final results from monday!

detect_structures.py

@@ -29,7 +29,7 @@ DRAW_FIRST_CONE_LAYER_BRIGTHER = True
 BISEC_CONE_ANGLE = 50
 CORRECTION_ANGLE = 23
 OVERLAY_ALPHA = 0.2
-COLORED_CANVAS = False
+COLORED_CANVAS = True
 BISEC_SKIP_LOWER_LEVELS = False
 DISPLAY_RASTER_ELEMENTS = 500
 KMEANS_AREA_MASK_THRESHOLD = 0.08 #max 1.0 (percent of pixels), cur 0.09,  sonntag mittag 0.05,   #smaller threshold -> more colors, higher threshold -> less colors
@@ -150,7 +150,6 @@ for img_name, img_bdcn in (list(zip(images, images_bdcn))[15:16] if SKIP_OPENPOS
         kmout_mask=cv2.cvtColor(kmout_mask,cv2.COLOR_GRAY2BGR) #change mask to a 3 channel image 
         km_mask_out=cv2.subtract(kmout_mask,kmeans_output)        #subtract mask from kmeans result
         km_mask_out=cv2.subtract(kmout_mask,km_mask_out)
-        
 
         #idea: count how many pixels the white mask has, count how many pixels each color from kmeans result appears in mask -> area > 80% is foreground
         kmeans_colors, kmeans_counts =   np.unique(kmeans_output.reshape(-1, kmeans_output.shape[-1]),axis=0,return_counts=True)
@@ -181,6 +180,10 @@ for img_name, img_bdcn in (list(zip(images, images_bdcn))[15:16] if SKIP_OPENPOS
             cv2.rectangle(kmeans_output, (220,15), (230,25), (int(filtered_km_mask_FG_colors[0][0]),int(filtered_km_mask_FG_colors[0][1]),int(filtered_km_mask_FG_colors[0][2])), -1)
             cv2.rectangle(kmeans_output, (220,15), (230,25), (255,255,255), 1)
 
+            cv2.rectangle(km_mask_out, (0,0), (235,30), (0,0,0), -1)
+            cv2.putText(km_mask_out, "Foreground colors:", (10,25), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255,255,255))
+            cv2.rectangle(km_mask_out, (220,15), (230,25), (255,255,255), 1)
+
             # cv2.imwrite(os.path.basename(img_bdcn)+'_km_mask_out_before.jpg',kmeans_output)
             binary_output = kmeans_output.copy()
             offset=220;
@@ -208,10 +211,12 @@ for img_name, img_bdcn in (list(zip(images, images_bdcn))[15:16] if SKIP_OPENPOS
                 # kmeans_output[((kmeans_output[:,:,0] == color[0]) & (kmeans_output[:,:,1] == color[1]) & (kmeans_output[:,:,2] == color[2]))]=colors_only_BG[0] #search in kmeans_output image for specific color and replace all by first color
                 # km_mask_out[((km_mask_out[:,:,0] == color[0]) & (km_mask_out[:,:,1] == color[1]) & (km_mask_out[:,:,2] == color[2]))]=colors_only_BG[0] #search in binary_output image for specific color and replace all by first color
 
+            cv2.imwrite(os.path.basename(img_name)+'_inkm_step5_kmeans_masked.jpg',km_mask_out)
             cv2.imwrite(os.path.basename(img_name)+'_inkm_step5_kmean_colorreplaced.jpg',kmeans_output)
             cv2.imwrite(os.path.basename(img_name)+'_inkm_step5_kmean_binarization.jpg',binary_output)
             
 
+
             # cv2.imwrite(os.path.basename(img_bdcn)+'_kmeans_output_after.jpg',kmeans_output)
             # cv2.imwrite(os.path.basename(img_bdcn)+'_km_mask_out.jpg',km_mask_out)
             # cv2.namedWindow("binary_output", cv2.WINDOW_NORMAL)