data

README.md

@@ -19,6 +19,9 @@
     - [LLaVA-Grounding Weights](#llava-grounding-weights)
     - [Demo](#demo)
     - [Training data](#training-data)
+      - [Flickr30k](#flickr30k)
+      - [COCO](#coco)
+      - [LLaVA](#llava)
     - [Training](#training)
     - [Citation](#citation)
 
@@ -82,9 +85,13 @@ data
 │          ├── llava_instruct_150k.json
 │          ├── llava_instruct_150k_visual_prompt.json
 
-
 ```
-
+#### Flickr30k
+Please refer to [MDETR's pre-processed flickr30k data](https://github.com/ashkamath/mdetr/blob/main/.github/flickr.md).
+#### COCO
+Please download coco train2014 and train2017 images and panoptic segmentation and semantic segmentation data. Other annoations can be downloaded [here]().
+#### LLaVA
+The processed annotations can be downloaded [here]().
 ### Training
 Stage 1
 ```shell
@@ -108,4 +115,11 @@ If you find LLaVA-Grounding useful for your research and applications, please ci
       year={2023},
       booktitle={arXiv}
 }
+
+@misc{liu2023llava,
+      title={Visual Instruction Tuning}, 
+      author={Liu, Haotian and Li, Chunyuan and Wu, Qingyang and Lee, Yong Jae},
+      publisher={arXiv:2304.08485},
+      year={2023}
+}
 ```