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Datasets:
mazafard
/
portugues_ocr_dataset

Tasks:
Image-to-Text
Languages:
Portuguese
English
Size:
1K<n<10K
Tags:
ocr
Portuguese
License:
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metadata
annotations_creators:
  - manual
language:
  - pt
  - en
license: mit
multilinguality: monolingual
pretty_name: Portuguese OCR Dataset
size_categories:
  - 1K<n<10K
source_datasets: []
task_categories:
  - image-to-text
tags:
  - ocr
  - Portuguese

📘 Portuguese OCR Dataset

This dataset contains scanned image-text pairs in European Portuguese, curated manually for Optical Character Recognition (OCR) tasks. It includes literary sentences and historical excerpts.

📦 Dataset Overview

  • Total Samples: 10,000
  • Image Shape: (10000, 100, 1200, 3) — color images with height 100 and width 1200 pixels
  • Text Example:
    "E mais avante o Estreito que se arreia"

📂 Dataset Structure

The dataset is stored in a single HDF5 file (dataset.h5), which includes:

  • images: a NumPy array of grayscale image data (from PNG files)
  • texts: a list of UTF-8 encoded strings, corresponding to each image

Each sample pairs an image and its corresponding transcription.

📊 Dataset Statistics

  • Format: HDF5 (dataset.h5)
  • Total samples: ~10,000
  • Average image size: 224x224 pixels (if preprocessed)
  • Language: European Portuguese
  • Source: literary and historic texts

💾 How to Load

To use this dataset with the Hugging Face Datasets library:

from datasets import load_dataset
import h5py

# Load from Hugging Face
dataset_path = "mazafard/portugues_ocr_dataset"
h5_file = load_dataset(dataset_path, data_files="dataset.h5", split="train")

# Alternatively, open the HDF5 file directly
with h5py.File("dataset.h5", "r") as f:
    images = f["images"][:]        # NumPy array of images
    texts = f["texts"][:]          # List of transcriptions

🧠 Use Cases

  • Fine-tuning OCR models like microsoft/trocr-base-printed
  • Document digitization
  • Research in Portuguese language modeling and handwritten/printed recognition

📜 License

MIT License — free for academic and commercial use with attribution.

📦 How to Inspect dataset.h5

You can extract metadata from the HDF5 file using h5py:

import h5py

with h5py.File("dataset.h5", "r") as f:
    print("Keys:", list(f.keys()))  # ['images', 'texts']
    print("Number of samples:", len(f["texts"]))
    print("Image shape:", f["images"].shape)
    print("Example text:", f["texts"][0])

⚠️ Note

This dataset uses synthetic text-image pairs for printed OCR. Handwritten or scanned documents are not included.