opencv python SIFT特征检测

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