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