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layoutlmv3-invoice-dataset

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LayoutLMv3 Invoice Dataset

This dataset is processed and ready for training LayoutLMv3 models for invoice information extraction.

Dataset Description

This dataset contains invoice documents with OCR-extracted text, bounding boxes, and entity labels for training document understanding models.

Dataset Structure

  • train: Training split
  • validation: Validation split (if available)
  • test: Test split (if available)

Features

  • input_ids: Tokenized text input
  • attention_mask: Attention mask for the input
  • bbox: Bounding box coordinates for each token
  • labels: BIO-tagged entity labels
  • pixel_values: Image tensors (if available)

Labels

The dataset includes 45 entity types:

  • O
  • B-INVOICE_NO
  • I-INVOICE_NO
  • B-INVOICE_DATE
  • I-INVOICE_DATE
  • B-SELLER
  • I-SELLER
  • B-CLIENT
  • I-CLIENT
  • B-SELLER_TAX_ID
  • I-SELLER_TAX_ID
  • B-CLIENT_TAX_ID
  • I-CLIENT_TAX_ID
  • B-IBAN
  • I-IBAN
  • B-ITEM_DESC
  • I-ITEM_DESC
  • B-ITEM_QTY
  • I-ITEM_QTY
  • B-ITEM_NET_PRICE
  • I-ITEM_NET_PRICE
  • B-ITEM_NET_WORTH
  • I-ITEM_NET_WORTH
  • B-ITEM_VAT
  • I-ITEM_VAT
  • B-ITEM_GROSS_WORTH
  • I-ITEM_GROSS_WORTH
  • B-TOTAL_NET_WORTH
  • I-TOTAL_NET_WORTH
  • B-TOTAL_VAT
  • I-TOTAL_VAT
  • B-TOTAL_GROSS_WORTH
  • I-TOTAL_GROSS_WORTH
  • B-DUE_DATE
  • I-DUE_DATE
  • B-PAYMENT_TERMS
  • I-PAYMENT_TERMS
  • B-CURRENCY
  • I-CURRENCY
  • B-SUBTOTAL
  • I-SUBTOTAL
  • B-DISCOUNT
  • I-DISCOUNT
  • B-SHIPPING
  • I-SHIPPING

Usage 

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("your-username/layoutlmv3-invoice-dataset")

# Load label information
import json
with open("label_info.json", "r") as f:
    label_info = json.load(f)

id2label = label_info["id2label"]
label2id = label_info["label2id"]

Training

This dataset is compatible with HuggingFace Transformers and can be used directly with LayoutLMv3 models.

Citation

If you use this dataset, please cite the original LayoutLMv3 paper:

@misc{huang2022layoutlmv3,
    title={LayoutLMv3: A Unified Transformer for Document AI},
    author={Yupan Huang and Tengchao Lv and Lei Cui and Yutong Lu and Furu Wei},
    year={2022},
    eprint={2204.08387},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}
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Size of downloaded dataset files:
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Size of the auto-converted Parquet files:
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Paper for Kwash67/layoutlmv3-invoice-dataset