Update README.md

README.md

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 ### Dataset Description
 The CompreCap benchmark is characterized by human-annotated scene graph and focuses on the evaluation of comprehensive image captioning.
 It provides new semantic segmentation annotations for common objects in images, with an average mask coverage of 95.83%.
-Beyond the careful annotation of objects, CompreCap also includes high-quality descriptions of the attributes bound to the objects, as well as directional relational descriptions between the objects, composing a complete and directed scene graph structure.
-Based on the CompreCap benchmark, researchers can comprehensively accessing the quality of image captions generated by large vision-language models.
+Beyond the careful annotation of objects, CompreCap also includes high-quality descriptions of the attributes bound to the objects, as well as directional relation descriptions between the objects, composing a complete and directed scene graph structure:
+<div align="center">
+<p>
+    <img src="graph_anno.png" alt="CompreCap" width="500" height="auto">
+</p>
+</div>
+
+The annotations of segmentation masks, category names, the descriptions of attributes and relationships are saved in [./anno.json](https://huggingface.co/datasets/FanLu31/CompreCap/blob/main/anno.json). Based on the CompreCap benchmark, researchers can comprehensively accessing the quality of image captions generated by large vision-language models.
 
 ### Licensing Information
 We distribute the image under a standard Creative Common CC-BY-4.0 license. The individual images are under their own copyrights.