datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
emotionsRobot-EQ
RobotEQ-Data
Official dataset release for RobotEQ.
Evaluation & Scripts
For inference scripts, evaluation scripts, and data production tooling, see the RobotEQ code repository.
Dataset Statistics
Item
Count
Behavior judgment scenarios (synthetic)
1,812
Behavior judgment scenarios (real POV)
223
Behavior judgment scenarios (total)
2,035
Behavior judgment behavior annotations
3,171
Spatial grounding questions
825… See the full description on the dataset page: https://huggingface.co/datasets/Tongji-Emotion/Robot-EQ.emotion6-testEMID-Emotion-Matching
EMID-Emotion-Matching
orrzohar/EMID-Emotion-Matching is a derived dataset built on top of
the Emotionally paired Music and Image Dataset (EMID) from ECNU (ecnu-aigc/EMID).
It is designed for music ↔ image emotion matching with Qwen-Omni–style models.
Each example contains:
audio: mono waveform stored as datasets.Audio (HF Hub preview can play it)
sampling_rate: sampling rate used when decoding (typically 16 kHz)
image: a single image (datasets.Image)
same: bool, whether the audio… See the full description on the dataset page: https://huggingface.co/datasets/orrzohar/EMID-Emotion-Matching.child-emotion-drawings-pilot
Children's Emotional Drawings Pilot Dataset
A small balanced derived pilot dataset for experimental classification of emotional patterns in children's drawings.
Dataset
204 unique original drawings
492 total image instances
3 target classes: happiness, anxiety_depression, anger_aggression
Splits:
train: 432 images
validation: 30 images
test: 30 images
The dataset was created from the public anamelClassification dataset.
Original… See the full description on the dataset page: https://huggingface.co/datasets/stanislav-dykyi/child-emotion-drawings-pilot.ukr-emotions-binary
EmoBench-UA: Emotions Detection Dataset in Ukrainian Texts
EmoBench-UA: the first of its kind emotions detection dataset in Ukrainian texts. This dataset covers the detection of basic emotions: Joy, Anger, Fear, Disgust, Surprise, Sadness, or None.
Any text can contain any amount of emotion -- only one, several, or none at all. The texts with None emotions are the ones where the labels per emotions classes are 0.
Binary: specifically this dataset contains binary labels… See the full description on the dataset page: https://huggingface.co/datasets/ukr-detect/ukr-emotions-binary.Visual_Emotional_AnalysisEmotion.Intelligencefacial_emotion_detection_dataset
Face Emotion Classification Dataset
This dataset contain about 35000 images which are belongs to 7 classes. This dataset can be used to train deep learning models for human emotion classification problems.
facial_emotion_images
Facial Emotion Images
Dataset Summary
facial_emotion_images contains 15,109 grayscale facial images categorized into four distinct facial expressions: happy, neutral, sad, and surprise. It is structured for image classification and emotion recognition tasks.
Dataset Structure
Data Fields
image: PIL Image object containing the cropped face photo.
label: Class label corresponding to the emotion expression.
Class Labels &… See the full description on the dataset page: https://huggingface.co/datasets/gabriellidenor/facial_emotion_images.EmotionClassHuman-Face_Images_for_Emotion_Recognitionukr-emotions-intensity
EmoBench-UA: Emotions Detection Dataset in Ukrainian Texts
EmoBench-UA: the first of its kind emotions detection dataset in Ukrainian texts. This dataset covers the detection of basic emotions: Joy, Anger, Fear, Disgust, Surprise, Sadness, or None.
Any text can contain any amount of emotion -- only one, several, or none at all. The texts with None emotions are the ones where the labels per emotions classes are 0.
Intensity: specifically this dataset contains intensity labels… See the full description on the dataset page: https://huggingface.co/datasets/ukr-detect/ukr-emotions-intensity.Dog_Emotion_Dataset_v2
Dataset Card for "Dog_Emotion_Dataset_v2"
The Dataset is based on a kaggle dataset
Label and its Meaning
0 : sad"
1 : angry"
2 : relaxed"
3 : happy"
ZJU-Children-Emotion
ZJU Children Emotion Dataset
Dataset Description
ZJU Children Emotion Dataset (ZCED) is a multi-modal multi-group children emotion dataset aimed for the research of disease classification and emotion recognition in children with neurodevelopmental disorders.
The ZCED dataset contains both behavioral and physiological recordings based on a video-based emotional stimulation paradigm for four groups of children including 19 TD, 15 ASD, 20 ADHD, and 18 ASD+ADHD.
Data are… See the full description on the dataset page: https://huggingface.co/datasets/Jiaheng-Wang/ZJU-Children-Emotion.emotion_bias
Emotion Bias in Synthetic Face Generation
Description
This dataset accompanies the paper "Happy Young Women, Grumpy Old Men? Emotion Prompts as Demographic Selectors in AI Image Generation".
It contains 56,000 synthetic face images generated by eight state-of-the-art text-to-image (T2I) models across seven emotion prompt conditions, along with demographic attribute annotations (gender, race, age) and perceived attractiveness labels for each image.
The dataset is designed… See the full description on the dataset page: https://huggingface.co/datasets/mengtingwei/emotion_bias.emotion_detectionFace-Emotion-DetectionEmotionsemotion-prediction-comet-atomic-2020
emotion-prediction-comet-atomic-2020
This dataset extends the COMET-Atomic-2020 commonsense reasoning dataset by focusing on the xReact (subject’s emotional reaction) and oReact (other person’s emotional reaction) relations.
Description
Each entry is expanded into a realistic, three‑sentence scenario, replacing the placeholders (PersonX/PersonY) with human names and adding contextual details.
Source (comet-atomic-2020) Example:
source
relation
target
PersonX… See the full description on the dataset page: https://huggingface.co/datasets/id4thomas/emotion-prediction-comet-atomic-2020.yolo-emotionsA merged emotions dataset was created using a highly curated subset of ExpW, FER2013 (enhanced with FER2013+), AffectNet (6 emotions), and RAF-DB in YOLO format, totaling approximately 155K samples. A YOLOv11-x model, fine-tuned on the WiderFace dataset for the bounding boxes, was used. The distribution is as follows:
TRAIN Set Class Distribution:
Class 0 (Angry): 8511 (6.84%)
Class 1 (Disgust): 6307 (5.07%)
Class 2 (Fear): 4249 (3.41%)
Class 3 (Happy): 37714 (30.30%)
Class 4… See the full description on the dataset page: https://huggingface.co/datasets/AdamCodd/yolo-emotions.gpt4v-emotion-dataset
Dataset Card for "gpt4v-emotion-dataset"
More Information needed
emotional_imagesHuman-Group-Emotions-LabelledImages of manually annotated groups of human faces + emotions (1) per face ("Angry", "Disgust","Fear", "Happy", "Sad", "Surprise", "Neutral").
Dataset consists of 162 JPEG images.
Annotated using https://labelstud.io/, using their Object detection + Labeling template.
new_emotion_image_embeddings_DFemotion-neural-weights-2026-18356-N128emotionhuman_face_emotions_roboflowRoboflows-emotion-datasetEmotion6_2step