update readme

README.md

@@ -27,15 +27,14 @@ task_ids:
 ### Dataset Description
 - **Repository:** [Microsoft unilm](https://github.com/microsoft/unilm/tree/master/kosmos-2)
 - **Paper:** [Kosmos-2](https://arxiv.org/abs/2306.14824)
-- **Point of Contact:** [Unilm team](fuwei@microsoft.com)
 
 ### Dataset Summary
 We introduce GRIT, a large-scale dataset of Grounded Image-Text pairs, which is created based on image-text pairs from [COYO-700M](https://github.com/kakaobrain/coyo-dataset) and LAION-2B. We construct a pipeline to extract and link text spans (i.e., noun phrases, and referring expressions) in the caption to their corresponding image regions. More details can be found in the [paper](https://arxiv.org/abs/2306.14824).
 
 ### Supported Tasks
-During the construction, we exclude the image-caption pair if no bounding boxes are retained. This procedure results in a high-quality image-caption subset of COYO-700M. We will validate it in the future.
+During the construction, we excluded the image-caption pairs if no bounding boxes are retained. This procedure resulted in a high-quality image-caption subset of COYO-700M, which we will validate in the future.
 
-Furthermore, this dataset contains text-span-bounding-box pairs. So it can be employed in many location-aware mono/multimodal tasks, such as phrase grounding, referring expression comprehension, referring expression generation and open-world object detection.
+Furthermore, this dataset contains text-span-bounding-box pairs. Thus, it can be used in many location-aware mono/multimodal tasks, such as phrase grounding, referring expression comprehension, referring expression generation, and open-world object detection.
 
 ### Data Instance
 One instance is
@@ -66,6 +65,27 @@ One instance is
 - `ref_exps`: The corresponding referring expressions. If a noun chunk has no expansion, we just copy it. 
 
 ### Download image
+We recommend to use [img2dataset](https://github.com/rom1504/img2dataset) tool to download the images. 
+1. Download the metadata. You can download it by cloning current repository:
+```bash
+git lfs install
+git clone https://huggingface.co/datasets/zzliang/GRIT
+```
+2. Install [img2dataset](https://github.com/rom1504/img2dataset).
+```bash
+pip install img2dataset
+```
+3. Download images
+You need to replace `/path/to/GRIT_dataset/grit-20m` with the local path to this repository. 
+```bash
+img2dataset --url_list /path/to/GRIT_dataset/grit-20m --input_format "parquet"\
+    --url_col "url" --caption_col "caption" --output_format webdataset \
+    --output_folder /tmp/grit --processes_count 4 --thread_count 64 --image_size 256 \
+    --resize_only_if_bigger=True --resize_mode="keep_ratio" --skip_reencode=True \
+    --save_additional_columns '["id","noun_chunks","ref_exps","clip_similarity_vitb32","clip_similarity_vitl14"]' \
+    --enable_wandb False
+```
+More img2dataset hyper-parameters can be found in [here](https://github.com/rom1504/img2dataset#api).
 
 ### Citation Information
 If you apply this dataset to any project and research, please cite our paper and coyo-700m: