datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IQA-PyTorch-Datasets
Description
This is the dataset repository used in the pyiqa toolbox. Please refer to Awesome Image Quality Assessment for details of each dataset
Example commandline script with huggingface-cli:
huggingface-cli download chaofengc/IQA-PyTorch-Datasets live.tgz --local-dir ./datasets --repo-type dataset
cd datasets
tar -xzvf live.tgz
Disclaimer for This Dataset Collection
This collection of datasets is compiled and maintained for academic, research, and educational… See the full description on the dataset page: https://huggingface.co/datasets/chaofengc/IQA-PyTorch-Datasets.IQA-PyTorch-Datasets-metainfo
Description
This repo contains the meta information of datasets stored in chaofengc/IQA-PyTorch-Weights. They are used in the training codes of the pyiqa toolbox.
Disclaimer for Datasets Included
This collection of datasets is compiled and maintained for academic, research, and educational purposes. It is important to note the following points regarding the datasets included in this Collection:
Rights & Permissions: Each dataset in this Collection is the property of its… See the full description on the dataset page: https://huggingface.co/datasets/chaofengc/IQA-PyTorch-Datasets-metainfo.IQA_dataastro_iqa
Dataset Card for Dataset Name
We provide here datasets to help in building classification for quality of astronomical images. It is inspired from the publication
Assessment of Astronomical Images Using Combined Machine-learning Models.
Authors of the publication did not provide access to the datasets used.
We provide 2 different datasets:
raw dataset: astronomical images with LDAC files containing features extracted with the tool SExtractor,
processed dataset: catalogs of… See the full description on the dataset page: https://huggingface.co/datasets/selfmaker/astro_iqa.public_iqa_vqa_databasesIQA_datasetIQAllava-10k-cot-iqa-opsambient-o-clip-iqa-patches-imagenet
Ambient Diffusion Omni (Ambient-o): Training Good Models with Bad Data
Dataset Description
Ambient Diffusion Omni (Ambient-o) is a framework for using low-quality, synthetic, and out-of-distribution images to improve the quality of diffusion models. Unlike traditional approaches that rely on highly curated datasets, Ambient-o extracts valuable signal from all available images during training, including data typically discarded as "low-quality."
This dataset card is for… See the full description on the dataset page: https://huggingface.co/datasets/adrianrm/ambient-o-clip-iqa-patches-imagenet.MP-IQAsocial_iqaIQA-Dataset
A Unified Interface for IQA Datasets
This repository contains a unified interface for downloading and loading 20 popular Image Quality Assessment (IQA) datasets. We provide codes for both general Python and PyTorch.
Citation
This repository is part of our Bayesian IQA project where we present an overview of IQA methods from a Bayesian perspective. More detailed summaries of both IQA models and datasets can be found in this interactive webpage.
If you find our project… See the full description on the dataset page: https://huggingface.co/datasets/IQA-Dataset-team-IVC/IQA-Dataset.llava-10k-cot-iqa-qwen_28_1024UHD-IQA-VC6UHD-IQA-J2Kllava-10k-cot-iqa-ops_28_1024faithfulness-social_iqa-debug-backupUHD-IQA-JPHfaithfulness-social_iqa-debug_1-sft-prompts-user-bias-balancedUHD-IQA-JPGfaithfulness-social_iqa-debug_1faithfulness-social_iqa-debug_1-sft-prompts-random-insertion-balancedUHD-IQA-VC6-Losslessfaithfulness-social_iqacompany_iqa_for_qftTatar_IQA_dsiqa-project-dataset
IQA Project Dataset
This is the dataset used in our capstone IQA project. Most of the labels.csvs
are produced by further processing the labels provided by
LIQE into a more
convenient format, using our dataset preprocessing
scripts.
labels.csv Columns
The meanings of the columns that can appear in labels.csv are as follows:
filename: The filename inside the images directory. If there are
subdirectories inside images, this can contain more than one path segment.
mos:… See the full description on the dataset page: https://huggingface.co/datasets/palapapa/iqa-project-dataset.faithfulness-social_iqa-debugfaithfulness-social_iqa-ibm-granite_granite-3.3-8b-instruct-user-biasUHD-IQA-J2K-Lossless