Stemson-AI/Warwick-STEM

Warwick STEM Dataset (WebDataset)

A collection of 19,769 experimental scanning transmission electron microscopy (STEM) images from the University of Warwick, spanning hundreds of diverse materials projects collected between 2010 and 2018.

Dataset Description

This dataset contains experimental STEM images originally published as part of the Warwick Electron Microscopy Datasets by Jeffrey Ede. The images cover a wide range of materials and imaging conditions, making them useful for self-supervised pre-training of microscopy foundation models.

Format

WebDataset format: 170 TAR shards (~1 GB each), 160 GB total.

Each sample in a shard contains:

• {idx:06d}.tif — 32-bit float TIFF image
• {idx:06d}.json — metadata

Metadata Fields

Field	Type	Description
original_filename	string	Original filename from the Warwick dataset
width	int	Image width in pixels
height	int	Image height in pixels
dtype	string	Pixel data type (float32)
min_value	float	Minimum pixel intensity
max_value	float	Maximum pixel intensity
mean_value	float	Mean pixel intensity
std_value	float	Standard deviation of pixel intensity

Image Properties

• Count: 19,769
• Format: 32-bit float TIFF
• Resolutions: Mixed — 2048x2048 (40%), 1024x1024 (34%), 512x512 (16%), other (10%)
• Modality: STEM (various detector configurations)
• Instruments: Multiple instruments at the University of Warwick (2010–2018)

Usage

import webdataset as wds
from torch.utils.data import DataLoader

url = "path/to/warwick_stem_wds/train-{0000..0169}.tar"
dataset = wds.WebDataset(url).decode().shuffle(1000)
dataloader = DataLoader(dataset, batch_size=32, num_workers=4)

for sample in dataloader:
    image = sample[".tif"]
    metadata = sample[".json"]

Source

Original data from Jeffrey-Ede/datasets on GitHub. Please cite the original work if you use this dataset.

License

CC-BY-4.0