[Docs] Add description-tagging examples

examples/description/captioning/README.md

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+# Coming soon...

examples/description/tagging/README.md

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+# Tagging Annotation Example
+
+Tagging annotation involves the task of recognizing and assigning labels to the elements within an image or shape.
+
+## Tagging Model
+
+X-AnyLabeling offers a range of tagging models for annotation, including [RAM](../../../anylabeling/configs/auto_labeling/ram_swin_large_14m.yaml) and [RAM++](../../../anylabeling/configs/auto_labeling/ram_plus_swin_large_14m.yaml). These models can be utilized for object tagging at the image-level or shape-level, and they can even be integrated with other models to create more intriguing pipelines like [GroundingSAM](../../../anylabeling/configs/auto_labeling/groundingdino_swinb_attn_fuse_sam_hq_vit_l_quant.yaml).
+
+<img src=".data/ram_grounded_sam.jpg" width="100%" />
+
+Here:
+
+- **[RAM](https://arxiv.org/abs/2306.03514)** is a strong image tagging model, which can recognize any common category with high accuracy.
+- **[RAM++](https://arxiv.org/abs/2310.15200)** is the next generation of RAM, which can recognize any category with high accuracy, including both predefined common categories and diverse open-set categories.
+
+## Image-level Tagging
+
+<img src=".data/annotated-image-level-tagging-data.png" width="100%" />
+
+## Shape-level Tagging
+
+<img src=".data/annotated-shape-level-tagging-data.png" width="100%" />
+
+For detailed output examples, refer to [this folder](./sources/).