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  - en
license: cc-by-nc-nd-4.0
  - image-classification
  - image-to-image
  - code
    - 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
    - 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

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This is just an example of the data

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  • 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 provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account:

TrainingData's GitHub:

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