Added steering wheel visualization

run.py

@@ -8,6 +8,9 @@
 saver = tf.train.Saver()
 saver.restore(sess, "save/model.ckpt")
 
+img = cv2.imread('steering_wheel_image.jpg',0)
+rows,cols = img.shape
+
 cap = cv2.VideoCapture(0)
 while(cv2.waitKey(10) != ord('q')):
     ret, frame = cap.read()
@@ -16,6 +19,9 @@
     call("clear")
     print("Predicted steering angle: " + str(degrees) + " degrees")
     cv2.imshow('frame', frame)
+    M = cv2.getRotationMatrix2D((cols/2,rows/2),-degrees,1)
+    dst = cv2.warpAffine(img,M,(cols,rows))
+    cv2.imshow("steering wheel", dst)
 
 cap.release()
 cv2.destroyAllWindows()

run_dataset.py

@@ -8,13 +8,19 @@
 saver = tf.train.Saver()
 saver.restore(sess, "save/model.ckpt")
 
+img = cv2.imread('steering_wheel_image.jpg',0)
+rows,cols = img.shape
+
 i = 0
 while(cv2.waitKey(10) != ord('q')):
     image = scipy.misc.imresize(scipy.misc.imread("driving_dataset/" + str(i) + ".jpg")[-150:], [66, 200]) / 255.0
     degrees = model.y.eval(feed_dict={model.x: [image], model.keep_prob: 1.0})[0][0] * 180.0 / scipy.pi
     call("clear")
     print("Predicted steering angle: " + str(degrees) + " degrees")
     cv2.imshow("frame", image)
+    M = cv2.getRotationMatrix2D((cols/2,rows/2),-degrees,1)
+    dst = cv2.warpAffine(img,M,(cols,rows))
+    cv2.imshow("steering wheel", dst)
     i += 1
 
 cv2.destroyAllWindows()