| --- |
| license: agpl-3.0 |
| base_model: Ultralytics/YOLO26 |
| pipeline_tag: object-detection |
| tags: |
| - yolo |
| - oriented-bounding-box |
| - obb |
| - circuit-schematics |
| - electronic-design-automation |
| - ultralytics |
| datasets: |
| - johannesbayer/cghd1152 |
| library_name: ultralytics |
| --- |
| |
| # Circuit Component Detector (YOLO26M-OBB, 16 classes) |
|
|
| Oriented-bounding-box detector for hand-drawn electronic circuit components. It is |
| Stage 1 of the pipeline in *"From Hand-Drawn Schematics to SPICE Netlists"* — it |
| localizes and orients components so a downstream occlusion + graph-join stage can |
| recover electrical connectivity. |
|
|
| - **Architecture:** YOLO26M-OBB (Ultralytics), fine-tuned. |
| - **Task:** oriented bounding-box detection. |
| - **Classes:** 16, merged down from CGHD-1152's 61 (variants the netlist does not |
| distinguish are collapsed; 30 rare device types fold into a single `other` class). |
| - **Reported performance:** mAP@0.5 = 89.0% on 468 held-out scans. |
|
|
| ## Intended use |
|
|
| Detecting and orienting components in scanned/photographed hand-drawn schematics as the |
| first stage of schematic-to-netlist digitization. The model recovers component **location, |
| orientation, and coarse class** — not device values. It is trained on a single hand-drawn |
| corpus; generalization to printed schematics or other drawing styles is unvalidated. |
|
|
| ## Training data & attribution |
|
|
| Trained on **CGHD-1152**, *A Public Ground-Truth Dataset for Handwritten Circuit Diagram |
| Images* by Felix Thoma, Johannes Bayer, Yakun Li, and Andreas Dengel (DFKI), licensed |
| **CC BY 4.0** and archived at Zenodo: <https://doi.org/10.5281/zenodo.6385814>. |
|
|
| ## License |
|
|
| The base weights are Ultralytics **YOLO26**, released under **AGPL-3.0**. This fine-tuned |
| derivative is therefore distributed under **AGPL-3.0**. If you need a non-AGPL license for |
| the weights, obtain an Ultralytics Enterprise License. (The surrounding pipeline *code* is |
| MIT and the CGHD-derived annotations are CC BY 4.0 — see the repository — but those licenses |
| do not extend to these weights.) |
|
|
| ## Links |
|
|
| - **Code:** <https://github.com/boscochanam/circuit-digitization> |
| - **Archived release (Zenodo):** <https://doi.org/10.5281/zenodo.21274158> (all versions) · |
| <https://doi.org/10.5281/zenodo.21274159> (v1.0.1) |
|
|
| ## Citation |
|
|
| If you use this model, please cite the paper and the software archive: |
|
|
| ```bibtex |
| @article{chanam2026circuitdigitization, |
| title = {From Hand-Drawn Schematics to SPICE Netlists: A Deterministic |
| Pipeline with Endpoint-Graph Wire Joining and a Human-Verified |
| Connectivity Benchmark}, |
| author = {Chanam, Bosco and Dcosta, Chris and Talupuri, Pranavesh Kumar and |
| Chiwhane, Shwetambari and Singh, Ashay Kumar and Das, Arghadeep}, |
| journal = {IEEE Access}, |
| year = {2026}, |
| note = {Under review} |
| } |
| |
| @software{chanam2026circuitdigitization_sw, |
| title = {Circuit Digitization: a deterministic hand-drawn-schematic-to-SPICE |
| pipeline with an endpoint-graph wire join and a human-verified |
| connectivity benchmark}, |
| author = {Chanam, Bosco and Dcosta, Chris and Talupuri, Pranavesh Kumar and |
| Chiwhane, Shwetambari and Singh, Ashay Kumar and Das, Arghadeep}, |
| year = {2026}, |
| version = {1.0.1}, |
| doi = {10.5281/zenodo.21274158}, |
| url = {https://github.com/boscochanam/circuit-digitization} |
| } |
| ``` |
|
|
| And the training dataset: |
|
|
| ```bibtex |
| @inproceedings{thoma2021cghd, |
| title = {A Public Ground-Truth Dataset for Handwritten Circuit Diagram Images}, |
| author = {Thoma, Felix and Bayer, Johannes and Li, Yakun and Dengel, Andreas}, |
| booktitle = {Proc. Int. Conf. Document Analysis and Recognition (ICDAR)}, |
| pages = {20--27}, |
| year = {2021}, |
| doi = {10.1007/978-3-030-86198-8_2} |
| } |
| ``` |
