chest-xray
nih-chest-xray-14-flatchest-xray-pneumoniaDataset Summary
The dataset is organized into 3 folders (train, test, val) and contains subfolders for each image category (Pneumonia/Normal). There are 5,863 X-Ray images (JPEG) and 2 categories (Pneumonia/Normal).
Chest X-ray images (anterior-posterior) were selected from retrospective cohorts of pediatric patients of one to five years old from Guangzhou Women and Children’s Medical Center, Guangzhou. All chest X-ray imaging was performed as part of patients’ routine clinical care.
For… See the full description on the dataset page: https://huggingface.co/datasets/hf-vision/chest-xray-pneumonia.vinbigdata-chest-xray-abnormalities-png
VinBigData Chest X-ray Abnormalities (Private Processed Mirror)
Private repository for personal transfer / research use only. Do not redistribute.
Derived from the VinBigData Chest X-ray Abnormalities Detection / VinDr-CXR dataset. Original data is subject to the VinBigdata / PhysioNet data use agreement; keep this repo private and do not share access with third parties.
Contents
Path
Description
image/train/*.png
4394 train images with abnormalities… See the full description on the dataset page: https://huggingface.co/datasets/ASD9987/vinbigdata-chest-xray-abnormalities-png.NIH-Chest-Xray-14chest-xray-classification
Dataset Labels
['NORMAL', 'PNEUMONIA']
Number of Images
{'train': 4077, 'test': 582, 'valid': 1165}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("keremberke/chest-xray-classification", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/mohamed-traore-2ekkp/chest-x-rays-qjmia/dataset/2
Citation… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/chest-xray-classification.nih-chest-xray
NIH ChestX-ray14 — WebDataset
Dataset original: nih-chest-xrays/data
Imágenes: 112,120 PNGs en escala de grises (1024×1024)
Formato: WebDataset (TAR archives, ~1000 imágenes por TAR)
Split: train
Cómo cargar
from datasets import load_dataset
ds = load_dataset("webdataset", data_dir="yeigen/nih-chest-xray", split="train", streaming=True)
for sample in ds:
img = sample["png"] # PIL Image
print(img.size)
break