Error while playing stored Video using OpenCV + Python

asked 2017-11-29 08:16:04 -0500

updated 2017-11-29 12:20:30 -0500


I'm using Opencv 3.2 + Python on ubuntu 16.04 LTS OS. I'm trying to undistort the fisheye video which is collected from web cam. Below is my code where I'm undistorting the fisheye video by undistorting frame by frame. The program is executing fine and its undistorting fisheye video correctly but when I try to play the stored undistorted video (undistortedop.avi) it gives a error message saying "Could not demultiplex stream". Could anyone please help me to solve this problem..?

image description

import numpy as np

import os

import glob

import sys

assert float(cv2.__version__.rsplit('.', 1)[0]) >= 3, 'OpenCV version 3 or newer required.'

DIM=(1280, 720)

K=np.array([[517.7167401534203, 0.0, 641.312338873659], [0.0, 518.0410707880329, 361.1273127787553], [0.0, 0.0, 1.0]])

D=np.array([[-0.00428080929837007], [-0.14786471866085527], [0.07941291495275071], [-0.025649243686649097]])




cap = cv2.VideoCapture(0)

Define the codec and create VideoWriter object

fourcc = cv2.VideoWriter_fourcc(*'XVID')

out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))

out1 = cv2.VideoWriter('undistortedop.avi',fourcc, 20.0, (640,480))

while True:

ret, frame =

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

# img = cv2.imread(img_path)

# dim1 = img.shape[:2][::-1] #dim1 is the dimension of input image to un-distort

dim1=(1280, 720)

assert dim1[0]/dim1[1] == DIM[0]/DIM[1], "Image to undistort needs to have same aspect ratio as the ones used in calibration"

if not dim2:

   dim2 = dim1

if not dim3:

   dim3 = dim1

dim3=(630, 480)

scaled_K = K * dim1[0] / DIM[0] # The values of K is to scale with image dimension.

scaled_K[2][2] = 1.0 # Except that K[2][2] is always 1.0

# This is how scaled_K, dim2 and balance are used to determine the final K used to un-distort image. OpenCV document failed to make this clear!

new_K = cv2.fisheye.estimateNewCameraMatrixForUndistortRectify(scaled_K, D, dim2, np.eye(3), balance=balance)

map1, map2 = cv2.fisheye.initUndistortRectifyMap(scaled_K, D, np.eye(3), new_K, dim3, cv2.CV_16SC2)

undistorted_img = cv2.remap(frame, map1, map2, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)

# cv2.imwrite('Testpic3_undistorted.jpg', undistorted_img)


cv2.imshow("undistorted", undistorted_img)

# Write the frame



# cv2.imshow('gray', gray)

if cv2.waitKey(1) & 0xFF == ord('q'):







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