| --- |
| license: cc-by-nc-4.0 |
| language: |
| - bn |
| - en |
| pretty_name: BaFCo |
| size_categories: |
| - n<1K |
| task_categories: |
| - object-detection |
| - image-to-text |
| tags: |
| - document-understanding |
| - document-layout-analysis |
| - key-information-extraction |
| - forms |
| - bengali |
| configs: |
| - config_name: kie |
| data_files: |
| - split: all |
| path: bafco_kie/all_annotations.json |
| - split: en |
| path: bafco_kie/en_annotations.json |
| - split: bn |
| path: bafco_kie/bn_annotations.json |
| - config_name: dla |
| data_files: |
| - split: all |
| path: bafco_dla/all_annotations.json |
| --- |
| |
| # BaFCo: A Document Understanding Benchmark for Complex Bangla Form Comprehension (ECCV 2026) |
|
|
| Real Bangladeshi government forms with manual annotations for two tasks: Document Layout |
| Analysis (DLA) and Key Information Extraction (KIE). |
|
|
| > **This is the dataset and its schema.** The full benchmark pipeline (inference, |
| > evaluation, and post-processing) lives in the code repository: |
| > **[github.com/mausulazad/BaFCo](https://github.com/mausulazad/BaFCo)**. |
| > Paper: [arXiv:2607.05614](https://arxiv.org/abs/2607.05614). |
|
|
| BaFCo curates **200 complex multi-page government forms** across 316 pages and 15 domains. |
| It provides **16,382 layout entities** and **8,771 inter-field relationships** under a |
| fine-grained 26-entity schema (with a separate 5-type coarse set) for DLA, and **1,926 |
| key-value pairs** across 156 forms for KIE. The forms come from sectors such as agriculture, |
| education, banking, and land management. |
|
|
| ## Subsets |
|
|
| - **`bafco_dla/`**: Document Layout Analysis. Layout bounding boxes, inter-box relations, |
| and form-level labels. Images are partitioned by domain. |
| - **`bafco_kie/`**: Key Information Extraction. Key-value pairs. Forms are split by language |
| (English and Bangla). |
|
|
| Each subset is self-contained: annotations in `all_annotations.json`, images under the |
| subset folder, and a `README.md` documenting the schema. Image references (`local_images`) |
| are relative and resolve after download. |
|
|
| ## Load |
|
|
| Download the dataset, then read a subset's annotations. Each record is one form; image |
| paths live in `local_images` as repo-relative strings. |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| import os, json |
| |
| root = snapshot_download("Mausul/bafco", repo_type="dataset") |
| |
| forms = json.load(open(os.path.join(root, "bafco_dla", "all_annotations.json"), encoding="utf-8")) |
| |
| # Resolve the first page of the first form to an OS-native file path. |
| rel = forms[0]["local_images"][0] # e.g. "images/<domain>/form_<id>/<page>.jpg" |
| page_path = os.path.join(root, "bafco_dla", *rel.split("/")) |
| ``` |
|
|
| The KIE subset loads the same way from `bafco_kie/all_annotations.json` (or the `en_` / |
| `bn_` language splits). Each subset's `README.md` documents the full annotation schema. |
|
|
| ## Running the benchmark |
|
|
| Inference, evaluation, and post-processing are in the code repository, which reads these |
| files through a `release_loader.py` adapter. See |
| [github.com/mausulazad/BaFCo](https://github.com/mausulazad/BaFCo) to reproduce the results. |
|
|
| ## License |
|
|
| Code: MIT, Dataset: CC-BY-NC-4.0. |
