Commercial

Makeup Detection Dataset: Female Images

Makeup Detection Dataset: Female Images includes 5,000 paired JPG facial images (2,500 subjects) of women with and without makeup, captured using diverse devices and lighting conditions. Each image is annotated with metadata (ID, gender, age, country, device model), making it ideal for facial recognition, makeup detection, and training computer vision models.

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  • images
    5,000
  • people
    2,500
  • Computer Vision
  • Machine Learning
  • Facial Recognition
  • Makeup Detection

Makeup Detection Dataset: Female Images includes 5,000 paired JPG facial images (2,500 subjects) of women with and without makeup, captured using diverse devices and lighting conditions. Each image is annotated with metadata (ID, gender, age, country, device model), making it ideal for facial recognition, makeup detection, and training computer vision models.

Get in touch Download sample
  • Computer Vision
  • Machine Learning
  • Facial Recognition
  • Makeup Detection
  • images
    5,000
  • people
    2,500

Dataset Info

Characteristic Data
Description Paired facial images of females with and without makeup
Data types Image
Tasks Beauty AI, Computer Vision
Number of people 2,500
Number of files in a set 2 images per person
Total number of files 5,000
Labeling Metadata (ID, gender, age, country, device model)
Gender Male, Female
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Statistics

Distribution by country
Distribution by gender

Technical
Characteristics

Characteristic Data
Image extension JPG
Source and collection methodology: Data was collected via crowdsourcing platforms.

Dataset Use Cases

  • Beauty Technology

    Training AI for Makeup Detection

    This facial makeup dataset provides paired images of female faces with and without makeup, enabling deep learning models to identify makeup presence under real-world conditions. The high-quality photos capture variations in lighting, facial features, and makeup styles, helping AI systems analyze facial appearance and support beauty tech applications such as virtual skin tone analysis and product recommendation systems.

  • Facial Recognition Research

    Improving Recognition Accuracy Across Makeup Variations

    Facial recognition algorithms often struggle when appearance changes due to heavy or light makeup. This dataset supports model training by offering paired before-and-after images that show makeup’s impact on identity features and facial landmarks. Researchers can use it to enhance detection algorithms, reduce false matches, and improve recognition accuracy in practical verification systems.

  • Cosmetics Industry

    Developing Virtual Try-On and Makeup Transfer Tools

    The facial makeup dataset helps beauty brands and developers build AI-driven virtual try-on applications and makeup transfer models. Containing real-world images of female subjects with different makeup styles, it allows systems to learn color blending, eye makeup patterns, and facial contours, resulting in realistic and personalized virtual cosmetics experiences for users across devices.

  • AI Ethics and Bias Studies

    Evaluating Fairness in Facial Recognition Systems

    This dataset supports ethical AI research by providing diverse female face images with and without makeup. It allows scientists to study how cosmetic variations influence detection accuracy, face matching, and model bias. Using this data, developers can improve fairness and ensure balanced performance across facial recognition and computer vision tasks involving appearance changes.

FAQs

What is included in this dataset?
The dataset consists of 5,000 paired facial images of female subjects, featuring both “makeup” and “no-makeup” versions for each person. Each image includes detailed metadata, such as ID, gender, age, country, and device model, supporting advanced face analysis and AI research.
Can I request a sample of the dataset before purchasing?
Yes. Free dataset samples are available for testing and evaluation. These samples help you assess data quality, diversity, and relevance before committing to a full purchase.
How was the data collected?
The dataset was collected through crowdsourcing platforms, ensuring real-world diversity across different individuals, makeup styles, and lighting conditions. Participants provided paired facial images captured according to controlled guidelines to maintain consistency and balance between makeup and non-makeup samples.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model: free samples are available for testing, while full datasets require purchase for full access and commercial use. This ensures both accessibility for research and protection of dataset integrity.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. All Unidata datasets comply with GDPR and relevant global data protection laws. Data is collected through lawful and ethical means, ensuring the privacy and informed consent of participants.
How are Unidata datasets stored?
All datasets are securely stored on AWS cloud infrastructure, which complies with ISO 27001 and ISO 27701 standards. This ensures data security, privacy, and high availability for all clients and partners.
How long does it take to receive the dataset?
Once you submit a request, our team will contact you to confirm details and complete documentation. After signing and payment, the dataset will be delivered within 3–10 business days.
Is this real-world or synthetic data?
This is a real-world dataset featuring genuine photographs of female subjects captured through verified crowdsourcing. The data reflects natural variations in makeup styles, lighting, and facial expressions - ideal for training robust recognition algorithms.
Still have questions about using Unidata datasets? Read our user-guides

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