A Public Ground-Truth Dataset for Handwritten Circuit Diagram Images (CGHD)

2023-11-17 (v. 1)

Contact author

Johannes Bayer

German Research Center for Artificial Intelligence

johannes.bayer@dfki.de

+4916092816413

You can cite this dataset as: Johannes Bayer, A Public Ground-Truth Dataset for Handwritten Circuit Diagram Images (CGHD) ,1,ID:CGHD_1,URL:https://tc11.cvc.uab.es/datasets/CGHD_1

Dataset Information

Dataset URL

https://zenodo.org/records/10056817

Keywords

Engeneering Diagram, Schematic, Line Drawing, Object Detection, Semantic Segmentation, Instance Segmentation, Handwritten Text Recognition

Description

This dataset contains images of hand-drawn electrical circuit diagrams as well as accompanying annotation and segmentation ground-truth files. It is intended to train (e.g. ANN) models for extracting electrical graphs from raster graphics.

Content

  • 2.424 Raw Images (Annotated)
    • 24 Drafters (plus Images provided by TU Dresden)
    • 12 Circuits per Drafter
    • 2 Drawings per Circuit
    • 4 Photos per Drawing
    • 201.142 Bounding Box Annotations
    • 26.898 Rotation Annotations
    • 61.595 Text String Annotations
  • 257 Binary Segmentation Maps (Annotated)
    • Strokes vs. Background
    • Accompanying Polygon Annotation Files
    • 19.562 Polygon Annotations
  • 59 Object Classes
  • Scripts for Data Loading, Statistics, Consistency Check and Training Preparation

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