Update README.md

README.md

@@ -26,21 +26,38 @@ The evaluation set is divided into 6 different categories:
 ```python
 from huggingface_hub import snapshot_download
 folder = snapshot_download(
-"Shilin-LU/W-Bench",
-repo_type="dataset",
-local_dir="./W-Bench/",
-allow_patterns="DET_INVERSION_1K/image/*")
+  "Shilin-LU/W-Bench",
+  repo_type="dataset",
+  local_dir="./W-Bench/",
+  allow_patterns="DET_INVERSION_1K/image/*" # to download a specific branch
+)
 ```
 
 For faster downloads, make sure to install `pip install huggingface_hub[hf_transfer]` and set the environment variable `HF_HUB_ENABLE_HF_TRANSFER=1`.
 
 ## Using `datasets`
 
+### 1. With Stream
 ```python
 from datasets import load_dataset
-wbench = load_dataset("Shilin-LU/W-Bench", streaming=True)
+dataset = load_dataset("Shilin-LU/W-Bench", split="train", streaming=True)
+next(iter(dataset))['image'].save('output_stream.png')
+```
+
+### 2. Without Stream
+```python
+from datasets import load_dataset
+dataset = load_dataset("Shilin-LU/W-Bench", split="train")
+dataset[1]['image'].save('output.png')
 ```
 
 # Citation Information
 Paper on [arXiv](https://arxiv.org/abs/2410.18775)
-
+```
+@article{lu2024robust,
+  title={Robust watermarking using generative priors against image editing: From benchmarking to advances},
+  author={Lu, Shilin and Zhou, Zihan and Lu, Jiayou and Zhu, Yuanzhi and Kong, Adams Wai-Kin},
+  journal={arXiv preprint arXiv:2410.18775},
+  year={2024}
+}
+```