OrigamiSet1.0

OrigamiSet1.0是由加州大学伯克利分校和国际计算机科学研究所创建的两个新数据集，用于折纸分类和难度估计。该数据集包含超过15,000张图像，分为两部分：一部分用于折纸图像分类，另一部分用于折纸难度估计。数据集的创建过程涉及从多媒体共享和其他数据库中筛选图像，并通过手动和自动方法进行清洗和分类。OrigamiSet1.0的应用领域包括机器学习和计算机视觉，旨在解决折纸图像的自动分类和难度评估问题。

OrigamiSet1.0 is a pair of novel datasets developed by the University of California, Berkeley and the International Computer Science Institute, tailored for origami classification and difficulty estimation. The dataset collection comprises over 15,000 images, divided into two subsets: one dedicated to origami image classification, and the other to origami difficulty estimation. The construction process of these datasets entails screening images from multimedia sharing platforms and other databases, followed by cleaning and categorization via both manual and automated approaches. OrigamiSet1.0 targets the fields of machine learning and computer vision, with the objective of resolving the challenges of automatic classification and difficulty assessment for origami images.

搜集汇总

背景与挑战

背景概述

OrigamiSet1.0是一个由Berkeley多媒体研究团队创建的公共数据集，专门用于折纸图像的分类和难度估计任务。该数据集包含两个主要部分：折纸分类数据和难度评估数据，适用于机器学习和计算机视觉领域的研究与应用。