Datasets:

bareethul
/

outfit-image-dataset

dataset_info:
  features:
    - name: Formality
      dtype: string
    - name: is winter wearable?
      dtype: int64
    - name: image
      dtype: image
  splits:
    - name: original
      num_bytes: 255235
      num_examples: 30
    - name: augmented
      num_bytes: 20565829
      num_examples: 300
  download_size: 20814911
  dataset_size: 20821064
configs:
  - config_name: default
    data_files:
      - split: original
        path: data/original-*
      - split: augmented
        path: data/augmented-*
license: cc
task_categories:
  - image-classification
language:
  - en
tags:
  - computervision
  - clothing
  - outfits
  - winterwear
  - education
pretty_name: Outfit Combos (Winter Wearability)
size_categories:
  - n<1K

Dataset Card for Outfit Dataset

This dataset card documents the Clothing Outfit Dataset.
It contains 30 original outfit images (shirt-pant combinations) with categorical and binary labels, with an augmented split expanding to 300 images.

Dataset Details

Dataset Description

Curated by: Bareethul Kader (Carnegie Mellon University)
Language(s): English (labels: formality, binary target)
License: CC BY 4.0
Repository: bareethul/clothing-outfits

Uses

Direct Use

Educational practice in computer vision dataset creation and augmentation.
Binary classification task: predict whether an outfit is wearable in winter with a jacket.
Multi-class classification: predict outfit formality (Casual, Semi-Formal, Formal).

Out-of-Scope Use

Not intended for fashion recommendations or e-commerce applications.
Images represent a limited personal wardrobe, not generalizable fashion data.

Dataset Structure

Original split: 30 manually captured outfit images (shirt–pant combos).
Augmented split: 300 images generated with torchvision transforms (random crop, flip, rotation, color jitter, etc.).

Features:

Image (224×224 JPG, RGB)
Formality (categorical: Casual, Semi-Formal, Formal)
is_winter_wearable (binary target: 1 = yes, 0 = no)

Dataset Creation

Curation Rationale
To study how outfit images can be labeled for seasonal wearability and formality classification in a simplified educational dataset.

Data Collection and Processing

Original images manually photographed by the dataset creator (shirt–pant combos).
Images resized to 224×224 pixels for consistency.
Binary label is_winter_wearable assigned based on whether the outfit could be worn in winter with a jacket.
Augmentation applied using PyTorch/Torchvision (random flips, rotations, color jitter, erasing, etc.).

Source Data Producers

Original producer: Bareethul Kader (personal clothing images).
Dataset curated solely for educational purposes.

Annotations

Annotation Process:
- Formality labeled manually by the creator (Casual, Semi-Formal, Formal).
- is_winter_wearable labeled based on personal judgment.
Annotators: Dataset creator.

Personal and Sensitive Information

No faces, people, or identifying information included.
Only images of inanimate clothing items.

Bias, Risks, and Limitations

Small dataset (30 images) — not representative of all outfit styles.
Subjective labels (formality, is_winter_wearable) may reflect individual judgment, not universal agreement.
Augmentation may create visually unrealistic variants.

Recommendations

Users should be aware of the limited scope and subjectivity of this dataset.
It is intended only for educational demonstrations of image dataset creation and augmentation.

Citation

BibTeX:

@dataset{bareethul_clothing_outfits,
  author       = {Kader, Bareethul},
  title        = {Clothing Outfit Dataset},
  year         = {2025},
  publisher    = {Hugging Face Datasets},
  url          = {https://huggingface.co/datasets/bareethul/clothing-outfits}
}