Added an option to put a warning message below the face if suspicious

trackmultiplefaces.py

@@ -19,7 +19,7 @@ import randomnames
 #Make sure that you copy this file from the opencv project to the root of this
 #project folder
 faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
-print( faceCascade.empty() )
+
 #The deisred output width and height
 OUTPUT_SIZE_WIDTH = 775
 OUTPUT_SIZE_HEIGHT = 600
@@ -45,7 +45,11 @@ def calculateAverageSuspicious(faceSuspicion):
         averageSuspicious = sum(faceSuspicion)/currentFaces
         print(f"Average suspicion: {averageSuspicious}")
 
-def detectAndTrackMultipleFaces(start_thread, charset, draw_person_dangerosity):
+def detectAndTrackMultipleFaces(start_thread, 
+                                charset, 
+                                draw_person_dangerosity,
+                                add_warning_message):
+
     #Open the first webcame device
     capture = cv2.VideoCapture(0)
 
@@ -217,6 +221,7 @@ def detectAndTrackMultipleFaces(start_thread, charset, draw_person_dangerosity):
 
                         # Pick up random name: Do we want a thread for that? 
                         # Advantage is that we can pop an "Identifying..." Message
+                        # Disadvantage is that is more "lourd"
                         
                         if start_thread :
                             #Start a new thread that is used to simulate face recognition. 
@@ -245,6 +250,7 @@ def detectAndTrackMultipleFaces(start_thread, charset, draw_person_dangerosity):
                 rectangle_around_face(fid, 
                                       faceTrackers, 
                                       faceSuspicion,
+                                      # If False, colors will not change with suspicion level
                                       draw_person_dangerosity, 
                                       resultImage)
 
@@ -271,30 +277,40 @@ def detectAndTrackMultipleFaces(start_thread, charset, draw_person_dangerosity):
 
                 width = resultImage.shape[1]
                 cv2.rectangle(resultImage, (int(width-50), 0), (int(width), 120), color, -1)
-
+                
+                # If Known -> print Name 
                 if fid in faceNames.keys():
-                    # Name's alignment
+
                     cv2.putText(resultImage, 
-                                faceNames[fid] ,
-                                (t_x+ int((t_w - len(faceNames[fid])*10)/2 +2), int(t_y)),
-                                cv2.FONT_HERSHEY_SIMPLEX,
-                                0.5, 
-                                (255, 255, 255), 
-                                1, 
-                                cv2.LINE_AA)
+                        faceNames[fid] ,
+                        # Name's alignment
+                        (t_x+ int((t_w - len(faceNames[fid])*10)/2 + 10), int(t_y) - 10),
+                        cv2.FONT_HERSHEY_SIMPLEX,
+                        0.5, 
+                        (255, 255, 255), 
+                        1, 
+                        cv2.LINE_AA)
+                    
+                    # Add a warning message depending on suspicious level
+                    if add_warning_message:
+                        put_warning_message(fid, 
+                                            faceTrackers, 
+                                            faceSuspicion, 
+                                            resultImage, 
+                                            threshold=2)
+                
+                # Else print Identifying
                 else:
-                    # Detecting
                     text = "Identifying"
                     cv2.putText(resultImage, 
                                 text ,
-                                (t_x + int((t_w - len(text)*10)/2 +2), int(t_y)),
+                                (t_x + int((t_w - len(text)*10)/2 + 10), int(t_y)),
                                 cv2.FONT_HERSHEY_SIMPLEX,
                                 0.5, 
                                 (255, 255, 255), 
                                 1, 
                                 cv2.LINE_AA)
 
-
             #Since we want to show something larger on the screen than the
             #original 320x240, we resize the image again
             #
@@ -308,9 +324,6 @@ def detectAndTrackMultipleFaces(start_thread, charset, draw_person_dangerosity):
             cv2.imshow("base-image", baseImage)
             cv2.imshow("result-image", resultImage) #largeResult)
 
-
-
-
     #To ensure we can also deal with the user pressing Ctrl-C in the console
     #we have to check for the KeyboardInterrupt exception and break out of
     #the main loop
@@ -321,6 +334,32 @@ def detectAndTrackMultipleFaces(start_thread, charset, draw_person_dangerosity):
     cv2.destroyAllWindows()
     exit(0)
 
+def put_warning_message(fid, faceTrackers, faceSuspicion, resultImage, threshold=2):
+    '''
+    Print a Warning message depending on suspicion level
+    '''
+    tracked_position =  faceTrackers[fid].get_position()
+
+    t_x = int(tracked_position.left())
+    t_y = int(tracked_position.top())
+    t_w = int(tracked_position.width())
+    t_h = int(tracked_position.height())
+    
+    suspicion_level = faceSuspicion[fid]
+    
+    if suspicion_level > threshold:
+        text = "ATTENTION! INDIVIDU DANGEREUX!"
+        cv2.putText(resultImage, 
+                    text ,
+                    # Name's alignment
+                    (t_x+ int((t_w - len(text)*10)/2 + 10), int(t_y) + 20 + t_h),
+                    cv2.FONT_HERSHEY_SIMPLEX,
+                    0.5, 
+                    RED, 
+                    1, 
+                    cv2.LINE_AA)
+
+
 def rectangle_around_face(fid, faceTrackers, faceSuspicion, draw_person_dangerosity, resultImage):
     '''
     Draw a rectangle around's people face
@@ -336,21 +375,25 @@ def rectangle_around_face(fid, faceTrackers, faceSuspicion, draw_person_dangeros
     # If we want to have a dangerosity color per personn  
     if draw_person_dangerosity :
         suspicionLevel = faceSuspicion[fid]
-        person_color = draw_person_dangerosity_color(suspicionLevel)
+        person_color = pick_person_dangerosity_color(suspicionLevel)
+    
     # Else default to rectangleColor
     else:
         person_color = rectangleColor
 
-    cv2.rectangle(resultImage, (t_x, t_y),
-                            (t_x + t_w , t_y + t_h),
-                            person_color,2)
+    # Draw Rectangle
+    cv2.rectangle(resultImage, 
+                  (t_x, t_y),
+                  (t_x + t_w , t_y + t_h),
+                  person_color,
+                  1)
 
-def draw_person_dangerosity_color(suspicionLevel):
+def pick_person_dangerosity_color(suspicionLevel, threshold=2):
     '''
     Compute person level suspicion -> simplified to 2 levels
     Can reintroduce the faceSuspicious dictionnary lated, was more clean
     '''
-    if suspicionLevel>2:
+    if suspicionLevel> threshold:
         color = RED
     else:
         color = GREEN
@@ -360,11 +403,11 @@ def draw_person_dangerosity_color(suspicionLevel):
 if __name__ == '__main__':
     detectAndTrackMultipleFaces(
             # False: Names are directly printed on screen, no new thread
-            start_thread=False, 
+            start_thread             = False, 
             # Select only names with letters and whitespace. Any other value will select printable.
-            charset     = "letters",
+            charset                  = "letters",
             # If True, then rectangle color around people' face will turn red if dangerous
-            # + a message will pop 
-            draw_person_dangerosity = True
-
+            draw_person_dangerosity  = True,
+            # Add a warning message if dangerous
+            add_warning_message      = True
             )