Update README.md

README.md

@@ -16,7 +16,7 @@
   <a href="#starter-bundle"><b>Starter Bundle</b></a>
   | <a href="#installation"><b>Installation</b></a>
   | <a href="#usage"><b>Usage</b></a>
-  | <a href="https://github.com/wkentaro/labelme/tree/main/examples"><b>Examples</b></a>
+  | <a href="#examples"><b>Examples</b></a>
   | <a href="https://github.com/wkentaro/labelme/discussions"><b>Community</b></a>
   <!-- | <a href="https://www.youtube.com/playlist?list=PLI6LvFw0iflh3o33YYnVIfOpaO0hc5Dzw"><b>Youtube FAQ</b></a> -->
 </div>
@@ -155,12 +155,6 @@ labelme data_annotated/  # Open directory to annotate all images in it
 labelme data_annotated/ --labels labels.txt  # specify label list with a file
 ```
 
-For more advanced usage, please refer to the examples:
-
-* [Semantic Segmentation Example](examples/semantic_segmentation)
-* [Instance Segmentation Example](examples/instance_segmentation)
-* [Video Annotation Example](examples/video_annotation)
-
 ### Command Line Arguments
 - `--output` specifies the location that annotations will be written to. If the location ends with .json, a single annotation will be written to this file. Only one image can be annotated if a location is specified with .json. If the location does not end with .json, the program will assume it is a directory. Annotations will be stored in this directory with a name that corresponds to the image that the annotation was made on.
 - The first time you run labelme, it will create a config file in `~/.labelmerc`. You can edit this file and the changes will be applied the next time that you launch labelme. If you would prefer to use a config file from another location, you can specify this file with the `--config` flag.
@@ -168,7 +162,7 @@ For more advanced usage, please refer to the examples:
 - Flags are assigned to an entire image. [Example](examples/classification)
 - Labels are assigned to a single polygon. [Example](examples/bbox_detection)
 
-## FAQ
+### FAQ
 
 - **How to convert JSON file to numpy array?** See [examples/tutorial](examples/tutorial#convert-to-dataset).
 - **How to load label PNG file?** See [examples/tutorial](examples/tutorial#how-to-load-label-png-file).
@@ -176,7 +170,23 @@ For more advanced usage, please refer to the examples:
 - **How to get annotations for instance segmentation?** See [examples/instance_segmentation](examples/instance_segmentation).
 
 
-## Developing
+## Examples
+
+### Dataset examples
+
+* [Object Detection Dataset](https://wkentaro.gumroad.com/l/labelmedataset-example-object-detection): 20 object categories and 1.7K images
+
+### Annotation examples
+
+A few object categories and images:
+
+* [Image Classification](examples/image_classification)
+* [Bounding Box Detection](examples/bbox_detection)
+* [Semantic Segmentation](examples/semantic_segmentation)
+* [Instance Segmentation](examples/instance_segmentation)
+* [Video Annotation](examples/video_annotation)
+
+## How to develop
 
 ```bash
 git clone https://github.com/wkentaro/labelme.git
@@ -189,7 +199,7 @@ pip install -e .
 ```
 
 
-## How to build standalone executable
+### How to build standalone executable
 
 Below shows how to build the standalone executable on macOS, Linux and Windows.  
 
@@ -207,7 +217,7 @@ dist/labelme --version
 ```
 
 
-## How to contribute
+### How to contribute
 
 Make sure below test passes on your environment.  
 See `.github/workflows/ci.yml` for more detail.