From 582878dd3da309e6d6177537c8998a0cb27b258c Mon Sep 17 00:00:00 2001 From: jeonhobeom Date: Mon, 12 Dec 2022 15:17:44 +0900 Subject: [PATCH] [Doc] Update EN README links for new doc structure Motivation #2113 break some critical links --- README.md | 30 +++++++++++++++--------------- 1 file changed, 15 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index 2560a0fccd..4283060c07 100644 --- a/README.md +++ b/README.md @@ -92,13 +92,13 @@ Find more new features in [1.x branch](https://github.com/open-mmlab/mmaction2/t - (2021-10-25) We provide a [guide](https://github.com/open-mmlab/mmaction2/blob/master/configs/skeleton/posec3d/custom_dataset_training.md) on how to train PoseC3D with custom datasets, [bit-scientist](https://github.com/bit-scientist) authored this PR! - (2021-10-16) We support **PoseC3D** on UCF101 and HMDB51, achieves 87.0% and 69.3% Top-1 accuracy with 2D skeletons only. Pre-extracted 2D skeletons are also available. -**Release**: v0.24.0 was released in 05/05/2022. Please refer to [changelog.md](docs/changelog.md) for details and release history. +**Release**: v0.24.0 was released in 05/05/2022. Please refer to [changelog.md](docs/en/changelog.md) for details and release history. ## Installation MMAction2 depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv), [MMDetection](https://github.com/open-mmlab/mmdetection) (optional), and [MMPose](https://github.com/open-mmlab/mmdetection)(optional). Below are quick steps for installation. -Please refer to [install.md](docs/install.md) for more detailed instruction. +Please refer to [install.md](docs/en/install.md) for more detailed instruction. ```shell conda create -n open-mmlab python=3.8 pytorch=1.10 cudatoolkit=11.3 torchvision -c pytorch -y @@ -114,16 +114,16 @@ pip3 install -e . ## Get Started -Please see [getting_started.md](docs/getting_started.md) for the basic usage of MMAction2. +Please see [getting_started.md](docs/en/getting_started.md) for the basic usage of MMAction2. There are also tutorials: -- [learn about configs](docs/tutorials/1_config.md) -- [finetuning models](docs/tutorials/2_finetune.md) -- [adding new dataset](docs/tutorials/3_new_dataset.md) -- [designing data pipeline](docs/tutorials/4_data_pipeline.md) -- [adding new modules](docs/tutorials/5_new_modules.md) -- [exporting model to onnx](docs/tutorials/6_export_model.md) -- [customizing runtime settings](docs/tutorials/7_customize_runtime.md) +- [learn about configs](docs/en/tutorials/1_config.md) +- [finetuning models](docs/en/tutorials/2_finetune.md) +- [adding new dataset](docs/en/tutorials/3_new_dataset.md) +- [designing data pipeline](docs/en/tutorials/4_data_pipeline.md) +- [adding new modules](docs/en/tutorials/5_new_modules.md) +- [exporting model to onnx](docs/en/tutorials/6_export_model.md) +- [customizing runtime settings](docs/en/tutorials/7_customize_runtime.md) A Colab tutorial is also provided. You may preview the notebook [here](demo/mmaction2_tutorial.ipynb) or directly [run](https://colab.research.google.com/github/open-mmlab/mmaction2/blob/master/demo/mmaction2_tutorial.ipynb) on Colab. @@ -262,16 +262,16 @@ Datasets marked with * are not fully supported yet, but related dataset preparat ## Benchmark -To demonstrate the efficacy and efficiency of our framework, we compare MMAction2 with some other popular frameworks and official releases in terms of speed. Details can be found in [benchmark](docs/benchmark.md). +To demonstrate the efficacy and efficiency of our framework, we compare MMAction2 with some other popular frameworks and official releases in terms of speed. Details can be found in [benchmark](docs/en/benchmark.md). ## Data Preparation -Please refer to [data_preparation.md](docs/data_preparation.md) for a general knowledge of data preparation. -The supported datasets are listed in [supported_datasets.md](docs/supported_datasets.md) +Please refer to [data_preparation.md](docs/en/data_preparation.md) for a general knowledge of data preparation. +The supported datasets are listed in [supported_datasets.md](docs/en/supported_datasets.md) ## FAQ -Please refer to [FAQ](docs/faq.md) for frequently asked questions. +Please refer to [FAQ](docs/en/faq.md) for frequently asked questions. ## Projects built on MMAction2 @@ -281,7 +281,7 @@ Currently, there are many research works and projects built on MMAction2 by user - Evidential Deep Learning for Open Set Action Recognition, ICCV 2021 **Oral**. [\[paper\]](https://arxiv.org/abs/2107.10161)[\[github\]](https://github.com/Cogito2012/DEAR) - Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspective, ICCV 2021 **Oral**. [\[paper\]](https://arxiv.org/abs/2103.17263)[\[github\]](https://github.com/xvjiarui/VFS) -etc., check [projects.md](docs/projects.md) to see all related projects. +etc., check [projects.md](docs/en/projects.md) to see all related projects. ## Contributing