Different Color Result Between Python OpenCV and MATLAB

I'm going to convert RGB image to YIQ image and viceversa. The problem is Python give me a weird image, while MATLAB shows the right one. I spent hours to figure what's wrong, but i still have no idea.

I use Python 3.5.2 with OpenCV 3.1.0 and MATLAB R2016a.

Python code for RGB2YIQ:

import cv2 as cv
import numpy as np

def rgb2yiq(img):
   row, col, ch = img.shape
   Y = np.zeros((row,col))
   I = np.zeros((row,col))
   Q = np.zeros((row,col))
   for i in range(row):
      for j in range(col):
         Y[i,j] = 0.299 * img[i,j,2] + 0.587 * img[i,j,1] + 0.114 * img[i,j,0]
         I[i,j] = 0.596 * img[i,j,2] - 0.274 * img[i,j,1] - 0.322 * img[i,j,0]
         Q[i,j] = 0.211 * img[i,j,2] - 0.523 * img[i,j,1] + 0.312 * img[i,j,0]
   yiq = cv.merge((Y,I,Q))
   return yiq.astype(np.uint8)

def main():
   img = cv.imread("C:/Users/Kadek/Documents/MATLAB/peppers.jpg")
   img = rgb2yiq(img)
   cv.imwrite("YIQ.jpg",img)
   cv.namedWindow('Image', cv.WINDOW_NORMAL)
   cv.imshow('Image', img)
   cv.waitKey(0)
   cv.destroyAllWindows()

main()

MATLAB code for RGB2YIQ:

img = imread('peppers.jpg');
[row col ch] = size(img);

for x=1:row
  for y=1:col
      Y(x,y) = 0.299 * img(x,y,1) + 0.587 * img(x,y,2) + 0.114 * img(x,y,3);
      I(x,y) = 0.596 * img(x,y,1) - 0.274 * img(x,y,2) - 0.322 * img(x,y,3);
      Q(x,y) = 0.211 * img(x,y,1) - 0.523 * img(x,y,2) + 0.312 * img(x,y,3);
  end
end

yiq(:,:,1) = Y;
yiq(:,:,2) = I;
yiq(:,:,3) = Q;

figure, imshow(yiq);

Result for RGB2YIQ

Python code for YIQ2RGB:

import cv2 as cv
import numpy as np

def yiq2rgb(img):
   row, col, ch = img.shape
   r = np.zeros((row,col))
   g = np.zeros((row,col))
   b = np.zeros((row,col))
   for i in range(row):
      for j in range(col):
         r[i,j] = img[i,j,0] * 1.0 + img[i,j,1] * 0.9562 + img[i,j,2] * 0.6214
         g[i,j] = img[i,j,0] * 1.0 - img[i,j,1] * 0.2727 - img[i,j,2] * 0.6468
         b[i,j] = img[i,j,0] * 1.0 - img[i,j,1] * 1.1037 + img[i,j,2] * 1.7006
   rgb = cv.merge((b,g,r))
   return rgb.astype(np.uint8)

def main():
   img = cv.imread("YIQ.jpg")
   img = yiq2rgb(img)
   cv.imwrite("test.jpg",img)
   cv.namedWindow('Image', cv.WINDOW_NORMAL)
   cv.imshow('Image', img)
   cv.waitKey(0)
   cv.destroyAllWindows()

main()

MATLAB code for YIQ2RGB:

img = imread('YIQ.jpg');
[row col ch] = size(img);

for x=1:row
  for y=1:col
      R(x,y) = 1.0 * img(x,y,1) + 0.9562 * img(x,y,2) + 0.6214 * img(x,y,3);
      G(x,y) = 1.0 * img(x,y,1) - 0.2727 * img(x,y,2) - 0.6468 * img(x,y,3);
      B(x,y) = 1.0 * img(x,y,1) - 1.1037 * img(x,y,2) + 1.7006 * img(x,y,3);
  end
end

rgb(:,:,1) = R;
rgb(:,:,2) = G;
rgb(:,:,3) = B;

imwrite(rgb,'YIQ2RGB.jpg');

figure, imshow(rgb);

Result for YIQ2RGB

Some said that i used to convert the image to float64 before manipulates it. Already tried that, but nothing changed. I also used astype(np.uint8) to convert float64 to uint8 to avoid values outside [0..255]. In MATLAB there is no such problem.