---
license: apache-2.0
language:
- en
- de
tags:
- object-detection
- document-understanding
- invoice
- layout-analysis
- bounding-box
- ocr-prep
task_categories:
- object-detection
size_categories:
- n<1K
pretty_name: Invoice Layout Annotated BBox Dataset
dataset_info:
  features:
  - name: image
    dtype: image
  - name: image_id
    dtype: int64
  - name: document_id
    dtype: int64
  - name: document_filename
    dtype: string
  - name: page_number
    dtype: int64
  - name: width
    dtype: int64
  - name: height
    dtype: int64
  - name: objects
    struct:
    - name: id
      list: int64
    - name: area
      list: float64
    - name: bbox
      list:
        list: float32
        length: 4
    - name: category
      list:
        class_label:
          names:
            '0': invoice_metadata
            '1': vendor_block
            '2': customer_block
            '3': table_block
            '4': line_item
            '5': summary_block
            '6': payment_block
            '7': Column
  splits:
  - name: train
    num_bytes: 40359783
    num_examples: 76
  download_size: 36093604
  dataset_size: 40359783
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---


Manually annotated invoice page images exported from **AnnotateEverything**, with axis-aligned bounding boxes for **8 document-layout regions**. Built for training object detectors (YOLO, DETR, etc.) on invoice macro-structure.

## Dataset summary

| Property | Value |
|----------|-------|
| **Pages** | 76 |
| **Documents** | 1 |
| **Source PDF** | `train_images.pdf` |
| **Total annotations** | 771 |
| **Avg boxes / page** | 10.14 |
| **Image width range** | 425 – 2853 px |
| **Image height range** | 570 – 4096 px |
| **Export date** | 2026-06-22T19:27:38.375Z |
| **Annotation tool** | AnnotateEverything |
| **Project** | Invoices (id=2) |

## Classes

| ID | Name | Description | Color | Count |
|----|------|-------------|-------|-------|
| 0 | `invoice_metadata` | Invoice number, date, header metadata | `#f59e0b` | 83 |
| 1 | `vendor_block` | Seller / vendor address block | `#22c55e` | 73 |
| 2 | `customer_block` | Client / customer address block | `#ef4444` | 74 |
| 3 | `table_block` | Line items table region | `#ec4899` | 76 |
| 4 | `line_item` | Individual line item row | `#8b5cf6` | 257 |
| 5 | `summary_block` | Totals / summary section | `#3b82f6` | 78 |
| 6 | `payment_block` | Payment / IBAN block | `#06b6d4` | 55 |
| 7 | `Column` | Table column header row | `#64748b` | 75 |

## Dataset Viewer schema

The `train` split uses COCO-style `objects` with `[x, y, width, height]` bboxes (top-left origin):

| Column | Type |
|--------|------|
| `image` | Image |
| `image_id`, `document_id`, `page_number`, `width`, `height` | int |
| `document_filename` | string |
| `objects.bbox` | list of `[x, y, w, h]` |
| `objects.category` | ClassLabel (8 layout regions) |
| `objects.area`, `objects.id` | float / int |

## Raw export layout

The original AnnotateEverything export is preserved under `raw_export/`:

```
raw_export/
├── manifest.json
├── annotations.json
└── documents/.../pages/page_NNN/image.png
```

## Sample pages

### Page 1 (8 boxes)

| Original | Annotated |
|----------|-----------|
| ![page 1 original](samples/page_001_original.jpg) | ![page 1 annotated](samples/page_001_annotated.jpg) |
### Page 20 (13 boxes)

| Original | Annotated |
|----------|-----------|
| ![page 20 original](samples/page_020_original.jpg) | ![page 20 annotated](samples/page_020_annotated.jpg) |
### Page 39 (10 boxes)

| Original | Annotated |
|----------|-----------|
| ![page 39 original](samples/page_039_original.jpg) | ![page 39 annotated](samples/page_039_annotated.jpg) |
### Page 58 (4 boxes)

| Original | Annotated |
|----------|-----------|
| ![page 58 original](samples/page_058_original.jpg) | ![page 58 annotated](samples/page_058_annotated.jpg) |
### Page 76 (8 boxes)

| Original | Annotated |
|----------|-----------|
| ![page 76 original](samples/page_076_original.jpg) | ![page 76 annotated](samples/page_076_annotated.jpg) |
### Page 19 (14 boxes)

| Original | Annotated |
|----------|-----------|
| ![page 19 original](samples/page_019_original.jpg) | ![page 19 annotated](samples/page_019_annotated.jpg) |

## Label distribution

| Label | Count |
|-------|-------|
| `line_item` | 257 |
| `invoice_metadata` | 83 |
| `summary_block` | 78 |
| `table_block` | 76 |
| `Column` | 75 |
| `customer_block (Receiver)` | 74 |
| `vendor_block (Sender)` | 73 |
| `payment_block` | 55 |

## Usage

### Load with Hugging Face Datasets (recommended)

```python
from datasets import load_dataset

ds = load_dataset("AvoCahDoe/invoice-annotated-bbox")
example = ds["train"][0]
print(example["objects"])  # COCO-style bboxes + categories
example["image"].show()
```

### Load raw AnnotateEverything export

```python
import json
from huggingface_hub import hf_hub_download

ann_path = hf_hub_download("AvoCahDoe/invoice-annotated-bbox", "raw_export/annotations.json", repo_type="dataset")
with open(ann_path) as f:
    pages = json.load(f)
```

### Convert to YOLO (invoice-extractor)

```bash
python scripts/prepare_annotated_dataset.py
```

## License

Apache 2.0