Update more details in Readme.md.

README.md

@@ -1,20 +1,65 @@
 ---
 license: mit
+task_categories:
+- image-classification
 ---
+
 The ImageNet-A dataset contains 7,500 natural adversarial examples.
 
-Source: https://github.com/hendrycks/natural-adv-examples.  
-Also see the ImageNet-C and ImageNet-P datasets at https://github.com/hendrycks/robustness
+- Source: https://github.com/hendrycks/natural-adv-examples.  
+- Also see the ImageNet-C and ImageNet-P datasets at https://github.com/hendrycks/robustness
+
+## Usage
+
+```python
+import os
+import json
+import io
+
+from datasets import load_dataset
+from huggingface_hub import snapshot_download
+from PIL import Image
+
+
+snapshot_download(repo_id="barkermrl/imagenet-a", repo_type="dataset", local_dir="./imagenet-a/")
+imagenet_a = load_dataset("parquet", data_files="./imagenet-a/data/train-*.parquet")['train']
 
+with open("./imagenet-a/dataset_infos.json", "r") as f:
+    infos = json.load(f)
+class_names = infos["barkermrl--imagenet-a"]["features"]["label"]["names"]
+
+imagenet_a = imagenet_a.map(lambda e: {"label_name": class_names[e["label"]]})
+for sample in imagenet_a:
+    image = sample["image"]
+    image_bytes = image["bytes"]
+    image_path = image['path']
+    img = Image.open(io.BytesIO(image_bytes)).convert("RGB")
+    print(img.size, image_path)
+
+    label = sample['label']
+    print(type(label))
+
+    label_name = sample['label_name']
+    print(type(label_name), label_name)
+    break
+```
+
+## Reference
+
+```bibtex
 @article{hendrycks2019nae,  
   title={Natural Adversarial Examples},  
   author={Dan Hendrycks and Kevin Zhao and Steven Basart and Jacob Steinhardt and Dawn Song},  
   journal={arXiv preprint arXiv:1907.07174},  
   year={2019}  
 }
+```
+
+## Classes
 
 There are 200 classes we consider. The WordNet ID and a description of each class is as follows.
 
+```
 n01498041 stingray 
 n01531178 goldfinch 
 n01534433 junco 
@@ -214,4 +259,5 @@ n09835506 baseball player
 n11879895 rapeseed 
 n12057211 yellow lady's slipper 
 n12144580 corn 
-n12267677 acorn 
+n12267677 acorn
+```