[Fix] Update files related to mim download dataset (#2635)

open-mmlab · Sep 6, 2023 · 9349a72 · 9349a72
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diff --git a/dataset-index.yml b/dataset-index.yml
@@ -1,39 +1,40 @@
+openxlab: true
 kinetics400:
-  dataset: Kinetics-400
+  dataset: OpenMMLab/Kinetics-400
   download_root: data
   data_root: data/kinetics400
-  script: tools/data/kinetics/k400_preprocess.sh
+  script: tools/data/kinetics/preprocess_k400.sh
 
 kinetics600:
-  dataset: Kinetics600
+  dataset: OpenMMLab/Kinetics600
   download_root: data
   data_root: data/kinetics600
-  script: tools/data/kinetics/k600_preprocess.sh
+  script: tools/data/kinetics/preprocess_k600.sh
 
 kinetics700:
-  dataset: Kinetics_700
+  dataset: OpenMMLab/Kinetics_700
   download_root: data
   data_root: data/kinetics700
-  script: tools/data/kinetics/k700_preprocess.sh
+  script: tools/data/kinetics/preprocess_k700.sh
 
 sthv2:
-  dataset: sthv2
+  dataset: OpenDataLab/sthv2
   download_root: data
   data_root: data/sthv2
   script: tools/data/sthv2/preprocess.sh
 
 ucf-101:
-  dataset: UCF101
+  dataset: OpenDataLab/UCF101
   download_root: data
   data_root: data/ucf101
 
 finegym:
-  dataset: FineGym
+  dataset: OpenDataLab/FineGym
   download_root: data
   data_root: data/gym
 
 diving48:
-  dataset: diving48
+  dataset: OpenDataLab/diving48
   download_root: data
   data_root: data/diving48
   script: tools/data/diving48/preprocess.sh
diff --git a/tools/data/diving48/README.md b/tools/data/diving48/README.md
@@ -21,10 +21,10 @@ For basic dataset information, you can refer to the official dataset [website](h
 ````{group-tab} Download by MIM
 MIM supports downloading from OpenDataLab and preprocessing Diving48 dataset with one command line.
 ```Bash
-# install OpenDataLab CLI tools
-pip install -U opendatalab
-# log in OpenDataLab
-odl login
+# install OpenXlab CLI tools
+pip install -U openxlab
+# log in OpenXLab
+openxlab login
 # download and preprocess by MIM
 mim download mmaction2 --dataset diving48
 ```

diff --git a/tools/data/diving48/README_zh-CN.md b/tools/data/diving48/README_zh-CN.md
@@ -21,10 +21,10 @@
 ````{group-tab} 使用 MIM 下载
 # MIM 支持下载 Diving48 数据集。用户可以通过一行命令，从 OpenDataLab 进行下载，并进行预处理。
 ```Bash
-# 安装 OpenDataLab CLI 工具
-pip install -U opendatalab
-# 登录 OpenDataLab
-odl login
+# 安装 OpenXLab CLI 工具
+pip install -U openxlab
+# 登录 OpenXLab
+openxlab login
 # 通过 MIM 进行数据集下载，预处理。注意这将花费较长时间
 mim download mmaction2 --dataset diving48
 ```

diff --git a/tools/data/diving48/preprocess.sh b/tools/data/diving48/preprocess.sh
@@ -3,6 +3,6 @@
 DOWNLOAD_DIR=$1
 DATA_ROOT=$2
 
-cat $DOWNLOAD_DIR/diving48/raw/*.tar.gz.*  | tar -xvz -C $(dirname $DATA_ROOT)
+cat $DOWNLOAD_DIR/OpenDataLab___diving48/raw/*.tar.gz.*  | tar -xvz -C $(dirname $DATA_ROOT)
 tar -xvf $DATA_ROOT/diving48.tar -C $(dirname $DATA_ROOT)
 rm $DATA_ROOT/diving48.tar
diff --git a/tools/data/kinetics/README.md b/tools/data/kinetics/README.md
@@ -38,10 +38,10 @@ All experiments on Kinetics in MMAction2 are based on this version, we recommend
 MIM supports downloading from OpenDataLab and preprocessing Kinetics-400/600/700 dataset with one command line.
 
 ```Bash
-# install OpenDataLab CLI tools
-pip install -U opendatalab
-# log in OpenDataLab
-odl login
+# install OpenXlab CLI tools
+pip install -U openxlab
+# log in OpenXLab
+openxlab login
 # download and preprocess Kinetics-400 by MIM. Note that this might take a long time.
 mim download mmaction2 --dataset kinetics400
 # download and preprocess Kinetics-600 by MIM. Note that this might take a long time.

diff --git a/tools/data/kinetics/README_zh-CN.md b/tools/data/kinetics/README_zh-CN.md
@@ -36,10 +36,10 @@ MMAction2 代码仓库中提供的 Kinetics 实验性能，都是基于这个版
 
 # MIM 支持下载 Kinetics-400/600/700 数据集。用户可以通过一行命令，从 OpenDataLab 进行下载，并进行预处理。
 ```Bash
-# 安装 OpenDataLab CLI 工具
-pip install -U opendatalab
-# 登录 OpenDataLab
-odl login
+# 安装 OpenXLab CLI 工具
+pip install -U openxlab
+# 登录 OpenXLab
+openxlab login
 # 通过 MIM 进行 Kinetics-400 数据集下载，预处理。注意这将花费较长时间
 mim download mmaction2 --dataset kinetics400
 # 通过 MIM 进行 Kinetics-600 数据集下载，预处理。注意这将花费较长时间

diff --git a/tools/data/kinetics/preprocess_k400.sh b/tools/data/kinetics/preprocess_k400.sh
@@ -5,5 +5,5 @@ set -x
 DOWNLOAD_DIR=$1
 DATA_ROOT=$2
 
-cat $DOWNLOAD_DIR/Kinetics-400/raw/*.tar.gz*  | tar -xvz -C $(dirname $DATA_ROOT)
+cat $DOWNLOAD_DIR/OpenMMLab___Kinetics-400/raw/*.tar.gz*  | tar -xvz -C $(dirname $DATA_ROOT)
 mv $(dirname $DATA_ROOT)/Kinetics-400 $DATA_ROOT
diff --git a/tools/data/kinetics/preprocess_k600.sh b/tools/data/kinetics/preprocess_k600.sh
@@ -5,5 +5,5 @@ set -x
 DOWNLOAD_DIR=$1
 DATA_ROOT=$2
 
-cat $DOWNLOAD_DIR/Kinetics600/raw/*.tar.gz*  | tar -xvz -C $(dirname $DATA_ROOT)
+cat $DOWNLOAD_DIR/OpenMMLab___Kinetics600/raw/*.tar.gz*  | tar -xvz -C $(dirname $DATA_ROOT)
 mv $(dirname $DATA_ROOT)/Kinetics600 $DATA_ROOT
diff --git a/tools/data/kinetics/preprocess_k700.sh b/tools/data/kinetics/preprocess_k700.sh
@@ -5,5 +5,5 @@ set -x
 DOWNLOAD_DIR=$1
 DATA_ROOT=$2
 
-cat $DOWNLOAD_DIR/Kinetics_700/raw/*.tar.gz*  | tar -xvz -C $(dirname $DATA_ROOT)
+cat $DOWNLOAD_DIR/OpenMMLab___Kinetics_700/raw/*.tar.gz*  | tar -xvz -C $(dirname $DATA_ROOT)
 mv $(dirname $DATA_ROOT)/Kinetics_700 $DATA_ROOT
diff --git a/tools/data/kinetics710/README.md b/tools/data/kinetics710/README.md
@@ -25,10 +25,10 @@ Before we start, please make sure that the directory is located at `$MMACTION2`.
 Kinetics-710 is a video benchmark based on Kinetics-400/600/700, which merges the training set of these Kinetics datasets, and deletes the repeated videos according to Youtube IDs. MMAction2 provides an annotation file based on the Kinetics-400/600/700 on [OpenDataLab](https://opendatalab.com/). So we suggest you download Kinetics-400/600/700 first from OpenDataLab by [MIM](https://github.com/open-mmlab/mim).
 
 ```shell
-# install OpenDataLab CLI tools
-pip install -U opendatalab
-# log in OpenDataLab
-odl login
+# install OpenXlab CLI tools
+pip install -U openxlab
+# log in OpenXLab
+openxlab login
 # download Kinetics-400/600/700, note that this might take a long time.
 mim download mmaction2 --dataset kinetics400
 mim download mmaction2 --dataset kinetics600

diff --git a/tools/data/kinetics710/README_zh-CN.md b/tools/data/kinetics710/README_zh-CN.md
@@ -23,10 +23,10 @@
 Kinetics-710 是基于 Kinetics-400/600/700 的视频数据集，它合并了这些 Kinetics 数据集的训练集，并根据 Youtube ID 删除了重复的视频。MMAction2 提供了一个基于 Kinetics-400/600/700 的 OpenDataLab 版本的标注文件，你可以通过 [MIM](https://github.com/open-mmlab/mim) 从 OpenDataLab 下载。
 
 ```shell
-# 安装 OpenDataLab CLI 工具
-pip install -U opendatalab
-# 登录 OpenDataLab
-odl login
+# 安装 OpenXLab CLI 工具
+pip install -U openxlab
+# 登录 OpenXLab
+openxlab login
 # 下载 Kinetics-400/600/700，注意这可能需要很长时间。
 mim download mmaction2 --dataset kinetics400
 mim download mmaction2 --dataset kinetics600

diff --git a/tools/data/sthv2/README.md b/tools/data/sthv2/README.md
@@ -22,10 +22,10 @@ For basic dataset information, you can refer to the dataset [website](https://de
 ````{group-tab} Download by MIM
 MIM supports downloading from OpenDataLab and preprocessing Something-Something V2 dataset with one command line.
 ```Bash
-# install OpenDataLab CLI tools
-pip install -U opendatalab
-# log in OpenDataLab
-odl login
+# install OpenXlab CLI tools
+pip install -U openxlab
+# log in OpenXLab
+openxlab login
 # download and preprocess by MIM
 mim download mmaction2 --dataset sthv2
 ```

diff --git a/tools/data/sthv2/README_zh-CN.md b/tools/data/sthv2/README_zh-CN.md
@@ -22,10 +22,10 @@
 ````{group-tab} 使用 MIM 下载
 # MIM 支持下载 Something-Something V2 数据集。用户可以通过一行命令，从 OpenDataLab 进行下载，并进行预处理。
 ```Bash
-# 安装 OpenDataLab CLI 工具
-pip install -U opendatalab
-# 登录 OpenDataLab
-odl login
+# 安装 OpenXLab CLI 工具
+pip install -U openxlab
+# 登录 OpenXLab
+openxlab login
 # 通过 MIM 进行数据集下载，预处理。注意这将花费较长时间
 mim download mmaction2 --dataset sthv2
 ```

diff --git a/tools/data/sthv2/preprocss.sh b/tools/data/sthv2/preprocss.sh
@@ -3,6 +3,6 @@
 DOWNLOAD_DIR=$1
 DATA_ROOT=$2
 
-cat $DOWNLOAD_DIR/sthv2/raw/*.tar.gz  | tar -xvz -C $(dirname $DATA_ROOT)
+cat $DOWNLOAD_DIR/OpenDataLab___sthv2/raw/*.tar.gz  | tar -xvz -C $(dirname $DATA_ROOT)
 tar -xvf $DATA_ROOT/sthv2.tar -C $(dirname $DATA_ROOT)
 rm $DATA_ROOT/sthv2.tar