datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
emonet-face-binary
EmoNet-Face: A Fine-Grained, Expert-Annotated Benchmark for Facial Emotion Recognition
Dataset Summary
EmoNet-Face is a comprehensive benchmark suite designed to address critical gaps in facial emotion recognition (FER). Current benchmarks often have a narrow emotional spectrum, lack demographic diversity, and use uncontrolled imagery. EmoNet-Face provides a robust foundation for developing and evaluating AI systems with a deeper, more nuanced understanding of human… See the full description on the dataset page: https://huggingface.co/datasets/laion/emonet-face-binary.danyig-pedri-binary-script-classifier
Danyig vs Pedri Binary Script Classification Dataset
Stage-2 binary classifier for distinguishing Danyig (5 subscripts: DraDring, DraRing, Drathung, Gongshabma, Tsegdrig) from Pedri (2 subscripts: Peri, Petsuk). Real-only, all images human-reviewed.
Images per class
Class
train
val
test
All
Danyig
480
60
60
600
Pedri
480
60
60
600
Total
960
120
120
1,200
Splits
Manuscript-stratified split — each manuscript work appears in exactly… See the full description on the dataset page: https://huggingface.co/datasets/BDRC/danyig-pedri-binary-script-classifier.places-water-binary
Places — Water or No Water
34 original photographs labelled by whether a body of water is visible, resized to
224x224. Homework 1.
Property
Value
Splits
train (391), validation (5), test (6)
Resolution
224x224 RGB
Target
label — 1 water, 0 no_water
Balance (all originals)
17 water / 17 no_water
Purpose
Binary image classification: is there a body of water in this scene?
Composition
Column
Type
Description
image
image… See the full description on the dataset page: https://huggingface.co/datasets/ssg1/places-water-binary.BinaryBreaKHistekno21-brain-stroke-dataset-binary
Dataset Card for BTX24/tekno21-brain-stroke-dataset-binary
Dataset Description
📌 EN:The TEKNO21 Brain Stroke Dataset consists of 7,369 anonymized brain CT scans in DICOM and PNG formats, labeled by seven expert radiologists. It includes acute/hyperacute ischemic and hemorrhagic stroke cases, as well as non-stroke images. Each annotation was verified for accuracy. The dataset was curated from the Turkish Ministry of Health’s e-Pulse and Teleradiology System (2019–2020) as… See the full description on the dataset page: https://huggingface.co/datasets/BTX24/tekno21-brain-stroke-dataset-binary.checkbox-cropped-binary
Source Reference
This dataset was sourced and prepared from the original dataset hosted on
Roboflow:
🔗 https://universe.roboflow.com/checkbox-detection-ztyeq/checkbox-kwtcz-qkbid/dataset/7
Checkbox Cropped Binary Dataset
This dataset contains cropped checkbox regions extracted from document images
for binary classification: checked vs unchecked.
Structure
train/
checked/
unchecked/
valid/
checked/
unchecked/
test/
checked/
unchecked/
Description… See the full description on the dataset page: https://huggingface.co/datasets/meghnagera15/checkbox-cropped-binary.stickers-binary-v2-cleaned
Stickers Binary v2 — Cleaned
Binary SFW/NSFW sticker classification dataset. This version has been cleaned
of likely label errors using cross-validated out-of-fold model predictions
combined with cleanlab's
find_label_issues.
Structure
This dataset has exactly two columns:
Column
Type
Description
image
image
The sticker image, 256x256, letterboxed (see below).
label
int64
0 = SFW, 1 = NSFW.
Class distribution
Split
Count… See the full description on the dataset page: https://huggingface.co/datasets/Pankaj8922/stickers-binary-v2-cleaned.