Add legal notice

opengeos · Jun 29, 2023 · 295dc8e · 295dc8e
1 parent 15aa9e8
commit 295dc8e
Show file tree

Hide file tree

Showing 3 changed files with 9 additions and 1 deletion.
diff --git a/README.md b/README.md
@@ -87,6 +87,10 @@ Video tutorials are available on my [YouTube Channel](https://youtube.com/@giswq
 
 The Segment Anything Model is computationally intensive, and a powerful GPU is recommended to process large datasets. It is recommended to have a GPU with at least 8 GB of GPU memory. You can utilize the free GPU resources provided by Google Colab. Alternatively, you can apply for [AWS Cloud Credit for Research](https://aws.amazon.com/government-education/research-and-technical-computing/cloud-credit-for-research), which offers cloud credits to support academic research. If you are in the Greater China region, apply for the AWS Cloud Credit [here](https://aws.amazon.com/cn/events/educate_cloud/research-credits).
 
+## Legal Notice
+
+This repository and its content are provided for educational purposes only. By using the information and code provided, users acknowledge that they are using the APIs and models at their own risk and agree to comply with any applicable laws and regulations. Users who intend to download a large number of image tiles from any basemap are advised to contact the basemap provider to obtain permission before doing so. Unauthorized use of the basemap or any of its components may be a violation of copyright laws or other applicable laws and regulations.
+
 ## Acknowledgements
 
 This project is supported by Amazon Web Services ([AWS](https://aws.amazon.com/)). In addition, this package was made possible by the following open source projects. Credit goes to the developers of these projects.

diff --git a/docs/index.md b/docs/index.md
@@ -87,6 +87,10 @@ Video tutorials are available on my [YouTube Channel](https://youtube.com/@giswq
 
 The Segment Anything Model is computationally intensive, and a powerful GPU is recommended to process large datasets. It is recommended to have a GPU with at least 8 GB of GPU memory. You can utilize the free GPU resources provided by Google Colab. Alternatively, you can apply for [AWS Cloud Credit for Research](https://aws.amazon.com/government-education/research-and-technical-computing/cloud-credit-for-research), which offers cloud credits to support academic research. If you are in the Greater China region, apply for the AWS Cloud Credit [here](https://aws.amazon.com/cn/events/educate_cloud/research-credits).
 
+## Legal Notice
+
+This repository and its content are provided for educational purposes only. By using the information and code provided, users acknowledge that they are using the APIs and models at their own risk and agree to comply with any applicable laws and regulations. Users who intend to download a large number of image tiles from any basemap are advised to contact the basemap provider to obtain permission before doing so. Unauthorized use of the basemap or any of its components may be a violation of copyright laws or other applicable laws and regulations.
+
 ## Acknowledgements
 
 This project is supported by Amazon Web Services ([AWS](https://aws.amazon.com/)). In addition, this package was made possible by the following open source projects. Credit goes to the developers of these projects.

diff --git a/samgeo/common.py b/samgeo/common.py
@@ -1614,7 +1614,7 @@ def sam_map_gui(sam, basemap="SATELLITE", repeat_mode=True, out_dir=None, **kwar
 
     # Skip the image layer if localtileserver is not available
     try:
-        m.add_raster(sam.image, layer_name="Image")
+        m.add_raster(sam.source, layer_name="Image")
     except:
         pass