task_categories:image-classification task_categories:image-to-image language:en license:cc-by-nc-nd-4.0 code region:us
The dataset consists of images capturing people displaying 7 distinct emotions
(anger, contempt, disgust, fear, happiness, sadness and surprise).
Each image in the dataset represents one of these specific emotions,
enabling researchers and machine learning practitioners to study and develop
models for emotion recognition and analysis.
The images encompass a diverse range of individuals, including different
genders, ethnicities, and age groups*. The dataset aims to provide
a comprehensive representation of human emotions, allowing for a wide range of
use cases.
@InProceedings{huggingface:dataset,
title = {facial-emotion-recognition-dataset},
author = {TrainingDataPro},
year = {2023}
}
---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
- image-to-image
tags:
- code
dataset_info:
  features:
  - name: set_id
    dtype: int32
  - name: neutral
    dtype: image
  - name: anger
    dtype: image
  - name: contempt
    dtype: image
  - name: disgust
    dtype: image
  - name: fear
    dtype: image
  - name: happy
    dtype: image
  - name: sad
    dtype: image
  - name: surprised
    dtype: image
  - name: age
    dtype: int8
  - name: gender
    dtype: string
  - name: country
    dtype: string
  splits:
  - name: train
    num_bytes: 22981
    num_examples: 19
  download_size: 453786356
  dataset_size: 22981
---
# Facial Emotion Recognition Dataset

The dataset consists of images capturing people displaying **7 distinct emotions** (*anger, contempt, disgust, fear, happiness, sadness and surprise*). Each image in the dataset represents one of these specific emotions, enabling researchers and machine learning practitioners to study and develop models for emotion recognition and analysis.

The images encompass a diverse range of individuals, including different *genders, ethnicities, and age groups*. The dataset aims to provide a comprehensive representation of human emotions, allowing for a wide range of use cases.

### The dataset's possible applications:
- automatic emotion detection
- mental health analysis
- artificial intelligence (AI) and computer vision
- entertainment industries
- advertising and market research
- security and surveillance

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F618942%2Fe72fc2820f1452bcdc99b4bc69e4c7b0%2FMacBook%20Air%20-%201.png?generation=1689578335866939&alt=media)

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=facial-emotion-recognition-dataset) to discuss your requirements, learn about the price and buy the dataset.

# Content

- **images**: includes folders corresponding to people and containing images with 8 different impersonated emotions, each file is named according to the expressed emotion
- **.csv** file: contains information about people in the dataset

### Emotions in the dataset:
- anger
- contempt
- disgust
- fear
- happy
- sad
- surprised


### File with the extension .csv

includes the following information for each set of media files:

- **set_id**: id of the set of images,
- **gender**: gender of the person, 
- **age**: age of the person,
- **country**: country of the person

# Images for facial emotion recognition might be collected in accordance with your requirements.

## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=facial-emotion-recognition-dataset) provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**