README.md

metadata

language:
  - az
license: cc-by-4.0
task_categories:
  - image-to-text
tags:
  - htr
  - handwritten-text-recognition
  - azerbaijani
  - ocr
  - benchmark
pretty_name: Azerbaijani Handwritten OCR Benchmark
configs:
  - config_name: lines
    data_files:
      - split: test
        path: lines/test-*
  - config_name: pages
    data_files:
      - split: test
        path: pages/test-*

Azerbaijani Handwritten OCR Benchmark

A manually annotated benchmark for handwritten text recognition (HTR) on Azerbaijani Latin script. Real-world scanned pages annotated in Label Studio with rotated bounding boxes and exact transcriptions.

Provided in two parallel views:

lines — Line-level recognition

Cropped images of single text lines paired with their transcription. Rotated regions are deskewed (warped to be axis-aligned) so each crop shows the line horizontally.

• Total lines: 442
• Source pages: 29
• Avg lines per page: 15.2

Schema:

Field	Type	Description
image	Image	Cropped (and deskewed if rotated) line image
text	string	Ground truth transcription
page_id	string	Source page identifier
line_id	int	Line index within page
source_image	string	Original scan filename

from datasets import load_dataset
ds = load_dataset("LocalDoc/azerbaijani-htr-benchmark", "lines", split="test")
print(ds[0])

pages — Full-page with structured annotations

Original scanned pages with axis-aligned bounding boxes (computed from the rotated polygons) and transcriptions of all lines.

Schema:

Field	Type	Description
image	Image	Full page scan
page_id	string	Page identifier
source_image	string	Original scan filename
image_width	int	Width of served image (pixels)
image_height	int	Height of served image (pixels)
num_lines	int	Number of annotated lines
lines	list	Per-line annotations
full_text	string	All line texts joined with newlines

from datasets import load_dataset
ds = load_dataset("LocalDoc/azerbaijani-htr-benchmark", "pages", split="test")
sample = ds[0]
print(f"Page {sample['page_id']}: {sample['num_lines']} lines")
# HF stores Sequence(of dict) as dict-of-lists. Iterate by index:
for i in range(sample["num_lines"]):
    line_id = sample["lines"]["line_id"][i]
    bbox = sample["lines"]["bbox"][i]
    text = sample["lines"]["text"][i]
    print(f"  Line {line_id}: bbox={bbox}, text={text}")

Linking between configs

Same page_id and line_id connect entries across both configs.

How it was built

1. Real Azerbaijani handwritten pages were collected
2. Uploaded to Label Studio for annotation
3. Each line was manually bounded with a (possibly rotated) rectangle and transcribed
4. For lines config: rotated regions are deskewed via affine transform so crops are horizontal
5. For pages config: rotated polygons are converted to their axis-aligned bounding boxes
6. Page images optionally downscaled to max 2200px for file size

Notes

• Transcriptions are literal — handwriting errors preserved as written
• Rotated bboxes are handled correctly via perspective transform
• lines crops have 4px padding around text
• pages bbox coords are in pixels of the served image (after resize)

License

CC BY 4.0