mmclassification/docs/en/index.rst

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Welcome to MMPretrain's documentation!
============================================
MMPretrain is a newly upgraded open-source framework for pre-training.
It has set out to provide multiple powerful pre-trained backbones and
support different pre-training strategies. MMPretrain originated from the
famous open-source projects
`MMClassification <https://github.com/open-mmlab/mmclassification/tree/1.x>`_
and `MMSelfSup <https://github.com/open-mmlab/mmselfsup>`_, and is developed
with many exiciting new features. The pre-training stage is essential for
vision recognition currently. With the rich and strong pre-trained models,
we are currently capable of improving various downstream vision tasks.
Our primary objective for the codebase is to become an easily accessible and
user-friendly library and to streamline research and engineering. We
detail the properties and design of MMPretrain across different sections.
Hands-on Roadmap of MMPretrain
-------------------------------
To help users quickly utilize MMPretrain, we recommend following the hands-on
roadmap we have created for the library:
- For users who want to try MMPretrain, we suggest reading the GetStarted_
section for the environment setup.
- For basic usage, we refer users to UserGuides_ for utilizing various
algorithms to obtain the pre-trained models and evaluate their performance
in downstream tasks.
- For those who wish to customize their own algorithms, we provide
AdvancedGuides_ that include hints and rules for modifying code.
- To find your desired pre-trained models, users could check the ModelZoo_,
which features a summary of various backbones and pre-training methods and
introfuction of different algorithms.
- Additionally, we provide Analysis_ and Visualization_ tools to help
diagnose algorithms.
- Besides, if you have any other questions or concerns, please refer to the
Notes_ section for potential answers.
We always welcome *PRs* and *Issues* for the betterment of MMPretrain.
.. _GetStarted:
.. toctree::
:maxdepth: 1
:caption: Get Started
get_started.md
.. _UserGuides:
.. toctree::
:maxdepth: 1
:caption: User Guides
user_guides/config.md
user_guides/dataset_prepare.md
user_guides/inference.md
user_guides/train.md
user_guides/test.md
user_guides/downstream.md
.. _AdvancedGuides:
.. toctree::
:maxdepth: 1
:caption: Advanced Guides
advanced_guides/datasets.md
advanced_guides/pipeline.md
advanced_guides/modules.md
advanced_guides/schedule.md
advanced_guides/runtime.md
advanced_guides/evaluation.md
advanced_guides/convention.md
.. _ModelZoo:
.. toctree::
:maxdepth: 1
:caption: Model Zoo
:glob:
modelzoo_statistics.md
papers/*
.. _Visualization:
.. toctree::
:maxdepth: 1
:caption: Visualization
useful_tools/dataset_visualization.md
useful_tools/scheduler_visualization.md
useful_tools/cam_visualization.md
useful_tools/t-sne_visualization.md
.. _Analysis:
.. toctree::
:maxdepth: 1
:caption: Analysis Tools
useful_tools/print_config.md
useful_tools/verify_dataset.md
useful_tools/log_result_analysis.md
useful_tools/complexity_analysis.md
useful_tools/confusion_matrix.md
useful_tools/shape_bias.md
.. toctree::
:maxdepth: 1
:caption: Deployment
useful_tools/model_serving.md
.. toctree::
:maxdepth: 1
:caption: Migration
migration.md
.. toctree::
:maxdepth: 1
:caption: API Reference
mmpretrain.apis <api/apis>
mmpretrain.engine <api/engine>
mmpretrain.datasets <api/datasets>
Data Process <api/data_process>
mmpretrain.models <api/models>
mmpretrain.structures <api/structures>
mmpretrain.visualization <api/visualization>
mmpretrain.evaluation <api/evaluation>
mmpretrain.utils <api/utils>
.. _Notes:
.. toctree::
:maxdepth: 1
:caption: Notes
notes/contribution_guide.md
notes/projects.md
notes/changelog.md
notes/faq.md
notes/pretrain_custom_dataset.md
notes/finetune_custom_dataset.md
.. toctree::
:maxdepth: 1
:caption: Device Support
device/npu.md
Indices and tables
==================
* :ref:`genindex`
* :ref:`search`