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README.md

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-license: other
-license_name: kqwln
-license_link: LICENSE
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+---
+license: other
+license_name: kqwln
+license_link: LICENSE
+---
+Facial Expressions for YOLO & ViT – 9 Emotions Dataset
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+Dataset ID: LaurenGurgiolo/9_Facial_Expressions
+Task: Facial Emotion Recognition
+Domain: Computer Vision, Deep Learning, Affective Computing
+Languages: N/A
+License: Refer to original Roboflow Universe sources
+
+Dataset Description
+
+The Facial Expressions for YOLO & ViT – 9 Emotions Dataset is a curated facial emotion recognition dataset derived from the Facial Expressions for YOLO Facial Expression Recognition – 9 Emotions Dataset, originally compiled from multiple high-quality repositories hosted on Roboflow Universe (Rimi, 2025).
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+This dataset has been reorganized and refined to support Vision Transformer (ViT)–based models, in addition to convolutional and YOLO-style pipelines. Specific emotional categories were selectively extracted, grouped, and restructured to ensure compatibility with ViT architectures and image classification workflows.
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+The dataset is intended to support research and experimentation in facial expression analysis across modern deep learning frameworks.
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+Emotion Classes
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+The dataset contains images labeled across nine emotional categories:
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+Angry
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+Disgust
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+Fear
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+Happy
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+Sad
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+Surprise
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+Neutral
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+Contempt
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+Calm
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+(Exact class naming may vary slightly depending on preprocessing and folder structure.)
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+Dataset Sources
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+The original dataset aggregates facial expression images from multiple curated repositories available through Roboflow Universe, selected for image quality, facial visibility, and emotional clarity.
+
+Primary Source:
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+Facial Expressions for YOLO Facial Expression Recognition – 9 Emotions Dataset
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+Roboflow Universe
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+Curated by Rimi (2025)
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+Data Processing & Curation
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+To prepare the dataset for use with Vision Transformer (ViT) models, the following steps were performed:
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+Extraction of images corresponding to selected emotional categories
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+Consolidation of images from multiple Roboflow sources into unified class groups
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+Reorganization of the dataset into a classification-friendly structure
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+Standardization of directory layout for compatibility with Hugging Face datasets and ViT pipelines
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+This restructuring ensures that the dataset can be easily used for image classification tasks without requiring bounding-box annotations.
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+Intended Use
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+This dataset is suitable for:
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+Facial emotion recognition
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+Vision Transformer (ViT) model training and evaluation
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+CNN-based emotion classification
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+Transfer learning experiments
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+Comparative studies between YOLO-based and classification-based emotion recognition pipelines
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+Limitations
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+Images originate from multiple public sources and may vary in lighting, pose, age, ethnicity, and cultural expression.
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+Some emotions may be visually ambiguous or overlapping.
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+Class imbalance may exist depending on the original source distributions.
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+Ethical Considerations
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+Faces are sourced from publicly available datasets.
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+The dataset may contain demographic biases inherent to the original repositories.
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+Users should ensure responsible and ethical use, particularly in sensitive applications.
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+Citations
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+If you use this dataset, please cite:
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+Rimi. (2025). Facial Expressions for YOLO Facial Expression Recognition – 9 Emotions Dataset. Roboflow Universe.
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+Dataset Access
+from datasets import load_dataset
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+dataset = load_dataset("LaurenGurgiolo/9_Facial_Expressions")
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+
+