facebookresearch/pycls
A PyTorch research codebase for image classification implementing standard deep learning models with multi-GPU training support.
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pycls is an image classification research framework built in PyTorch, originally developed for visual recognition design space research. It supports rapid implementation and evaluation of research ideas with implementations of standard vision architectures including ResNet, ResNeXt, EfficientNet, and RegNet. The codebase includes a model zoo with pretrained weights and baseline results across various computational regimes.
Frequently asked
- What is facebookresearch/pycls?
- A PyTorch research codebase for image classification implementing standard deep learning models with multi-GPU training support.
- Is pycls open source?
- Yes — facebookresearch/pycls is open source, released under the MIT license.
- What language is pycls written in?
- facebookresearch/pycls is primarily written in Python.
- How popular is pycls?
- facebookresearch/pycls has 2.2k stars on GitHub.
- Where can I find pycls?
- facebookresearch/pycls is on GitHub at https://github.com/facebookresearch/pycls.