AvoCahDoe/invoice-layout-yolov8m
Object Detection • Updated • 726
Datasets:
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|---|---|---|---|---|---|---|---|
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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 20 (13 boxes)
| Original | Annotated |
|---|---|
 |
 |
Page 39 (10 boxes)
| Original | Annotated |
|---|---|
 |
 |
Page 58 (4 boxes)
| Original | Annotated |
|---|---|
 |
 |
Page 76 (8 boxes)
| Original | Annotated |
|---|---|
 |
 |
Page 19 (14 boxes)
| Original | Annotated |
|---|---|
 |
 |
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)
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
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)
python scripts/prepare_annotated_dataset.py
License
Apache 2.0
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Models trained or fine-tuned on AvoCahDoe/invoice-annotated-bbox