FD_Dataset.7z

The dataset comprises 720 images each depicting four distinct defect types in colored fabrics: Oil, Hole, Cutting, and Crack, totaling approximately 180 images per type. This dataset holds significant academic value, particularly within the realm of Computer Vision, serving as a crucial resource for developing image processing algorithms and deep learning models for tasks such as classification, object detection, or segmentation. Its application stands to significantly enhance advancements in textile engineering and manufacturing processes.<br>The FD_Dataset comprises two distinct files: FD, which encompasses comprehensive datasets alongside Label.mat facilitated through MATLAB for any object detection model.YOLO, housing datasets for training, validation, and testing specifically tailored for YOLO object detection models.

本数据集包含720张彩色织物缺陷图像，每张图像均展示了四类典型织物缺陷：油污（Oil）、破洞（Hole）、割疵（Cutting）与裂纹（Crack），每类缺陷的图像数量约为180张。
本数据集具有显著的学术研究价值，尤其在计算机视觉（Computer Vision）领域，是开发图像处理算法与深度学习模型的关键资源，可用于分类、目标检测、语义分割等视觉任务的算法研发。其应用可有效推动纺织工程与制造工艺的技术升级与发展。
FD_Dataset包含两类独立文件：一类为FD文件夹，整合了完整数据集与配套的Label.mat标注文件，可通过MATLAB加载，适配任意目标检测模型；另一类为YOLO文件夹，内含专为YOLO目标检测模型定制的训练、验证与测试数据集。

搜集汇总

背景与挑战

背景概述

FD_Dataset.7z是一个包含720张织物缺陷图像的数据集，涵盖四种缺陷类型，适用于计算机视觉任务，如分类、目标检测和分割。数据集分为FD和YOLO两部分，分别支持MATLAB和YOLO模型的应用。