Hi,

I’m fairly new to OpenCV so please excuse my very limited understanding.

I am working through the OpenCV tutorials and I’m currently working on calculating the Epipolar lines from two images. However, even though I’m using the exact code from the OpenCV tutorial and the same test images I’m getting very strange results.

If anybody could point me in the right direction for a solution it would be greatly appreciated

My Result:

Code:

```
import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
def drawlines(img1, img2, lines, pts1, pts2):
"""img1 - image on witch we draw the epilines for the points in img2
lines - corresponding epilines"""
r, c = img1.shape
img1 = cv.cvtColor(img1, cv.COLOR_GRAY2BGR)
img2 = cv.cvtColor(img2, cv.COLOR_GRAY2BGR)
for r,pt1,pt2 in zip(lines, pts1, pts2):
color = tuple(np.random.randint(0, 255, 3).tolist())
x0, y0 = map(int, [0, -r[0]/r[1]])
x1, y1 = map(int, [c, -(r[2] + r[0]*c/r[1])])
img1 = cv.line(img1, (x0, y0), (x1, y1), color, 1)
img1 = cv.circle(img1, tuple(pt1), 3, color, -1)
img2 = cv.circle(img2, tuple(pt2), 3, color, -1)
return img1, img2
if __name__ == '__main__':
img1 = cv.imread('left.jpg', 0) # queryingImage # left image
img2 = cv.imread('right.jpg', 0) # trainImage # right image
sift = cv.xfeatures2d.SIFT_create()
# find the keypoints and descriptors with SIFT
kp1, des1 = sift.detectAndCompute(img1, None)
kp2, des2 = sift.detectAndCompute(img2, None)
# FLANN parameters
FLANN_INDEX_KDTREE = 0
index_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 5)
search_params = dict(checks = 50)
flann = cv.FlannBasedMatcher(index_params, search_params)
matches = flann.knnMatch(des1, des2, k=2)
good = []
pts1 = []
pts2 = []
# ratio test as per Lowe's paper
for i, (m,n) in enumerate(matches):
if m.distance < 0.8*n.distance:
good.append(m)
pts1.append(kp1[m.queryIdx].pt)
pts2.append(kp2[m.trainIdx].pt)
pts1 = np.int32(pts1)
pts2 = np.int32(pts2)
F, mask = cv.findFundamentalMat(pts1, pts2, cv.FM_LMEDS) #F = fundamental matrix
print(F)
# We select only inlier points
pts1 = pts1[mask.ravel() == 1]
pts2 = pts2[mask.ravel() == 1]
# 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 ,F)
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, F)
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.show()
```