Academic-Only Dataset Access Request
This dataset is available exclusively to academic organizations for non-commercial use. Please answer the following questions to verify your eligibility.
Eligibility is limited to individuals affiliated with academic institutions using this dataset for research or educational purposes only.
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FoodLogAthl Meal Image Dataset
Overview
FoodLogAthl-218 is a real-world meal image dataset containing 6,925 original photos, each annotated with one or more food bounding boxes and rich metadata (capture date, user ID). Unlike web-sourced collections, these images come from an actual dietary management app, FoodLog Athl, reflecting everyday photo conditions and meal diversity.
Background & Motivation
Most public food image datasets (e.g. Food-101, UEC Food256, Food2K) are built from carefully curated web images, often favoring visually polished, single-dish photos. Such benchmarks fail to capture the messy, multi-dish snapshots people take for personal food logs.
FoodLogAthl-218 bridges this gap by leveraging images uploaded by real users of the FoodLog Athl app, yielding a challenging, authentic benchmark for both classification and object-detection models in dietary-management applications.
Data Collection
- Source: FoodLog Athl (dietary-management app)
- Period: May 2023 – Oct 2024
- User selection: all meal records linked to dietitians with ≥3 active users
- Record contents: user ID, recording date, original image, crop-based bounding boxes, dish names
- Multi-dish handling: each detected dish becomes a separate sample, but images with any invalid crop are discarded as a whole to preserve real meal frequency
Directory Structure
FoodLogAthl-218/
├── images/
│ ├── image_XXXXX.jpg
│ └── ... (total 6,925 images)
├── annotations/
│ └── instances_coco.json
├── metadata.csv
├── class_map.csv
├── .gitattributes
├── .gitignore
└── README.md
File Descriptions
images/
All original.jpgfiles namedimage_<ID>.jpg.annotations/instances_coco.json
Standard COCO fields:images(id, file_name, width, height)annotations(id, image_id, category_id, bbox [x_min, y_min, w, h], area, iscrowd)categories(id, name)
metadata.csv
file_name record_date user_id image_125683.jpg 2024-06-17 248 image_121223.jpg 2023-05-12 105 image_123574.jpg 2024-06-17 105 … … … class_map.csv:
- Mapping information between class names and IDs
.gitattributes:
- Git attributes configuration file
.gitignore:
- Git ignore configuration file
README.md
This overview, plus usage and license details.
Usage Example
from datasets import load_dataset
ds = load_dataset("your-username/foodlogathl")
print(ds)
# ➞ DatasetDict({
# train: Dataset(...)
# })
# Access:
images = ds["train"]["images"]
annotations = ds["train"]["annotations"]
metadata = ds["train"]["metadata"]
User Instructions for FoodLogAthl-218
This dataset is available exclusively to academic institutions for non-commercial research and educational use.
To request access, please fill out the application form with the required information and click Apply.
Once we review your request (typically within 2–3 business days), you will receive an email notification with access instructions.
After You Apply
- Review period: 2–3 business days
- Eligibility: Only applications from academic or research institutions with non-commercial intent will be considered
- Contact: For any questions about access, please email foodlog-hal@hal.t.u-tokyo.ac.jp
- Access granted: If approved, you'll receive read-only access to the
images/andannotations/folders via your Hugging Face account
Usage Policy
This dataset is strictly limited to academic institutions and may only be used for non-commercial research and educational purposes. Commercial use, redistribution, or use by non-academic organizations is not permitted. All access requests are manually reviewed to ensure compliance with these conditions.
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