Oi sensor

See merge request !55

oi-sensor/oi-sensor.py

@@ -19,6 +19,7 @@ from asyncua import Server
 import argparse
 import time
 
+
 SLEEP_DURATION = 10e-3 # 10 milliseconds
 
 # algorith defaults
@@ -30,7 +31,7 @@ DEFAULT_US = (190, 255,)
 DEFAULT_UV = (190, 255,)
 # the minimal number of pixes which we consider as a shape
 # and the maximal (configurable) such
-DEFAULT_AREA = (10000, 50000,)
+DEFAULT_AREA = (6000, 50000,)
 
 # command line handling
 parser = argparse.ArgumentParser(description='Run optical inspection OPC UA server.')
@@ -39,6 +40,8 @@ a('--ipv4', help='The IPv4 address on which the OPC UA server runs', default="0.
 a('--port', help='The port on which the OPC UA server runs', default="4840")
 a('--camera', help='The index of the camera (i.e. indxed in /dev/videoX)', default=0)
 a('--headless', help='Run without screen in a headless mode (boolean, default=0)', default=False)
+# XXX: allow to specify from CLI DEFAULT_LH & friends
+
 args = parser.parse_args()
 ipv4 = args.ipv4
 port = args.port
@@ -65,6 +68,11 @@ async def main():
     myvar = await myobj.add_variable(idx, "shape", 0.0)
     await myvar.set_writable()
 
+    # Initialize
+    result = 0.0
+    result_stack = []
+    current_shape = 0.0
+
     # init camera
     cap = cv2.VideoCapture(camera)
     font = cv2.FONT_HERSHEY_COMPLEX
@@ -124,26 +132,59 @@ 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)
                 x = approx.ravel()[0]
                 y = approx.ravel()[1]
+                number_of_points = len(approx)
                 if area > designated_area_min and area < designated_area_max:
-                    print("\tDetected area (px)=%.2f" %area)
+                    contour_detected = True
+                    if not headless:
                         cv2.drawContours(frame, [approx], 0, (0, 0, 0), 5)
-                    number_of_points = len(approx)
                     if number_of_points == 3:
+                        if not headless:
                             cv2.putText(frame, "Triangle", (x, y), font, 1, (0, 0, 0))
-                        await myvar.write_value(1.0)
+                        result = 1.0
                     elif number_of_points == 4:
+                        if not headless:
                             cv2.putText(frame, "Rectangle", (x, y), font, 1, (0, 0, 0))
-                        await myvar.write_value(2.0)
+                        result = 2.0
                     elif 7 < number_of_points < 20:
+                        if not headless:
                             cv2.putText(frame, "Circle (%s)" %number_of_points, (x, y), font, 1, (0, 0, 0))
-                        await myvar.write_value(3.0)
-                    else:
-                        await myvar.write_value(0.0)
+                        result = 3.0
+
+                    # printout
+                    print("\tDetected area (px)=%.2f, result=%d" %(area, result))
+
+                    # update list for last X results (FILO)
+                    default_occurence_number = 5
+                    result_stack.append(result)
+                    if len(result_stack) > default_occurence_number:
+                        # leave only last X items
+                        result_stack = result_stack[-default_occurence_number:]
+
+                    # to avoid sometimes errors in detection algorithm we change OPC UA node
+                    # variable only if at least we have 2 (40%) of last 5 (100%) items detected as this
+                    # shape. Not complex but avoid false results.
+                    count = result_stack.count(result)
+                    if count >= 2:
+                        # update OPC UA server's node attribute
+                        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: