opencv cv2.remap creates strange images

Question

I'm new to stereo calibration and tried to get the matrices of a stereo camera and then remap the images, so I could use them for depth-map generation. I used the sample images left*.jpg and right*.jpg and parts of this code: http://docs.opencv.org/3.0-beta/doc/py_tutorials/py_calib3d/py_calibration/py_calibration.html#calibration (and also from samples/python/calibrate.py)

So my code is the following:

import cv2
...
img_names = [glob('../data/left*.jpg'), glob('../data/right*.jpg')]
obj_points = [[], []]
img_points = [[], []]
h = ... #
w = ... #

... # get the obj_points and img_points from both image sets like in the examples
# This works fine, I viewed the results with cv2.drawChessboardCorners

rms_l, camera_matrix_l, dist_coeffs_l, _, _ = cv2.calibrateCamera(obj_points[0], img_points[0], (w, h), None, None)
rms_r, camera_matrix_r, dist_coeffs_r, _, _ = cv2.calibrateCamera(obj_points[1], img_points[1], (w, h), None, None)

stereo_flags = 0
stereo_flags |= cv2.CALIB_USE_INTRINSIC_GUESS
stereo_flags |= cv2.CALIB_FIX_INTRINSIC

# run stereo calibration
rms_stereo, camera_matrix_l, dist_coeffs_l, camera_matrix_r, dist_coeffs_r, R, T, E, F  = cv2.stereoCalibrate(obj_points[0], img_points[0], img_points[1], camera_matrix_l, dist_coeffs_l, camera_matrix_r, dist_coeffs_r, (w, h), flags=stereo_flags)

# run stereo rectification
rectification_matrix_l, rectification_matrix_r, projection_matrix_l, projection_matrix_r, _, _, _ = cv2.stereoRectify(camera_matrix_l, dist_coeffs_l, camera_matrix_r, dist_coeffs_r, (w, h), R, T)

map1, map2 = [], []
map1[0], map2[0] = cv2.initUndistortRectifyMap(camera_matrix_l, dist_coeffs_l, rectification_matrix_l, projection_matrix_l, (w, h), cv2.CV_16SC2)
map1[1], map2[1] = cv2.initUndistortRectifyMap(camera_matrix_r, dist_coeffs_r, rectification_matrix_r, projection_matrix_r, (w, h), cv2.CV_16SC2)

print ... # see below

for in in range(2):
    img = cv2.imread(img_names[i][0], 0)
    imgt = cv2.remap(img, map1[i], map2[i], cv2.INTER_LINEAR)
    cv2.imshow('image', imgt)
    cv2.waitKey(0)

But then, my the resulting images are very strange (left and right):

Now is my question, what can be my mistake? Did I calculated the matrices not correct or inserted wrong parameters? I saw many examples which are using those functions in a similar way, but altough their results are not like mine.

EDIT: Here are my matrices:

---------- Camera Stereo ----------
RMS: 54.0798238093
camera matrix left:
[[ 532.80990768    0.          342.49522241]
 [   0.          532.93344826  233.88792572]
 [   0.            0.            1.        ]]
distortion coefficients left:  [ -2.81325825e-01   2.91151900e-02   1.21234424e-03  -1.40823847e-04
   1.54861062e-01]
camera matrix right:
[[ 537.43775429    0.          327.6113408 ]
 [   0.          536.95118843  248.89561922]
 [   0.            0.            1.        ]]
distortion coefficients right:  [-0.29741745  0.14930176 -0.00077008  0.00032599 -0.06565751]
R:
[[ 0.81520177  0.24703546  0.52385071]
 [ 0.42427129  0.36098612 -0.83047149]
 [-0.39425873  0.89925664  0.18946647]]
Rectification matrix Left :
[[ 0.84817656  0.5225405  -0.08687895]
 [-0.44783099  0.61975759 -0.64447493]
 [-0.28292036  0.58553561  0.75967369]]
Rectification matrix Right :
[[ 0.77500946  0.62063732  0.11903635]
 [-0.54957916  0.56894011  0.61177602]
 [ 0.31196648 -0.5395521   0.7820233 ]]
Projection Matrix Left :
[[ 448.32924881    0.          328.40793514    0.        ]
 [   0.          448.32924881  215.26811713    0.        ]
 [   0.            0.            1.            0.        ]]
Projection Matrix Right :
[[  4.48329249e+02   0.00000000e+00   3.28407935e+02   0.00000000e+00]
 [  0.00000000e+00   4.48329249e+02   2.15268117e+02   1.97345858e+04]
 [  0.00000000e+00   0.00000000e+00   1.00000000e+00   0.00000000e+00]]