MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project.
Documentation: https://mmclassification.readthedocs.io/en/latest/
- Various backbones and pretrained models
- Bag of training tricks
- Large-scale training configs
- High efficiency and extensibility
This project is released under the Apache 2.0 license.
Results and models are available in the model zoo.
Supported backbones:
- ResNet
- ResNeXt
- SE-ResNet
- SE-ResNeXt
- RegNet
- ShuffleNetV1
- ShuffleNetV2
- MobileNetV2
- MobileNetV3
Please refer to install.md for installation and dataset preparation.
Please see getting_started.md for the basic usage of MMClassification. There are also tutorials for finetuning models, adding new dataset, designing data pipeline, and adding new modules.
We appreciate all contributions to improve MMClassification. Please refer to CONTRUBUTING.md for the contributing guideline.
MMClassification is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new classifiers.