datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
stable-diffusion-v1-5-glazed
Dataset Card for Stable Diffusion v1.5 Glazed Samples
Dataset Description
Dataset Summary
This dataset contains image samples originally generated by runwayml/stable-diffusion-v1-5
and subsequently processed by Glaze tool.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information… See the full description on the dataset page: https://huggingface.co/datasets/hanamizuki-ai/stable-diffusion-v1-5-glazed.age-difference-dataset
Age Difference Images Dataset for Facial Recognition
Dataset comprises 10,557 images of 2,627 unique individuals captured at different stages of their lives, showcasing the same people across various ages. It is designed for research in age estimation, facial aging analysis, and age progression modeling, providing a robust foundation for machine learning models and statistical analysis.
By leveraging this dataset, researchers and developers can explore age differences, gender… See the full description on the dataset page: https://huggingface.co/datasets/UniDataPro/age-difference-dataset.ultrasound_images_diffusionThis dataset contains synthetic EDM2 generated images of ultrasound scan, as described in the paper A Foundational EDM2-Based Generative Model for High-Resolution Synthetic Fetal Ultrasound Imaging from Open Datasets.
Code: https://github.com/xfetus/fetal-ultrasound-edm2
The class labels correspond to the following labels:
plane_classes = {
0: 'Other',
1: 'Maternal cervix',
2: 'Fetal abdomen',
3: 'Fetal brain',
4: 'Fetal femur',
5: 'Fetal thorax',
}
Facial-Expression
Facial Expression Dataset
Description
This dataset contains images of human faces categorized by emotional expression. It is intended for training and evaluating models for facial expression recognition.
Structure
The dataset is divided into two main folders:
train: Contains images for training the model.
test: Contains images for evaluating the model.
Both train and test folders contain subfolders for each of the 7 emotion categories:
angry
disgusted… See the full description on the dataset page: https://huggingface.co/datasets/Teen-Different/Facial-Expression.DiffraNet
DiffraNet
Dataset description
This repository contains the DiffraNet diffraction image dataset introduced by Souza et al. in the paper "DeepFreak: Learning Crystallography Diffraction Patterns with Automated Machine Learning". The original dataset consists of 512×512 grayscale diffraction images, including both synthetic and real experimental data. The synthetic images were generated using the nanoBragg simulator, while the real images were collected from serial… See the full description on the dataset page: https://huggingface.co/datasets/DobromirN/DiffraNet.generated-flowers-diffusion
Dataset Card for generated_flowers_with_embeddings
This is a FiftyOne dataset with 150 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("jkubuni/generated-flowers-diffusion")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/jkubuni/generated-flowers-diffusion.diffusion-flowers-fiftyone
Dataset Card for generated_flowers_with_embeddings
This is a FiftyOne dataset with 10 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("finnfrei/diffusion-flowers-fiftyone")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/finnfrei/diffusion-flowers-fiftyone.diffusion_model_assessment_v2
Dataset Card for generated_flowers_with_embeddings
This is a FiftyOne dataset with 286 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("CarloColumbo/diffusion_model_assessment_v2")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/CarloColumbo/diffusion_model_assessment_v2.diffusion_model_assessment_v2
Dataset Card for generated_flowers_with_embeddings
This is a FiftyOne dataset with 20 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Linus-L/diffusion_model_assessment_v2")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Linus-L/diffusion_model_assessment_v2.