metadata

dataset_info:
  features:
    - name: image_id
      dtype: int64
    - name: image
      dtype: image
    - name: width
      dtype: int32
    - name: height
      dtype: int32
    - name: objects
      struct:
        - name: bbox
          sequence:
            sequence: float32
            length: 4
        - name: category_id
          sequence: int64
        - name: category
          sequence: string
        - name: area
          sequence: float32
        - name: iscrowd
          sequence: int64
  splits:
    - name: train
      num_bytes: 97076536.768
      num_examples: 3456
    - name: valid
      num_bytes: 14929397
      num_examples: 470
    - name: test
      num_bytes: 9853454
      num_examples: 311
  download_size: 121355015
  dataset_size: 121859387.768
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: valid
        path: data/valid-*
      - split: test
        path: data/test-*

Experimento-3 - Industrial Machinery Text Detection Dataset

Dataset Description

This dataset contains 4,237 images of industrial machinery nameplates with detailed text field annotations for OCR and information extraction tasks. The dataset focuses on extracting key information from equipment nameplates including manufacturer, model, serial numbers, and dates.

Dataset Summary

Task: Industrial text detection and OCR
Domain: Industrial machinery and equipment
Images: 4,237 total images
Annotations: Bounding boxes for text fields with 8 categories
Source: Roboflow Universe - Experimento-3

Dataset Structure

Splits

Split	Images
Train	3,456
Valid	470
Test	311

ID	Category	Description
0	tipos-pl	Equipment type (unused in annotations)
1	FABRICANTE	Manufacturer name
2	FECHA	Date information
3	MODEL	Model designation
4	MODELO	Model designation (Spanish)
5	NUMERO DE SERIE	Serial number (full text)
6	SN	Serial number (abbreviated)
7	YEAR	Year information

Data Fields

Each example contains:

image_id: Unique image identifier
image: PIL Image of the machinery nameplate
width: Image width in pixels
height: Image height in pixels
objects: Dictionary containing:
- bbox: List of bounding boxes in [x, y, width, height] format (COCO format)
- category_id: List of category IDs (0-7)
- category: List of category names
- area: List of bounding box areas
- iscrowd: List of crowd flags (typically 0)

Use Cases

This dataset is ideal for:

Industrial OCR Systems: Extracting text from machinery nameplates
Equipment Inventory Management: Automated data collection from equipment
Maintenance Planning: Identifying equipment details for service schedules
Asset Tracking: Digital cataloging of industrial equipment
Computer Vision Research: Multi-language text detection in industrial settings

Data Collection

The images were collected from various industrial machinery and equipment, focusing on nameplates and identification tags. The dataset includes equipment from multiple manufacturers and spans different time periods, providing diverse examples for robust model training.

Licensing & Attribution

Please refer to the original Roboflow dataset for licensing information. When using this dataset, please cite:

@misc{
    experimento-3_dataset,
    title = { Experimento-3 Dataset },
    type = { Open Source Dataset },
    author = { Marcos Feria },
    howpublished = { \url{ https://universe.roboflow.com/marcos-feria/experimento-3 } },
    url = { https://universe.roboflow.com/marcos-feria/experimento-3 },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    note = { visited on 2025-01-25 },
}

Loading the Dataset

from datasets import load_dataset

# Load the full dataset
dataset = load_dataset("kahua-ml/experimento3-industrial-text-detection")

# Load specific split
train_dataset = load_dataset("kahua-ml/experimento3-industrial-text-detection", split="train")

# Example usage
example = dataset["train"][0]
image = example["image"]
bboxes = example["objects"]["bbox"]
categories = example["objects"]["category"]

Dataset Statistics

Average annotations per image: ~6.2 text fields
Most common categories: FABRICANTE, SN, NUMERO DE SERIE
Image resolution: Primarily 544x416 pixels
Languages: Mixed Spanish/English text fields

Applications

This dataset has been successfully used for:

Training YOLO models for industrial text detection
Fine-tuning vision transformers for equipment OCR
Developing maintenance automation systems
Creating inventory management solutions

Contact

For questions about this dataset, please refer to the original Roboflow project or create an issue in this repository.

Datasets:

kahua-ml
/

experimento3-industrial-text-detection