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| Format: | Preprint |
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2024
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| Online-Zugang: | https://arxiv.org/abs/2407.04180 |
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| _version_ | 1866914024804843520 |
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| author | Jignasu, Anushrut Marshall, Kelly O. Mishra, Ankush Kumar Rillo, Lucas Nerone Ganapathysubramanian, Baskar Balu, Aditya Hegde, Chinmay Krishnamurthy, Adarsh |
| author_facet | Jignasu, Anushrut Marshall, Kelly O. Mishra, Ankush Kumar Rillo, Lucas Nerone Ganapathysubramanian, Baskar Balu, Aditya Hegde, Chinmay Krishnamurthy, Adarsh |
| contents | G-code (Geometric code) or RS-274 is the most widely used computer numerical control (CNC) and 3D printing programming language. G-code provides machine instructions for the movement of the 3D printer, especially for the nozzle, stage, and extrusion of material for extrusion-based additive manufacturing. Currently, there does not exist a large repository of curated CAD models along with their corresponding G-code files for additive manufacturing. To address this issue, we present Slice-100K, a first-of-its-kind dataset of over 100,000 G-code files, along with their tessellated CAD model, LVIS (Large Vocabulary Instance Segmentation) categories, geometric properties, and renderings. We build our dataset from triangulated meshes derived from Objaverse-XL and Thingi10K datasets. We demonstrate the utility of this dataset by finetuning GPT-2 on a subset of the dataset for G-code translation from a legacy G-code format (Sailfish) to a more modern, widely used format (Marlin). Our dataset can be found at https://github.com/idealab-isu/Slice-100K. Slice-100K will be the first step in developing a multimodal foundation model for digital manufacturing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_04180 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing Jignasu, Anushrut Marshall, Kelly O. Mishra, Ankush Kumar Rillo, Lucas Nerone Ganapathysubramanian, Baskar Balu, Aditya Hegde, Chinmay Krishnamurthy, Adarsh Computer Vision and Pattern Recognition G-code (Geometric code) or RS-274 is the most widely used computer numerical control (CNC) and 3D printing programming language. G-code provides machine instructions for the movement of the 3D printer, especially for the nozzle, stage, and extrusion of material for extrusion-based additive manufacturing. Currently, there does not exist a large repository of curated CAD models along with their corresponding G-code files for additive manufacturing. To address this issue, we present Slice-100K, a first-of-its-kind dataset of over 100,000 G-code files, along with their tessellated CAD model, LVIS (Large Vocabulary Instance Segmentation) categories, geometric properties, and renderings. We build our dataset from triangulated meshes derived from Objaverse-XL and Thingi10K datasets. We demonstrate the utility of this dataset by finetuning GPT-2 on a subset of the dataset for G-code translation from a legacy G-code format (Sailfish) to a more modern, widely used format (Marlin). Our dataset can be found at https://github.com/idealab-isu/Slice-100K. Slice-100K will be the first step in developing a multimodal foundation model for digital manufacturing. |
| title | Slice-100K: A Multimodal Dataset for Extrusion-based 3D Printing |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2407.04180 |