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--- |
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license: cc-by-4.0 |
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task_categories: |
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- visual-question-answering |
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language: |
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- en |
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- de |
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tags: |
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- engineering |
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- drawing |
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- CAD |
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pretty_name: Technical drawings for Manufacturability Benchmark |
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size_categories: |
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- n<1K |
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configs: |
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- config_name: default |
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data_files: |
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- split: test |
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path: "techmb.tsv" |
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--- |
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# Dataset Card for TechMB |
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## Dataset Details |
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The Technical drawing for Manufacturability Benchmark (TechMB) gives a domain specific benchmark for the task of manufacturability evaluations based on technical drawings. |
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This task is described as a Visual Question Answering (VQA) task targeted at Vision Language Models (VLM) consisting of 947 question-answer pairs on 180 distinct techical drawings. |
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The objects, the technical drawings are developed from, represent a selection of parts of the [Fusion 360 Gallery Segmentation Dataset](https://github.com/AutodeskAILab/Fusion360GalleryDataset/tree/master). |
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Please refer to [their publication](https://doi.org/10.48550/arXiv.2104.00706) for further information. Their licence statement can be found [here](https://github.com/AutodeskAILab/Fusion360GalleryDataset/blob/master/LICENSE.md). |
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The IDs of the parts from the f360 segmentation dataset also declare the corresponding technical drawings for better association. |
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- **Curated by:** Leonhard Kunz |
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- **Funded by:** Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer (543073350) |
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- **Language(s) (NLP):** English, German |
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- **License:** CC-BY-4.0 |
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## Dataset Structure |
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The dataset consists contains the following fields: |
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- **task_id:** ID of the specific question. |
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- **eval_type:** Classifier for the expected answer type (answer matching or multiple choice). |
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- **drw_id:** ID of the part and the corresponding drawing. |
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- **image:** Bit64 encoded image of the exported technical drawing. |
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- **drw_complexity:** Numeric complexity of the drawing. Calculated with the following formula: $complexity=(faces+dimensionings+\frac{annotation characters}{4.6})*views$ |
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- **question:** The question text. |
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- **answer:** The expected answer corresponding to the answer type. |
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- **label_confidence:** The confidence of the assorted labels in manual labelling (low, medium, high). |
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## Citation: |
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Please refer to our dataset using the following DOI: [doi:10.57967/hf/6214](https://doi.org/10.57967/hf/6214) |
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For more information, refer to our publication: |
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``` |
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@inproceedings{kunz2025techmb, |
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title={TechMB: Exploring the Potential of Vision Language Models for Interpreting Technical Drawings}, |
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author={Kunz, Leonhard and Klostermeier, Mario and Thanabalan, Kokulan and Legler, Tatjana and Ruskowski, Martin and others}, |
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booktitle={DS 140: Proceedings of the 36th Symposium Design for X (DFX2025)}, |
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pages={1--10}, |
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year={2025}, |
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doi={https://doi.org/10.35199/dfx2025.19} |
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} |
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``` |
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