Visualize the epilines of both images. Full article for context and remaining code: https://www.andreasjakl.com/understand-and-apply-stereo-rectification-for-depth-maps-part-2/

visualize_epilines.py

# Visualize epilines
# Adapted from: https://docs.opencv.org/master/da/de9/tutorial_py_epipolar_geometry.html
def drawlines(img1src, img2src, lines, pts1src, pts2src):
    ''' img1 - image on which we draw the epilines for the points in img2
        lines - corresponding epilines '''
    r, c = img1src.shape
    img1color = cv.cvtColor(img1src, cv.COLOR_GRAY2BGR)
    img2color = cv.cvtColor(img2src, cv.COLOR_GRAY2BGR)
    # Edit: use the same random seed so that two images are comparable!
    np.random.seed(0)
    for r, pt1, pt2 in zip(lines, pts1src, pts2src):
        color = tuple(np.random.randint(0, 255, 3).tolist())
        x0, y0 = map(int, [0, -r[2]/r[1]])
        x1, y1 = map(int, [c, -(r[2]+r[0]*c)/r[1]])
        img1color = cv.line(img1color, (x0, y0), (x1, y1), color, 1)
        img1color = cv.circle(img1color, tuple(pt1), 5, color, -1)
        img2color = cv.circle(img2color, tuple(pt2), 5, color, -1)
    return img1color, img2color


# Find epilines corresponding to points in right image (second image) and
# drawing its lines on left image
lines1 = cv.computeCorrespondEpilines(
    pts2.reshape(-1, 1, 2), 2, fundamental_matrix)
lines1 = lines1.reshape(-1, 3)
img5, img6 = drawlines(img1, img2, lines1, pts1, pts2)

# Find epilines corresponding to points in left image (first image) and
# drawing its lines on right image
lines2 = cv.computeCorrespondEpilines(
    pts1.reshape(-1, 1, 2), 1, fundamental_matrix)
lines2 = lines2.reshape(-1, 3)
img3, img4 = drawlines(img2, img1, lines2, pts2, pts1)

plt.subplot(121), plt.imshow(img5)
plt.subplot(122), plt.imshow(img3)
plt.suptitle("Epilines in both images")
plt.show()