用HDF5格式替代STEP，让工业级三维模型更易用于大规模学习。
Better STEP, a format and dataset for boundary representation
- 提出HDF5格式替代STEP，支持跨平台读取与集群部署。
- 转换Fusion 360和ABC数据集，四类任务验证数据完整性。
- 开源工具包提供采样、法向、曲率等标准功能，便于集成。
工业中广泛使用的边界表示（B-rep）通常以STEP格式存储，需依赖CAD内核读取，导致在大规模学习流水线中应用受限，尤其因每节点授权成本高而难以部署于计算集群。本文提出一种基于开放、跨平台的HDF5格式的替代方案，并构建了对应的公开数据集，配套开源库支持查询与处理。该Python工具包提供采样、法向量、曲率等标准功能，便于融入现有机器学习流程。为验证有效性，将Fusion 360与ABC数据集转换为新格式，并设计四个标准任务（法向估计、去噪、表面重建、分割）评估数据保真度与原始STEP文件的一致性。
原文摘要 · Abstract (English)
Boundary representation (B-rep) generated from computer-aided design (CAD) is widely used in industry, with several large datasets available. However, the data in these datasets is represented in STEP format, requiring a CAD kernel to read and process it. This dramatically limits their scope and usage in large learning pipelines, as it constrains the possibility of deploying them on computing clusters due to the high cost of per-node licenses. This paper introduces an alternative format based on the open, cross-platform format HDF5 and a corresponding dataset for STEP files, paired with an open-source library to query and process them. Our Python package also provides standard functionalities such as sampling, normals, and curvature to ease integration in existing pipelines. To demonstrate the effectiveness of our format, we converted the Fusion 360 dataset and the ABC dataset. We developed four standard use cases (normal estimation, denoising, surface reconstruction, and segmentation) to assess the integrity of the data and its compliance with the original STEP files.
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