Facial Emotion Recognition is a dataset for facial emotion classification tasks, designed to be used for training and evaluating various emotion recognition models.

This dataset covers seven basic emotions: anger, disgust, fear, happiness, neutrality, sadness, and surprise. The data is based on and integrated from the publicly available FER2013 and RAF-DB datasets. Face images were filtered using HaarCascade (approximately 0.8 confidence level) for denoising and quality enhancement. Grayscale images from FER2013 were also uniformly converted to RGB to ensure data consistency. It should be noted that the sample size for each emotion category is imbalanced; resampling or weighting strategies may be necessary during training.