SOHL Multi-Dish Indian Food Detection Dataset with 377 Annotated Images

377 annotated images of Indian food plates, each containing multiple dishes, designed for training YOLO models. The dataset includes 16 food classes and was created on 2025-08-16 by Ayyan18.

Use Cases

• Train object detection models to identify multiple Indian food dishes on a single plate based on the annotated images.
• Benchmark model performance for multi-label food recognition tasks.
• Develop applications for dietary tracking or food logging using visual recognition of Indian cuisine.

Strengths

• 377 images with corresponding annotations, ensuring a paired image-label structure.
• 16 distinct food classes, including breads like roti and naan, providing a multi-class classification challenge.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Dataset size of 377 images may be limited for training complex models without augmentation.

Provenance

Source

Ayyan18 on Hugging Face.

Collection Method

Method of gathering is not described.

Time Range

Creation date is 2025-08-16; temporal coverage of images is not specified.

Freshness

Last updated 2026-04-12 20:40:21; freshness should be verified.

Geography

Focus is on Indian food; spatial coverage is not explicitly stated.