update code

Robot_Development/catkin_ws/src/lane_detection/src/detect.py

@@ -57,7 +57,7 @@ def ROI(pic):
 # pic: original image to apply the pre-set region of interest too
 def ROI_real(pic):
     height = pic.shape[0]
-    triangle = np.array([[(0, height), (200, 250), (400, 250), (600, height)]], dtype=np.int32)
+    triangle = np.array([[(150, 200), (0, height), (650, height), (500, 300)]], dtype=np.int32)
     mask = np.zeros_like(pic)
     cv2.fillPoly(mask, triangle, 255)
     roi = cv2.bitwise_and(pic, mask)
@@ -282,15 +282,15 @@ while not rospy.is_shutdown():
         Mpoints = find_middle(Lpoints, Rpoints)
 
         # (type(Rpoints[0][0]))
-        plt.cla()
-        plt.clf()
+        #plt.cla()
+        #plt.clf()
 
-        plt.scatter(Rpoints[0], Rpoints[1])
-        plt.scatter(Lpoints[0], Lpoints[1])
+        #plt.scatter(Rpoints[0], Rpoints[1])
+        #plt.scatter(Lpoints[0], Lpoints[1])
         lanes = detectDeparture(Lpoints, 400, Rpoints)
         lanes_detected(lanes)
         if (Mpoints != 0):
-            plt.scatter(Mpoints[0], Mpoints[1])
+            #plt.scatter(Mpoints[0], Mpoints[1])
             lane_distance = detectDepartureNew(Mpoints)
             lane_status(lane_distance)
 
@@ -298,11 +298,11 @@ while not rospy.is_shutdown():
             print("No midpoint calculated")
         #plt.scatter(310, 300)
 
-        plt.imshow(frame, zorder=0)
+        #plt.imshow(frame, zorder=0)
 
-        plt.pause(.001)
+        #plt.pause(.001)
 
-    #lane = applyLines(frame, lines)
+    lane = applyLines(frame, lines)
 
     #cv2.imshow("edges", wEdges)
     #cv2.imshow("cropped", cropped)