datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multi-label-food-recognition
Multi-Label Food Recognition Dataset
This is a multi-label food recognition dataset generated from single-class food images.
Each image contains 2-5 different food items composited together using natural composition methods.
Dataset Details
Total Images: 13,000
Training Images: 10,400 (80%)
Validation Images: 2,600 (20%)
Number of Classes: 90
Labels per Image: 2-5 labels
Image Format: RGB, 512x512 pixels
File Format: Parquet
Dataset Structure
Each sample… See the full description on the dataset page: https://huggingface.co/datasets/ibrahimdaud/multi-label-food-recognition.multilabel-imagenet-1k
MultiLabel ImageNet-1K Train Annotations with Selected Masks
This dataset contains automated multi-label annotations for the ImageNet-1K training split, together with spatial masks for the selected object-level labels.
The release is designed to make the annotations easy to inspect and reuse. It does not include the original ImageNet images. Users need access to the ImageNet-1K training images separately; image paths are stored relative to the ImageNet train root, for example:… See the full description on the dataset page: https://huggingface.co/datasets/k3999/multilabel-imagenet-1k.