Added ros code

Detect/detect.py

 #!/usr/bin/python
 
 import numpy as np
-#import rospy
+import rospy
 import matplotlib.pyplot as plt
 import cv2
-
-width = 275
+from imutils.video import WebcamVideoStream
+from imutils.video import FPS
+from std_msgs.msg import String
+from std_msgs.msg import Float64
+pub = rospy.Publisher('direction', String, queue_size=10)
+pub1 = rospy.Publisher('lane_distance', Float64, queue_size=10)
+rospy.init_node('lane_status')
+rate = rospy.Rate(10)  # 100hz
+width = 325
 # Converts picture to grayscale and applies filter to picture
 # params
 # pic : a numpy array of pixel values to represent a picture
@@ -41,7 +48,7 @@ def ROI(pic):
     roi = cv2.bitwise_and(pic, mask)
     return roi
 
-# Define the region of in which the lanes will be in the cameras view for the robot
+# Define the region of in which the lanes will be in the cameras view
 # params
 # pic: original image to apply the pre-set region of interest too
 def ROI_real(pic):
@@ -86,32 +93,24 @@ def find_middle(leftPoints, rightPoints):
 
     middle_lines = [[],[]]
 
-    if rightPoints[1] is None:
-        print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Caught the empty right list~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
+    if leftPoints[1] == []:
+        print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Caught the empty list~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
         return 0
-    elif leftPoints[1] is None :
-        print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Caught the empty left list~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
+
+    elif rightPoints[1] == []:
+        print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Caught the empty list~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
         return 0
+
     else:
-        #print(leftPoints[1])
-        #print(rightPoints[1])
         for x in range(150):
 
-            #print("Right x point: " + str(rightPoints[0][x]))
-            #print("Left x point: " + str(leftPoints[0][x]))
-            #print("Right Y point: " + str(rightPoints[1][x]))
-            #print("Left Y point: " + str(leftPoints[1][x]))
-
             midPoint = (rightPoints[0][149-x] + leftPoints[0][x]) / 2
-            #print("midPoint X: " + str(midPoint))
-            #print("midPoint Y: " + str(leftPoints[1][x]))
+
             middle_lines[1].append(leftPoints[1][x])
             middle_lines[0].append(midPoint)
 
     return middle_lines
 
-
-
 # Find the two average lines given the set of lines
 # params
 # pic: the original image
@@ -232,25 +231,25 @@ def detectDepartureNew(midPoints):
 def myround(x):
     return int(5 * round(float(x)/5))
 
+def lane_status(lane_distance):
+    rospy.loginfo(lane_distance)
+    pub.publish(lane_distance)
+    rate.sleep()
 
 
-
-video = cv2.VideoCapture("midTest.avi")
+#video = cv2.VideoCapture("test2.mp4")
 #video = cv2.VideoCapture("highway.mp4")
 
 
-#video = cv2.VideoCapture(0)
+video = WebcamVideoStream(src=1).start()
 plt.ion()
 
-while True:
-    ret, frame = video.read()
+while not rospy.is_shutdown():
+    frame = video.read()
     # gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
     # frame = cv2.imread("../frame.jpeg")
     frame_edge = detect_edge(frame)
 
-    if not ret:
-        video = cv2.VideoCapture(1)
-        continue
 
     new_img = formatImg(frame)
 
@@ -276,22 +275,25 @@ while True:
 
         plt.scatter(Rpoints[0], Rpoints[1])
         plt.scatter(Lpoints[0], Lpoints[1])
+        if(Mpoints != 0):
             plt.scatter(Mpoints[0], Mpoints[1])
+            lane_distance = detectDepartureNew(Mpoints)
+            lane_status(lane_distance)
 
-        plt.scatter(300, 400)
+        else:
+            print("No midpoint calculated")
+        #plt.scatter(310, 300)
 
         plt.imshow(frame, zorder=0)
 
-        #detectDeparture(Lpoints, 310, Rpoints)
-        detectDepartureNew(Mpoints)
 
         plt.pause(.001)
 
 
-    lane = applyLines(frame, lines)
+    #lane = applyLines(frame, lines)
 
     #cv2.imshow("edges", wEdges)
-    #cv2.imshow("cropped", cropped)
+    cv2.imshow("cropped", cropped)
     #cv2.imshow("frame", lane)
 
     key = cv2.waitKey(25)