datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
imagenet-r
ImageNet-R
This repo is made to facilitate the evaluation of various pretraining models. It's constructed from the source file provided by official implementation.
Usage
from datasets import load_dataset
dataset = load_dataset('axiong/imagenet-r')
Dataset Summary
ImageNet-R(endition) contains art, cartoons, deviantart, graffiti, embroidery, graphics, origami, paintings, patterns, plastic objects, plush objects, sculptures, sketches, tattoos, toys, and video… See the full description on the dataset page: https://huggingface.co/datasets/axiong/imagenet-r.pmc_oa_demoFoundation models trained on large-scale dataset gain a recent surge in CV and NLP. In contrast, development in biomedical domain lags far behind due to data scarcity.
To address this issue, we build and release PMC-OA, a biomedical dataset with 1.6M image-caption pairs collected from PubMedCentral's OpenAccess subset, which is 8 times larger than before.
PMC-OA covers diverse modalities or diseases, with majority of the image-caption samples aligned at finer-grained level, i.e., subfigure and subcaption.
While pretraining a CLIP-style model on PMC-OA, our model named PMC-CLIP achieves state-of-the-art results on various downstream tasks,
including image-text retrieval on ROCO, MedMNIST image classification, Medical VQA, i.e. +8.1% R@10 on image-text retrieval, +3.9% accuracy on image classification.pokemon-blip-captions
Dataset Card for Pokémon BLIP captions
Dataset used to train Pokémon text to image model
BLIP generated captions for Pokémon images from Few Shot Pokémon dataset introduced by Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis (FastGAN). Original images were obtained from FastGAN-pytorch and captioned with the pre-trained BLIP model.
For each row the dataset contains image and text keys. image is a varying size PIL jpeg, and text is the… See the full description on the dataset page: https://huggingface.co/datasets/AxionLab-official/pokemon-blip-captions.