Create README.md

README.md

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+---
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: question_id
+    dtype: int64
+  - name: question
+    dtype: string
+  - name: answers
+    sequence: string
+  - name: data_split
+    dtype: string
+  - name: ocr_results
+    struct:
+    - name: page
+      dtype: int64
+    - name: clockwise_orientation
+      dtype: float64
+    - name: width
+      dtype: int64
+    - name: height
+      dtype: int64
+    - name: unit
+      dtype: string
+    - name: lines
+      list:
+      - name: bounding_box
+        sequence: int64
+      - name: text
+        dtype: string
+      - name: words
+        list:
+        - name: bounding_box
+          sequence: int64
+        - name: text
+          dtype: string
+        - name: confidence
+          dtype: string
+  - name: other_metadata
+    struct:
+    - name: ucsf_document_id
+      dtype: string
+    - name: ucsf_document_page_no
+      dtype: string
+    - name: doc_id
+      dtype: int64
+    - name: image
+      dtype: string
+  splits:
+  - name: train
+    num_examples: 39463
+  - name: validation
+    num_examples: 5349
+  - name: test
+    num_examples: 5188
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
+  - split: test
+    path: data/test-*
+license: mit
+task_categories:
+- question-answering
+language:
+- en
+pretty_name: d
+size_categories:
+- 10K<n<100K
+---
+
+# Dataset Card for DocVQA Dataset
+
+## Dataset Description
+
+- **Point of Contact from curators:** [Minesh Mathew](mailto:[email protected]), [Dimosthenis Karatzas]([email protected]), [C. V. Jawahar]([email protected])
+- **Point of Contact Hugging Face:** [Pablo Montalvo](mailto:[email protected])
+
+### Dataset Summary
+
+DocVQA dataset is a document dataset introduced in Mathew et al. (2021) consisting of 50,000 questions defined on 12,000+ document images. 
+
+### Usage
+
+This dataset can be used with current releases of Hugging Face `datasets` library. 
+Here is an example using a custom collator to bundle batches in a trainable way on the `train` split
+
+```python
+
+from datasets import load_dataset
+
+
+
+docvqa_dataset = load_dataset("pixparse/docvqa-single-page", split="train"
+)
+
+collator_class = Collator()
+loader = DataLoader(docvqa_dataset, batch_size=8, collate_fn=collator_class.collate_fn)
+```
+
+The loader can then be iterated on normally and yields image + question and answer samples. 
+
+### Data Splits
+
+
+#### Train
+* 10194 images, 39463 questions and answers.
+
+### Validation
+
+* 1286 images, 5349 questions and answers.
+
+### Test
+
+* 1,287 images,  5,188 questions.
+  
+## Additional Information
+
+### Dataset Curators
+
+Pablo Montalvo, Ross Wightman
+
+### Licensing Information
+
+MIT
+
+### Citation Information
+
+Mathew, Minesh, Dimosthenis Karatzas, and C. V. Jawahar. "Docvqa: A dataset for vqa on document images." Proceedings of the IEEE/CVF winter conference on applications of computer vision. 20