91 lines
2.8 KiB
Python
91 lines
2.8 KiB
Python
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import numpy as np
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import cv2
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from matplotlib import pyplot as plt
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# Load the left and right images
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# in gray scale
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imgLeft = cv2.imread('image_l.jpg', 0)
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imgRight = cv2.imread('image_r.jpg', 0)
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# Detect the SIFT key points and
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# compute the descriptors for the
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# two images
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sift = cv2.SIFT_create()
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keyPointsLeft, descriptorsLeft = sift.detectAndCompute(imgLeft, None)
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keyPointsRight, descriptorsRight = sift.detectAndCompute(imgRight, None)
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assert(len(keyPointsLeft) == len(descriptorsLeft))
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assert(len(keyPointsRight) == len(descriptorsRight))
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# Create FLANN matcher object
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FLANN_INDEX_KDTREE = 0
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indexParams = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
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searchParams = dict(checks=50)
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flann = cv2.FlannBasedMatcher(indexParams, searchParams)
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matches = flann.knnMatch(descriptorsLeft, descriptorsRight, 2)
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# Apply ratio test
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goodMatches = []
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ptsLeft = []
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ptsRight = []
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for m, n in matches:
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if m.distance < 0.8 * n.distance:
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goodMatches.append([m])
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# ptsLeft.append(keyPointsLeft[m.trainIdx].pt)
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# ptsRight.append(keyPointsRight[n.trainIdx].pt)
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ptsLeft.append(keyPointsLeft[m.queryIdx].pt)
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ptsRight.append(keyPointsRight[m.trainIdx].pt)
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ptsLeft = np.int32(ptsLeft)
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ptsRight = np.int32(ptsRight)
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# r F l = 0 <- find f
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F, mask = cv2.findFundamentalMat(ptsLeft,
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ptsRight,
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cv2.FM_LMEDS)
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# We select only inlier points
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ptsLeft = ptsLeft[mask.ravel() == 1]
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ptsRight = ptsRight[mask.ravel() == 1]
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def drawlines(img1, img2, lines, pts1, pts2):
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r, c = img1.shape
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img1 = cv2.cvtColor(img1, cv2.COLOR_GRAY2BGR)
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img2 = cv2.cvtColor(img2, cv2.COLOR_GRAY2BGR)
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for i, (r, pt1, pt2) in enumerate(zip(lines, pts1, pts2)):
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color = tuple(np.random.randint(0, 255, 3).tolist())
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x0, y0 = map(int, [0, -r[2] / r[1]])
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x1, y1 = map(int, [c, -(r[2] + r[0] * c) / r[1]])
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img1 = cv2.line(img1, (x0, y0), (x1, y1), color, 1)
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img1 = cv2.circle(img1, tuple(pt1), 5, color, -1)
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img2 = cv2.circle(img2, tuple(pt2), 5, color, -1)
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return img1, img2
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# Find epilines corresponding to points
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# in right image (second image) and
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# drawing its lines on left image
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linesLeft = cv2.computeCorrespondEpilines(ptsRight.reshape(-1, 1, 2), 2, F)
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linesLeft = linesLeft.reshape(-1, 3)
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img5, img6 = drawlines(imgLeft, imgRight,
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linesLeft, ptsLeft,
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ptsRight)
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# Find epilines corresponding to
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# points in left image (first image) and
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# drawing its lines on right image
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linesRight = cv2.computeCorrespondEpilines(ptsLeft.reshape(-1, 1, 2), 1, F)
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linesRight = linesRight.reshape(-1, 3)
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img3, img4 = drawlines(imgRight, imgLeft,
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linesRight, ptsRight,
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ptsLeft)
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plt.subplot(121), plt.imshow(img5)
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plt.subplot(122), plt.imshow(img3)
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plt.show()
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