diff --git a/panda b/panda
index 7aa6e7ae..d527579b 160000
--- a/panda
+++ b/panda
@@ -1 +1 @@
-Subproject commit 7aa6e7ae1f831b99ba8a94032495882f8cf68ba4
+Subproject commit d527579b41293680ad2124970fbb605b3502072b
diff --git a/tools/webcam/warp_vis_interactive.py b/tools/webcam/warp_vis_interactive.py
new file mode 100755
index 00000000..d5efd6e7
--- /dev/null
+++ b/tools/webcam/warp_vis_interactive.py
@@ -0,0 +1,106 @@
+#!/usr/bin/env python
+
+import numpy as np
+import math
+import sys
+import cv2
+
+# copied from common.transformations/camera.py
+eon_focal_length = 910.0  # pixels
+eon_dcam_focal_length = 860.0  # pixels
+
+# adjust these for your specific camera specs if known
+cam_width = 1280
+cam_height = 720
+cam_fov = 80
+cam_focal_length = cam_width/(2*math.tan(cam_fov/2/180*math.pi))
+
+# EON intrinsics
+eon_intrinsics = np.array([
+  [eon_focal_length,   0.,   1164/2.],
+  [  0.,  eon_focal_length,  874/2.],
+  [  0.,    0.,     1.]])
+
+# TODO: implement driver cam
+eon_dcam_intrinsics = np.array([
+  [eon_dcam_focal_length,   0,   1152/2.],
+  [  0,  eon_dcam_focal_length,  864/2.],
+  [  0,    0,     1]])
+
+final_warp = []
+
+if __name__ == "__main__":
+  in_cmd = sys.argv
+  cam_number = 0
+
+  if (len(in_cmd) < 3) or ("-h" in in_cmd)or ("--help" in in_cmd):
+    print("USAGE: ./warp_vis.py [camera_number] [path_to_png.png]")
+    print("-h or --help to display this dialogue")
+    exit()
+  else:
+    print("CONTROLS:\n\
+      q - zoom in\n\
+      e - zoom out\n\
+      w - shift up in\n\
+      s - shift down\n\
+      a - shift left\n\
+      d - shift right\n\
+      x - exit and print warp mesh\n\
+      ")
+    cam_number = in_cmd[1]
+    background = cv2.imread(in_cmd[2])   
+
+  cap = cv2.VideoCapture("/dev/video" + cam_number)
+  cap.set(cv2.CAP_PROP_FRAME_WIDTH, cam_width)
+  cap.set(cv2.CAP_PROP_FRAME_HEIGHT, cam_height)
+
+  while (True):
+
+    k = cv2.waitKey(1)
+
+    if (k == ord('x')):
+      break
+    if (k == ord('q')):
+      cam_focal_length += 1
+    if (k == ord('e')):
+      cam_focal_length -= 1
+    if (k == ord('a')):
+      cam_width += 1
+    if (k == ord('d')):
+      cam_width -= 1
+    if (k == ord('w')):
+      cam_height += 1
+    if (k == ord('s')):
+      cam_height -= 1
+
+    ret, img = cap.read()
+
+    if ret:
+      cam_intrinsics = np.array([
+          [cam_focal_length,   0.,   cam_width/2.],
+          [  0.,  cam_focal_length,  cam_height/2.],
+          [  0.,    0.,   1]]) 
+      rear_warp = np.dot(eon_intrinsics, np.linalg.inv(cam_intrinsics))
+
+      cv2.imshow('original',img)
+      img = cv2.warpPerspective(img, rear_warp, (1164,874), borderMode=cv2.BORDER_CONSTANT, borderValue=0)
+    #   img = cv2.addWeighted(background,0.8,img,1,0)
+      cv2.imshow('preview', img)
+
+  print("FINAL WARP: ")
+  final_warp = rear_warp.flatten()
+
+  # string format to make copying into camera_webcam.cc easier
+  warp_string = "  float ts[9] = {"
+  cnt_fmt = 0
+  for item in final_warp:
+    warp_string += str(item)
+    cnt_fmt += 1
+    if cnt_fmt != 9:
+      if cnt_fmt % 3 == 0:
+        warp_string += ",\n                "
+      else:
+        warp_string += ", "
+  warp_string += "};"
+
+  print(warp_string)