fvcore
fvcore is a light-weight core library that provides the most common and essential functionality shared in various computer vision frameworks developed in FAIR, such as Detectron2, PySlowFast ClassyVision. All components in this library are type-annotated, tested, and benchmarked.
The computer vision team in FAIR is responsible for maintaining this library.
Features:
Besides some basic utilities, the most notable features of fvcore are:
- A hierarchical per-operator flop counting tool: see this note for details.
- Recursive parameter counting: Doc.
Install:
fvcore requires pytorch and python >= 3.6.
Use one of the following ways to install:
1. Install from PyPI (updated nightly)
pip install -U fvcore
2. Install from Anaconda Cloud (updated nightly)
conda install -c fvcore -c iopath -c conda-forge fvcore
3. Install latest from GitHub
pip install -U 'git+https://github.com/facebookresearch/fvcore'
4. Install from a local clone
git clone https://github.com/facebookresearch/fvcore
pip install -e fvcore
License
This library is released under the Apache 2.0 license.