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dbow-python's Introduction

DBow_Python

DBow_Python是DBow的python精简版。

  • ORB特征提取
  • Kmeans聚类
  • 字典树结构保存字典文件

生成的字典文件能直接用于orb slam2中。

Usage

  • Python2 + Opencv3 + Numpy

生成特定场景的视觉词典

  • 替换imgages中的图片，图片尽可能多
  • 修改main.py中N，K，L，一般K设为10，L设为5
  • 在orb.py中，修改每幅图像提取特征点的数量，为了增加字典中单词的数量

比较图像之间的相似度

创建视觉词典就是为了比较两幅图像之间的相似度，只是采用bow模型，降低复杂度而已。每幅图像可以用视觉词典中的单词向量表示，再计算向量之间的余弦相似度。在字典树中，叶子节点就是单词，比如创建5，3的树，就会有K**L个单词，一幅图像就可以表示为125维向量。
结果如下：

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