Fbow
FBOW (Fast Bag of Words) is an extremmely optimized version of the DBow2/DBow3 libraries.
Install / Use
/learn @rmsalinas/FbowREADME
FBOW
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.
Main features:
* 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
The main differences with DBOW2/3 are:
* Not yet implemented indexing of images.
Citing
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
Vocabularies
In directory vocabularies you have one already prepared for orb.
Test speed
Go to test and run the program test_dbow2VSfbow
License
This software is distributed under MIT License
Related Skills
node-connect
337.7kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
frontend-design
83.3kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
openai-whisper-api
337.7kTranscribe audio via OpenAI Audio Transcriptions API (Whisper).
commit-push-pr
83.3kCommit, push, and open a PR
