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Two Photon lithography additive manufacturing: Video dataset of parameter sweep of light dosages photo-curable resins and structures

机译:两个光子光刻添加剂制造:光剂量可光固化树脂和结构的参数扫描视频数据集

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摘要

This document describes the collection and organization of a dataset that consists of raw videos and extracted sub-images from video frames of a promising additive manufacturing technique called Two-Photon Lithography (TPL).  Four unprocessed videos were collected, with each video capturing the printing process of different combinations of 3D parts on different photoresists at varying light dosages.  These videos were further trimmed to obtain short clips that are organized by experimental parameters. Additionally, this dataset also contains a python script to reproduce an organized directory of cropped video frames extracted from the trimmed videos. These cropped frames focus on a region of interest around the parts being printed. We envision that the raw videos and cropped frames provided in this dataset will be used to train various computer vision and machine learning algorithms for applications such as object segmentation and localization applications. The cropped video frames were manually labelled by an expert to determine the quality of the printed part and for printing parameter optimization as presented in “Automated Detection of Part Quality during Two-Photon Lithography via Deep Learning” .
机译:本文档描述了数据集的集合和组织,该数据集包括来自所谓的两光子光刻(TPL)的承诺添加剂制造技术的视频帧中提取的子图像。收集了四个未加工的视频,每个视频在不同的光剂量下捕获不同光致抗蚀剂上的3D部件的不同组合的打印过程。这些视频进一步修剪以获得通过实验参数组织的短夹子。此外,该数据集还包含一个Python脚本,用于重现从修剪视频中提取的裁剪视频帧的有组织目录。这些裁剪框架聚焦在打印的部件周围的感兴趣区域。我们设想在此数据集中提供的RAW视频和裁剪帧将用于培训各种计算机视觉和机器学习算法,以获取对象分段和本地化应用程序的应用程序。裁剪视频帧由专家手动标记,以确定印刷部分的质量和打印参数优化,如“通过深度学习在双光子光刻期间的部分质量自动检测”中所示。

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