Published November 8, 2024
| Version 14
Dataset
Open
A Public Ground-Truth Dataset for Handwritten Circuit Diagram Images
Description
CGHD
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
- 3.173 Annotated Raw Images
- 30 Drafters
- 12 Circuits per Drafter
- 2 Drawings per Circuit
- 4 Photos per Drawing
- Additional Circuit Images provided by TU Dresden (from Real-World Examinations, Drafter 0)
- Additional Circuit Images provided by RPTU Kaiserslautern-Landau (Drafter -1)
- 245.962 Bounding Box Annotations
- 39.955 Rotation Annotations
- 1.339 Mirror Annotations
- 84.431 Text String Annotations (equals 93.41% completeness)
- 286.467 Text Characters
- 98 Character Types (Upper/Lower Case Latin, Numbers, Special Characters)
- 30 Drafters
- 284 Binary Segmentation Maps
- Strokes vs. Background
- Accompanying Polygon Annotation Files
- 21.186 Polygon Annotations
- 59 Object Classes
- Scripts for Data Loading, Statistics, Consistency Check and Training Preparation
Technical info (English)
Added 2 more drafters and content from RPTU employees. Corrections in all annotations types. New, experimental mirror annotations.
Files
cghd-zenodo-14.zip
Additional details
Related works
- Is described by
- Preprint: https://arxiv.org/abs/2107.10373 (URL)
- Conference paper: 10.1007/978-3-030-86198-8_2 (DOI)
- Preprint: https://arxiv.org/abs/2301.03155 (URL)
- Poster: 10.5281/zenodo.7652836 (DOI)
- Preprint: https://arxiv.org/abs/2402.11093 (URL)
Dates
- Updated
-
2024-11-08Zenodo V14 Update
Software
- Repository URL
- https://gitlab.com/circuitgraph
- Programming language
- Python
- Development Status
- Wip