datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
corruption-glass_blur
Corruption Dataset: Glass_Blur
Dataset Description
This dataset contains corrupted versions of ImageNet-1K images using glass_blur corruption. It is part of the ImageNet-C benchmark for evaluating model robustness to common image corruptions.
Dataset Structure
Train: 1,281,167 corrupted images
Validation: 50,000 corrupted images
Classes: 1000 ImageNet-1K classes
Format: Arrow (Hugging Face Datasets)
Corruption Type: Glass_Blur
Applies glass blur… See the full description on the dataset page: https://huggingface.co/datasets/MarMaster/corruption-glass_blur.SynGallery-abl4-tex-light-glass-frame
SynGallery-abl4-tex-light-glass-frame: + frame variety
Rung 4 of the SynGallery instance-level artwork-recognition ablation ladder. 4,898 MET paintings × 5 camera viewpoints = 24,490 synthetic RGB images at 512×512, paired with their source photos and museum metadata.
In this rung, the scene varies textures, lighting, glass and frame molding variant + color/roughness/metallic, while freezing camera pose (the only frozen factor). Same schema, source images and index↔painting… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-abl4-tex-light-glass-frame.SynGallery-abl3-tex-light-glass
SynGallery-abl3-tex-light-glass: + glass
Rung 3 of the SynGallery instance-level artwork-recognition ablation ladder. 4,898 MET paintings × 5 camera viewpoints = 24,490 synthetic RGB images at 512×512, paired with their source photos and museum metadata.
In this rung, the scene varies textures, lighting and a glass sheet present with probability 0.25, while freezing frame variant/color, camera pose. Same schema, source images and index↔painting mapping as every other rung — they… See the full description on the dataset page: https://huggingface.co/datasets/patryk-bartkowiak/SynGallery-abl3-tex-light-glass.water_glassbottle_aesthetics_rated
Dataset Card for Dataset Name
This dataset holds 121 images of glass bottles for drinking water. The aesthetics were rated by five participants from Germany across different demographics.