Practical overview
When it fits
Use Fbow when an OpenCV-based application needs visual vocabulary creation or descriptor-to-bag-of-words conversion and those operations belong in a C++ library.
Who it is for
- C++ developers building OpenCV-based computer-vision workflows.
- Researchers and engineers who need to create visual vocabularies or convert image descriptors into bag-of-words representations.
Documented uses
- Create a visual vocabulary from a set of images.
- Transform binary or floating-point image descriptors into bag-of-words representations.
- Load a vocabulary for visual feature processing, including the included ORB vocabulary.
Requirements & limits
The project is presented as open-source software distributed under the MIT License.
- OpenCV is the documented dependency.
- AVX, SSE and MMX optimizations are described; the README's transformation speed comparison specifies machines with AVX instructions.
- Image indexing is not implemented.
- An ORB vocabulary is provided in the repository.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Use the included ORB vocabulary for descriptor processing
Load the prepared ORB vocabulary and transform image descriptors into a bag-of-words representation.
Before you start
- FBOW, which depends on OpenCV.
- The ORB vocabulary included in the repository’s vocabularies directory.
Steps
Locate the prepared ORB vocabulary in the repository’s vocabularies directory.
Load the vocabulary with FBOW.
Transform image descriptors into a bag-of-words representation; FBOW supports binary and real-valued descriptors.
Expected outcome
Image descriptors are represented as bag-of-words using the prepared ORB vocabulary.
Guide limitations
- Image indexing is not implemented.
- The README does not provide the specific API calls or commands for loading and transforming descriptors.
Run the documented FBOW speed comparison
Run the repository’s test program for comparing FBOW and DBOW2 speed.
Before you start
- A checked-out FBOW repository with its test directory.
Steps
Go to the test directory.
Run the program named test_dbow2VSfbow.
Expected outcome
The documented speed comparison program runs; the README does not specify particular results.
Guide limitations
- The README does not provide build or invocation details beyond the program name and test directory.
- The README’s AVX speed comparison applies to machines with AVX instructions.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 18 October 2026
- Original website title
- rmsalinas/fbow · Official homepage title · retained in its source language