--- license: cc-by-4.0 task_categories: - visual-question-answering language: - en - de tags: - engineering - drawing - CAD pretty_name: Technical drawings for Manufacturability Benchmark size_categories: - n<1K --- # Dataset Card for TechMB ## Dataset Details The Technical drawing for Manufacturability Benchmark (TechMB) gives a domain specific benchmark for the task of manufacturability evaluations based on technical drawings. 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. 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). 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). The IDs of the parts from the f360 segmentation dataset also declare the corresponding technical drawings for better association. - **Curated by:** Leonhard Kunz - **Funded by:** Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer (543073350) - **Language(s) (NLP):** English, German - **License:** CC-BY-4.0 ## Dataset Structure The dataset consists contains the following fields: - **task_id:** ID of the specific question. - **eval_type:** Classifier for the expected answer type (answer matching, multiple choice, or containing keywords). - **drw_id:** ID of the part and the corresponding drawing. - **image:** Bit64 encoded image of the exported technical drawing. - **drw_complexity:** Numeric complexity of the drawing. Calculated with the following formula: $complexity=(faces+dimensionings+\frac{annotation characters}{4.6})*views$ - **question:** The question text. - **answer:** The expected answer corresponding to the answer type. - **label_confidence:** The confidence of the assorted labels in manual labelling (low, medium, high). ## Citation: For more information, refer to our publication (upcomming): ``` ```