labels, stats, centroids) = output
+        stats, centroids = stats[1:], centroids[1:]
+        for i in range(numLabels-1):
+            vert = {"xy": centroids[i], "type": "flashing_end_point"}
+            vertices.append(vert) 
 
+            uu = int(centroids[i][1])
+            vv = int(centroids[i][0])
+            # plot a cross
+            apex_map_on_ade[uu, vv] = (255,0,0)
+            shift=[(1,0),(-1,0),(0,1),(0,-1), (2,0),(-2,0),(0,2),(0,-2), (3,0),(-3,0),(0,3),(0,-3)]
+            h,w,_ = apex_map_on_ade.shape
+            for ss in shift:
+              if uu+ss[0] >= 0 and uu+ss[0] < h and vv+ss[1] >= 0 and vv+ss[1] < w:
+                apex_map[uu+ss[0], vv+ss[1]] = (255,0,0)
+                apex_map_on_ade[uu+ss[0], vv+ss[1]] = (255,0,0)
+                apex_map_on_gest[uu+ss[0], vv+ss[1]] = (255,0,0)
+    ''''''
     # imsave apex and eave_end
     if DUMP_IMG:
       import random
@@ -466,7 +488,8 @@ def get_vertices_and_edges_from_two_segmentations(ade_seg_np, gest_seg_np, edge_
       conn = []
       # Plot all possible connection pixels in one mask
       mask = cv2.bitwise_or(apex_mask, eave_end_mask)
-      for edge_class in ['eave', 'ridge', 'rake', 'valley', 'step_flashing']:
+      #for edge_class in ['eave', 'ridge', 'rake', 'valley', 'step_flashing' ]:#, 'flashing']:
+      for edge_class in ['eave', 'ridge', 'rake', 'valley', 'step_flashing' , 'flashing']:
         edge_color = np.array(gestalt_color_mapping[edge_class])
         mask_e = cv2.morphologyEx(cv2.inRange(gest_seg_np,
                                             edge_color-color_th,
@@ -751,7 +774,7 @@ def predict(entry, visualize=False, prune_dist_thr=600, depth_scale=2.5, ) -> Tu
           depth_scale = 2.5
         elif i==2: # only visualize view 0,1
           continue 
-          
+        
         if i!=0:
           continue
         '''