修复同一底库训练出词袋不同问题； 添加获取单词数、词典训练层数接口； 修复单词的id 大于总单词数的问题； 修复 调用transform（features，level，fBoW，fBoW2） 与调用fBoW=transform（features）， fBoW结果不一致问题；
FBOW (Fast Bag of Words) is an extremmely optimized version of the DBow2/DBow3 libraries. The library is highly optimized to speed up the Bag of Words creation using AVX,SSE and MMX instructions. In loading a vocabulary, fbow is ~80x faster than DBOW2 (see tests directory and try). In transforming an image into a bag of words using on machines with AVX instructions, it is ~6.4x faster.
* Only depends on OpenCV
* Any type of descriptors allowed out of the box (binary and real)
* Dictionary creation from a set of images. Bugs found in DBOW2/3 corrected.
* Extremmely fast bow creation using specialized versions using AVX,SSE and MMX instructions both for binary and floating point descriptors.
* Very fast load of vocabularies
* Not yet implemented indexing of images.
If you use this project in academic research you must cite us. This project is part of the ucoslam project. Visit ucoslam.com for more information
In directory vocabularies you have one already prepared for orb.
Go to test and run the program test_dbow2VSfbow
This software is distributed under MIT License