Datasets
Open Access
Real-Life Diabetogenic Database
- Citation Author(s):
- Submitted by:
- Cong Bai
- Last updated:
- Tue, 05/17/2022 - 22:21
- DOI:
- 10.21227/h6zz-mn96
- Link to Paper:
- License:
- Categories:
Abstract
Real-Life Diabetogenic (RLD) database is built for evaluating the cross-modal retrieval algorithm in real-life dietary environment, and it has 4500 multimodal pairs in total,where each images can be related to multiple texts and each text can be related to multiple images.
For more details, you can refer to our paper: P. Zhou, C. Bai, J. Xia and S. Chen, "CMRDF: A Real-Time Food Alerting System Based on Multimodal Data," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2020.2996009.
Please cite the above paper if you use this database.
Package structure
Since this is a multimodal database, the images in RLD is related to texts by share the same tag, which is saved in `food/im_label`
* `Lifelog`: the real-world food images and the associative instant bio-data {
** `RL`: the folder that contains all the real-world food images.
** `biodata.csv`: the csv file that contains all the associative instant bio-data, these data are associated to food images by the file names of images.
** `biodata.txt`: the txt that indicate the attributes of each column in `biodata.csv`.
}
* `Food`: the food description texts and the associative food nutrition composition data
{
** `description.csv`: the csv file that contains all the food description texts refered to each tag.
** `description.txt`: the txt file that indicate the attributes of each column in `description.csv`.
** `composition.csv`: the csv file that contains all the food nutrition composition data refered to each tag.
** `composition.txt`: the txt file that indicate the attributes of each column in `composition.csv`.
** `im_label.csv`: the csv file that contains all the tags related to each image.
** `im_label.txt`: the txt file that indicate the attributes of each column in `image.csv`.
}
* `data_category.csv`: the health category tags that help the model test the performance of cross-modal retrieval.
Dataset Files
- RLD.zip (459.82 MB)
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Documentation
Attachment | Size |
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README.txt | 2.01 KB |