%0 Computer Program
%A Bayer, Johannes
%D 2024
%T A Public Ground-Truth Dataset for Handwritten Circuit Diagram Images
%U 
%R 10.4121/ad04db6b-cf81-438d-9506-80ba8184bb10.v1
%K Schematic
%K Circuit Diagram
%K CircuitGraph
%K CGHD
%K Object Recognition
%K Semantic Segmentation
%K Handwriting Recognition
%X <p><strong>CGHD</strong></p><p>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.</p><p><br></p><p><strong>Content</strong></p><ul><li><strong>2.549</strong> Raw Images (Annotated)</li><li class="ql-indent-1">25 Drafters (plus Images provided by TU Dresden)</li><li class="ql-indent-1">12 Circuits per Drafter</li><li class="ql-indent-1">2 Drawings per Circuit</li><li class="ql-indent-1">4 Photos per Drawing</li><li class="ql-indent-1"><strong>212.280 </strong>Bounding Box Annotations</li><li class="ql-indent-1"><strong>29.790</strong> Rotation Annotations</li><li class="ql-indent-1"><strong>71.307</strong> Text String Annotations</li><li><strong>264</strong> Binary Segmentation Maps (Annotated)</li><li class="ql-indent-1">Strokes vs. Background</li><li class="ql-indent-1">Accompanying Polygon Annotation Files</li><li class="ql-indent-1"><strong>20.060</strong>&nbsp;Polygon Annotations</li><li><strong>59 </strong>Object Classes</li><li><strong>Scripts</strong> for Data Loading, Statistics, Consistency Check and Training Preparation</li></ul>
%I German Research Center for Artificial Intelligence