一、環境準備

目前 Opencv 有2.x 和 3.x 版本，兩個版本之間的差異主要是一些功能函式被放置到了不同的功能模組，因此大多數情況兩個版本的程式碼並不能通用。建議安裝 Anaconda，自行下載相應版本。直接命令安裝:

conda install -c menpo opencv3
pip install imagedt

二、SIFT/SURF 特徵提取與匹配

# coding: utf-8
from matplotlib import pyplot as plt
from imagedt.decorator import time_cost
import cv2
print
 
 'cv version: ', cv2.__version__


def bgr_rgb(img):
    (r, g, b) = cv2.split(img)
    return cv2.merge([b, g, r])


def orb_detect(image_a, image_b):
    # feature match
    orb = cv2.ORB_create()

    kp1, des1 = orb.detectAndCompute(image_a, None)
    kp2, des2 = orb.detectAndCompute(image_b, None
 
)

    # create BFMatcher object
    bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)

    # Match descriptors.
    matches = bf.match(des1, des2)

    # Sort them in the order of their distance.
    matches = sorted(matches, key=lambda x: x.distance)

    # Draw first 10 matches.
    img3 = cv2.drawMatches(image_a, kp1, image_b, kp2, matches[:100
 
], None, flags=2)

    return bgr_rgb(img3)

@time_cost
def sift_detect(img1, img2, detector='surf'):
    if detector.startswith('si'):
        print "sift detector......"
        sift = cv2.xfeatures2d.SURF_create()
    else:
        print "surf detector......"
        sift = cv2.xfeatures2d.SURF_create()

    # find the keypoints and descriptors with SIFT
    kp1, des1 = sift.detectAndCompute(img1, None)
    kp2, des2 = sift.detectAndCompute(img2, None)

    # BFMatcher with default params
    bf = cv2.BFMatcher()
    matches = bf.knnMatch(des1, des2, k=2)

    # Apply ratio test
    good = [[m] for m, n in matches if m.distance < 0.5 * n.distance]

    # cv2.drawMatchesKnn expects list of lists as matches.
    img3 = cv2.drawMatchesKnn(img1, kp1, img2, kp2, good, None, flags=2)

    return bgr_rgb(img3)


if __name__ == "__main__":
    # load image
    image_a = cv2.imread('./img1.jpg')
    image_b = cv2.imread('./img2.png')

    # ORB
    # img = orb_detect(image_a, image_b)

    # SIFT or SURF
    img = sift_detect(image_a, image_b)

    plt.imshow(img)
    plt.show()

三、輸出展示

cv version:  3.1.0
surf detector......
==> time-cost: 0.187422     sift_detect

Output:

img1

img2