opencv python SIFT特征检测
SIFT, python, opencv
·
import numpy as np
import cv2
import os
test_path = './'
for files in os.listdir(test_path):
img = cv2.imread(test_path + files)
sift = cv2.xfeatures2d.SIFT_create()
# 创建FLANN匹配对象
FLANN_INDEX_KDTREE = 0
indexParams = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
# 索引里的树应该被递归遍历的次数
searchParams = dict(checks=50)
flann = cv2.FlannBasedMatcher(indexParams, searchParams)
kp, des = sift.detectAndCompute(img, None)
# 构建半透明图片。feature points 画在半透明图片上,视觉效果更清楚。
bottom = np.zeros(img.shape, np.uint8)
bottom.fill(255)
top = img.copy()
overlapping = cv2.addWeighted(bottom, 0.5, top, 0.5, 0)
# 在关键点的位置上绘制大小为keypoint小圆圈
overlapping = cv2.drawKeypoints(overlapping, kp, img)
# 存储结果
cv2.imwrite('output.png', overlapping)
opencv 版本 3.4.2
某些报错是可以这样解决的; img = img.astype(np.uint8)
Input:
Output
更多推荐
所有评论(0)