【OpenCV】OpenCV3以降でDense SIFTを使いたい

画像から特徴量抽出する方法として、Dense SIFTを使いたいと思ったのですが、何故かOpenCV2のあるバージョンで削除されてしまったようです。ただ幸いkeypointを指定することでDense SIFTを実施できるようなのでメモします（とはいえSIFTの特許の問題があるので2019年3月までは様子見、もしくは別の抽出器を利用でしょうか）。

# dense_feature_detector.py

import cv2

class DenseFeatureDetector(object):
    def __init__(self, detector, step, scale, start):
        self._detector = detector
        self._step = step
        self._scale = scale
        self._start = start
        pass

    def detect(self, image):
        # Convert image to gray if it is color
        if len(image.shape) == 3:
            gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        else:
            gray_image = image

        # Create dense keypoints
        keypoints = self._create_keypoints(gray_image)
        _, features = self._detector.compute(image, keypoints)
        return keypoints, features

    def _create_keypoints(self, gray_image):
        keypoints = []
        rows, cols = gray_image.shape
        for y in range(self._start, rows, self._step):
            for x in range(self._start, cols, self._step):
                keypoints.append(cv2.KeyPoint(float(x), float(y), self._scale))
        return keypoints

# main.py

import cv2
from dense_feature_detector import DenseFeatureDetector

if __name__ == '__main__':
    image = cv2.imread('lenna.jpg')
    sift = cv2.xfeatures2d.SIFT_create()
    detector = DenseFeatureDetector(sift, step=15, scale=15, start=15)
    keypoints, features = detector.detect(image)
    dense_keypoints_on_image = cv2.drawKeypoints(image, keypoints, None)
    cv2.imwrite('dense.png', dense_keypoints_on_image)