dimun/dates
收藏Hugging Face2024-03-03 更新2024-03-04 收录
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---
license: apache-2.0
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# Annotation
The provided format is a generalized representation of metadata associated with image files. Each image entry includes details such as its height and width. Additionally, it contains annotations represented as a list ("ann"), where each annotation is described by a dictionary. Each annotation dictionary includes the class of the annotation ("cls"), the bounding box coordinates ("bbox") in the format [x_min, y_min, x_max, y_max], and the transcription associated with that annotation. This format allows for the annotation of various elements within images, making it suitable for tasks such as object detection, text recognition, or any other task where spatial and semantic information needs to be annotated.
# Citation
Dataset published originally in `A Generalized Framework for Recognition of Expiration Date on Product Packages Using Fully Convolutional Networks`
@article{seker2022generalized,
title={A generalized framework for recognition of expiration dates on product packages using fully convolutional networks},
author={Seker, Ahmet Cagatay and Ahn, Sang Chul},
journal={Expert Systems with Applications},
pages={117310},
year={2022},
publisher={Elsevier}
}
提供机构：
dimun
原始信息汇总
数据集描述
标注格式
提供的格式是与图像文件相关联的元数据的通用表示。每个图像条目包括其高度和宽度等详细信息。此外，它包含以列表形式表示的标注（"ann"），其中每个标注由一个字典描述。每个标注字典包括标注的类别（"cls"）、边界框坐标（"bbox"）以[x_min, y_min, x_max, y_max]格式表示，以及与该标注相关的转录。这种格式适用于图像中各种元素的标注，适合用于对象检测、文本识别或其他需要空间和语义信息标注的任务。
引用
数据集最初发表于以下文献：
- 标题：A Generalized Framework for Recognition of Expiration Date on Product Packages Using Fully Convolutional Networks
- 作者：Seker, Ahmet Cagatay 和 Ahn, Sang Chul
- 期刊：Expert Systems with Applications
- 页码：117310
- 年份：2022
- 出版商：Elsevier
