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Watermelon appearance and knock correlate data sets with sugar content
- Citation Author(s):
- Submitted by:
- Ryan Chen
- Last updated:
- Tue, 12/17/2024 - 09:15
- DOI:
- 10.21227/wb3s-h174
- Data Format:
- License:
1750 ViewsAbstract
We are pleased to introduce the Qilin Watermelon Dataset, a unique collection of data aimed at investigating the relationship between a watermelon's appearance, tapping sound, and sweetness. This dataset is the result of our dedicated efforts to capture and record various aspects of Qilin watermelons, a special variety known for its exceptional taste and quality.
Our dataset consists of two primary components: wav files and jpg files. The wav files contain audio recordings of the tapping sounds produced when striking the watermelons with varying degrees of force. These recordings capture the acoustic properties of the watermelons, which may provide insights into their internal structure and ripeness. Alongside the audio files, we have also included jpg files that showcase the external appearance of each watermelon. These images encompass various visual characteristics, such as color, texture, and shape, which may contribute to the overall assessment of the watermelon's quality.
To ensure the accuracy and reliability of our dataset, we employed a rigorous data collection process. We used a sugar meter to measure the sweetness of each watermelon, providing a quantitative value that can be correlated with the tapping sounds and visual appearance. By recording the sweetness levels, we aim to establish a comprehensive understanding of how these factors interplay and potentially influence the watermelon's taste.
麒麟西瓜数据集的主要目的是促进对西瓜外部因素与其内部品质之间关系的研究和分析。通过探索外观、敲击声和甜味之间的联系，我们希望发现有价值的见解，有助于对西瓜质量进行无损评估。该数据集有可能为农业、食品科学和机器学习等各个领域做出贡献，在这些领域中，用于水果质量评估的预测模型的开发引起了极大的兴趣。
我们相信，麒麟西瓜数据集将成为研究人员、数据科学家和有兴趣探索西瓜品质评估复杂性的爱好者的宝贵资源。通过提供全面的音频、视频和甜味数据集合，我们旨在促进这一令人兴奋的研究领域的创新和合作。
Qilin Watermelon Dataset Structure
The Qilin Watermelon Dataset is structured in a way that facilitates easy understanding and usage. The dataset consists of two main directories: "picture" and "audio", which contain the original data files, and a processed data directory named "chu".
In the dataset, each file follows a naming convention that includes an underscore symbol ("_"). The part before the underscore represents the unique identifier or serial number of the watermelon sample, while the part after the underscore indicates the sweetness measurement obtained using a sugar meter.
For example, a file named "001_12.jpg" would represent the image of watermelon sample number 001, which has a sweetness measurement of 12 according to the sugar meter.
The "picture" directory contains the jpg files showcasing the external appearance of each watermelon, capturing visual characteristics such as color, texture, and shape. These images can be used for visual analysis and feature extraction.
The "audio" directory contains the wav files capturing the tapping sounds produced when striking the watermelons with varying degrees of force. These audio recordings can be used to analyze the acoustic properties of the watermelons and potentially correlate them with the sweetness measurements.
In addition to the original data, the dataset also includes a "chu" directory, which contains processed data. This directory is intended for users who prefer to work with pre-processed data or want to compare their processing techniques with the provided processed files.
If you are unsure about how to use or navigate the Qilin Watermelon Dataset, you can refer to the GitHub repository at https://github.com/crf0409/watermelon_eval. This repository contains code examples and explanations that can guide you through the process of loading, processing, and analyzing the dataset.
By understanding the structure and naming convention of the Qilin Watermelon Dataset, you can easily access and utilize the data for your research or analysis related to watermelon quality assessment.
