datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
textures3
Description
This is the third iteration and official release of a dataset curated to power the Materializer model for Blender. The dataset contains a range of labeled texture images that were sourced from ambientCG under their Creative Commons CC0 1.0 Universal License. These textures are designed to help in the classification of various material maps, which are essential for creating realistic 3D materials in Blender.
Future Plans
The dataset is still evolving, and I… See the full description on the dataset page: https://huggingface.co/datasets/DeathDaDev/textures3.texture-shape-cue-conflictThis dataset contains the stimuli for ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness by Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A. Wichmann, and Wieland Brendel.
The stimuli allow testing of the texture/shape bias in an observer model (human or artificial) by containing two conflicting cues per image (shape and texture). The images generated using iterative style transfer (Gatys et al., 2016) between… See the full description on the dataset page: https://huggingface.co/datasets/rgeirhos/texture-shape-cue-conflict.Kather-texture-2016
Collection of textures in colorectal cancer histology
Description
This data set represents a collection of textures in histological images of human colorectal cancer.
It contains 5000 histological images of 150 * 150 px each (74 * 74 µm). Each image belongs to exactly one of eight tissue categories.
Image format
All images are RGB, 0.495 µm per pixel, digitized with an Aperio ScanScope (Aperio/Leica biosystems), magnification 20x.
Histological samples are… See the full description on the dataset page: https://huggingface.co/datasets/YueFanXia/Kather-texture-2016.