Awesome
<p align=center>Bento800🍱</p>
🎑 News
- [23/03/06] Bento800🍱_Text📝 is released.
- [22/10/22] Paper and Bento800🍱 (Version1.0) are released.
- [22/09/13] Add Bento800 creation process.
- [22/08/04] This repo is created.
🍀 Overview
Bento800 is the first manually annotated synthetic box lunch presentation dataset for novel aesthetic box lunch presentation design.
Bento800 is composited from 34 single food images in 6 categories:
<p align=center> Rice🍚(10) ; Fried Chicken🍗(5) ; Salt-grilled Salmon🐟(5) ; Tamagoyaki🧈(6) ; Croquette🍪(5) ; Fried Shrimp🍤(3) </p>with 3 different types of food presentations:
(1) Place fried chicken on rice;
(2) Place salt-grilled salmon and tamagoyaki on rice;
(3) Place croquette and fried shrimp on rice, the fried shrimp is on the croquette.
🌱 Dataset Creation Process
Bento800🍱_Text📝
- Image Details
| Content | Tools | Details |
|---|---|---|
| Resize | - | Paste images in Bento800 onto a transparent image. |
- Text Description Details
| Content | Tools | Details |
|---|---|---|
| Text Paraphrasing | ChatGPT | Rephrase the above sentences with the template “Rephrase: [Input] with 25 examples” and “Rephrase: [Input]"+"Please try again"×24. |
Bento800🍱
- Image Details
| Content | Tools | Details |
|---|---|---|
| Image Collection | Google Image | These high-resolution images contain at least one complete food item. |
| Remove Background | removebg | Remove the background and unnecessary parts. |
| Image Compositing | - | Manually composite + random data augmentation. |
- Annotation Details
| Content | Tools | Details |
|---|---|---|
| Modal Segmentation | Dataloop | Manually marked visible parts and occluded parts. |
| Food Item Labels & Bounding Box & Ordering List | VGG Image Annotator (VIA) | Manually annotated several food item attributes. |
🎁 Download
| Content | Size | Files | Format | Details |
|---|---|---|---|---|
| Bento800🍱_Text📝 [Google Drive] [Tencent Cloud] | - | 1600 | Main Folder | |
| ├ Image | 216MB | 800 | PNG | Food images from Bento800 of size 600×600 |
| ├ Text | 793 KB | 800 | TXT | 9 descriptions for each image in Bento800 |
| Content | Size | Files | Format | Details |
|---|---|---|---|---|
| Bento800🍱v1.0 [Google Drive] | - | 872 | Main Folder | |
| ├ S1_collection | 3.26 MB | 34 | JPG | 34 food images in 6 categories |
| ├ S2_removebg | 2.81 MB | 34 | PNG | Remove Background |
| ├ S3_train | 410 MB | 766 | PNG | Training images |
| ├ S3_val | 18.8 MB | 34 | PNG | Testing images |
| ├ S4_segmentation | 8.72 MB | 2 | JSON | Semantic Segmentation |
| ├ S5_annotation | 403 KB | 2 | CSV | Simple text descriptions + Ordering id + Bounding Box + Food item labels |
📚 Feedback
Please fill out the Bento800 Dataset Feedback Form.
I would greatly value your thoughts, suggestions, concerns or problems.
⭐ Citation
<p align=center>“We eat🍴 first with our eyes👀~ ”</p>
If you find this dataset helpful for your research, please cite it as below:
@inproceedings{zhou2022able,
title={ABLE: Aesthetic Box Lunch Editing},
author={Zhou, Yutong and Shimada, Nobutaka},
booktitle={Proceedings of the 1st International Workshop on Multimedia for Cooking, Eating, and related APPlications},
pages={53--56},
year={2022}
}