Update README.md

README.md

@@ -99,6 +99,20 @@ next(iter(dataset["train"])).keys()
 ```
 `image` will be a byte string containing the image contents. `answers` is a list of possible answers, aligned with the expected inputs to the [ANLS metric](https://arxiv.org/abs/1905.13648).
 
+Calling 
+
+```python
+from PIL import Image
+from io import BytesIO
+image = Image.open(BytesIO(docvqa_dataset["train"][0]["image"]['bytes']))
+```
+will yield the image
+
+<center>
+    <img src="https://huggingface.co/datasets/pixparse/docvqa-single-page-questions/resolve/main/doc_images_docvqa/docvqa_example.png" alt="An example of document available in docVQA" width="600" height="300">
+    <p><em>A document overlapping with tobacco on which questions are asked such as 'When is the contract effective date?' with the answer ['7 - 1 - 99']</em></p>
+</center>
+
 The loader can then be iterated on normally and yields questions. Many questions rely on the same image, so there is some amount of data duplication.
 
 ### Data Splits