Set shape to 0.0 if in current processing run no contour

was detected.

oi-sensor/oi-sensor.py

@@ -131,6 +131,7 @@ async def main():
             now = time.time() * 1000
             diff = (now-before)
             print("Processing time = %.2f ms, countours = %d" %(diff, len(contours)))
+            contour_detected = False
             for cnt in contours:
                 area = cv2.contourArea(cnt)
                 approx = cv2.approxPolyDP(cnt, 0.02*cv2.arcLength(cnt, True), True)
@@ -138,6 +139,7 @@ async def main():
                 y = approx.ravel()[1]
                 number_of_points = len(approx)
                 if area > designated_area_min and area < designated_area_max:
+                    contour_detected = True
                     if not headless:
                         cv2.drawContours(frame, [approx], 0, (0, 0, 0), 5)
                     if number_of_points == 3:
@@ -152,8 +154,7 @@ async def main():
                         if not headless:
                             cv2.putText(frame, "Circle (%s)" %number_of_points, (x, y), font, 1, (0, 0, 0))
                         result = 3.0
-                    else:
-                        result = 0.0
+
                     # printout
                     print("\tDetected area (px)=%.2f, result=%d" %(area, result))
 
@@ -173,6 +174,17 @@ async def main():
                         current_shape = result
                         await myvar.write_value(result)
 
+                    # break current countour detection loop as in this example we care
+                    # for first detected SHAPE, we do not expect more shapes
+                    break
+
+            if not contour_detected:
+                # no countours actually detected thus update OPC UA server's node attribute
+                result = 0.0
+                result_stack.append(result)
+                current_shape = result
+                await myvar.write_value(result)
+
             # show current MASK and camera output windows
             if not headless:
                 cv2.imshow("Frame", frame)