Update README.md

Author: thucbx99

DATASETS.md

@@ -0,0 +1,94 @@
+## Notice (2023-08-01)
+
+### Transfer-Learning-Library Dataset Link Failure Issue
+Dear users,
+
+We sincerely apologize to inform you that the dataset links of Transfer-Learning-Library have become invalid due to a cloud storage failure, resulting in many users being unable to download the datasets properly recently.
+
+We are working diligently to resolve this issue and plan to restore the links as soon as possible. Currently, we have already restored some dataset links, and they have been updated on the master branch. You can obtain the latest version by running "git pull."
+
+As the version on PyPI has not been updated yet, please temporarily uninstall the old version by running "pip uninstall tllib" before installing the new one.
+
+In the future, we are planning to store the datasets on both Baidu Cloud and Google Cloud to provide more stable download links.
+
+Additionally, a small portion of datasets that were backed up on our local server have also been lost due to a hard disk failure. For these datasets, we need to re-download and verify them, which might take longer to restore the links.
+
+Within this week, we will release the updated dataset and confirm the list of datasets without backup. For datasets without backup, if you have previously downloaded them locally, please contact us via email. Your support is highly appreciated.
+
+Once again, we apologize for any inconvenience caused and thank you for your understanding.
+
+Sincerely,
+
+The Transfer-Learning-Library Team
+
+## Update (2023-08-09)
+
+Most of the dataset links have been restored at present. The confirmed datasets without backups are as follows:
+
+- Classification
+  - COCO70
+  - EuroSAT
+  - PACS
+  - PatchCamelyon
+  - [Partial Domain Adaptation]
+    - CaltechImageNet
+
+- Keypoint Detection
+  - Hand3DStudio
+  - LSP
+  - SURREAL
+
+- Object Detection
+  - Comic
+
+- Re-Identification
+  - PersonX
+  - UnrealPerson
+
+**For these datasets, if you had previously downloaded them locally, please contact us via email. We greatly appreciate everyone's support.**
+
+## Notice (2023-08-01)
+
+### Transfer-Learning-Library数据集链接失效问题
+
+各位使用者，我们很抱歉通知大家，最近Transfer-Learning-Library的数据集链接因为云盘故障而失效，导致很多使用者无法正常下载数据集。
+
+我们正在全力以赴解决这一问题，并计划在最短的时间内恢复链接。目前我们已经恢复了部分数据集链接，更新在master分支上，您可以通过git pull来获取最新的版本。
+
+由于pypi上的版本还未更新，暂时请首先通过pip uninstall tllib卸载旧版本。
+
+日后我们计划将数据集存储在百度云和谷歌云上，提供更加稳定的下载链接。
+
+另外，小部分数据集在我们本地服务器上的备份也由于硬盘故障而丢失，对于这些数据集我们需要重新下载并验证，可能需要更长的时间来恢复链接。
+
+我们会在本周内发布已经更新的数据集和确认无备份的数据集列表，对于无备份的数据集，如果您之前有下载到本地，请通过邮件联系我们，非常感谢大家的支持。
+
+再次向您表达我们的歉意，并感谢您的理解。
+
+Transfer-Learning-Library团队
+
+## Update (2023-08-09)
+
+目前大部分数据集的链接已经恢复，确认无备份的数据集如下：
+
+- Classification
+  - COCO70
+  - EuroSAT
+  - PACS
+  - PatchCamelyon
+  - [Partial Domain Adaptation]
+    - CaltechImageNet
+
+- Keypoint Detection
+  - Hand3DStudio
+  - LSP
+  - SURREAL
+
+- Object Detection
+  - Comic
+
+- Re-Identification
+  - PersonX
+  - UnrealPerson
+
+**对于这些数据集，如果您之前有下载到本地，请通过邮件联系我们，非常感谢大家的支持。**

README.md

@@ -16,94 +16,7 @@ We upload an offline version of documentation [here](/docs/html.zip). You can do
 
 ## Notice (2023-08-09)
 
-目前大部分数据集的链接已经恢复，确认无备份的数据集如下：
-
-- Classification
-  - COCO70
-  - EuroSAT
-  - PACS
-  - PatchCamelyon
-  - [Partial Domain Adaptation]
-    - CaltechImageNet
-
-- Keypoint Detection
-  - Hand3DStudio
-  - LSP
-  - SURREAL
-
-- Object Detection
-  - Comic
-
-- Re-Identification
-  - PersonX
-  - UnrealPerson
-
-对于这些数据集，如果您之前有下载到本地，请通过邮件联系我们，非常感谢大家的支持。
-
-Most of the dataset links have been restored at present. The confirmed datasets without backups are as follows:
-
-- Classification
-  - COCO70
-  - EuroSAT
-  - PACS
-  - PatchCamelyon
-  - [Partial Domain Adaptation]
-    - CaltechImageNet
-
-- Keypoint Detection
-  - Hand3DStudio
-  - LSP
-  - SURREAL
-
-- Object Detection
-  - Comic
-
-- Re-Identification
-  - PersonX
-  - UnrealPerson
-
-For these datasets, if you had previously downloaded them locally, please contact us via email. We greatly appreciate everyone's support.
-
-## Notice (2023-08-01)
-
-### Transfer-Learning-Library数据集链接失效问题
-
-各位使用者，我们很抱歉通知大家，最近Transfer-Learning-Library的数据集链接因为云盘故障而失效，导致很多使用者无法正常下载数据集。
-
-我们正在全力以赴解决这一问题，并计划在最短的时间内恢复链接。目前我们已经恢复了部分数据集链接，更新在master分支上，您可以通过git pull来获取最新的版本。
-
-由于pypi上的版本还未更新，暂时请首先通过pip uninstall tllib卸载旧版本。
-
-日后我们计划将数据集存储在百度云和谷歌云上，提供更加稳定的下载链接。
-
-另外，小部分数据集在我们本地服务器上的备份也由于硬盘故障而丢失，对于这些数据集我们需要重新下载并验证，可能需要更长的时间来恢复链接。
-
-我们会在本周内发布已经更新的数据集和确认无备份的数据集列表，对于无备份的数据集，如果您之前有下载到本地，请通过邮件联系我们，非常感谢大家的支持。
-
-再次向您表达我们的歉意，并感谢您的理解。
-
-Transfer-Learning-Library团队
-
-### Transfer-Learning-Library Dataset Link Failure Issue
-Dear users,
-
-We sincerely apologize to inform you that the dataset links of Transfer-Learning-Library have become invalid due to a cloud storage failure, resulting in many users being unable to download the datasets properly recently.
-
-We are working diligently to resolve this issue and plan to restore the links as soon as possible. Currently, we have already restored some dataset links, and they have been updated on the master branch. You can obtain the latest version by running "git pull."
-
-As the version on PyPI has not been updated yet, please temporarily uninstall the old version by running "pip uninstall tllib" before installing the new one.
-
-In the future, we are planning to store the datasets on both Baidu Cloud and Google Cloud to provide more stable download links.
-
-Additionally, a small portion of datasets that were backed up on our local server have also been lost due to a hard disk failure. For these datasets, we need to re-download and verify them, which might take longer to restore the links.
-
-Within this week, we will release the updated dataset and confirm the list of datasets without backup. For datasets without backup, if you have previously downloaded them locally, please contact us via email. Your support is highly appreciated.
-
-Once again, we apologize for any inconvenience caused and thank you for your understanding.
-
-Sincerely,
-
-The Transfer-Learning-Library Team
+A note on broken dataset links can be found here: [DATASETS.md](DATASETS.md).
 
 ## Introduction
 *TLlib* is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms, or readily apply existing algorithms.