---
title: "Makeup Detection Dataset: Female Images"
description: "Makeup dataset including 5,000 paired JPG facial images (2,500 subjects) of women with and without makeup, captured using diverse devices and lighting conditions. Each image…"
url: "https://unidata.pro/datasets/makeup-detection-dataset-female-images/"
date_modified: "2025-11-27T20:00:02+03:00"
language: "en-US"
---
Makeup dataset including 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.

## Dataset Structure

### The Numbers Section

**Numbered list:**

- **Number:** 5,000 — **Text:** images
- **Number:** 2,500 — **Text:** people

### Tooltips Section

**Tooltip items:**

- **Name:** Computer Vision
- **Name:** Machine Learning
- **Name:** Facial Recognition
- **Name:** Makeup Detection

### Dataset Information

**Table with data:**

| 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 |

**Media Slider:**

- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2025/08/makeup-detection-dataset-female-images0a-primerfoto2-scaled.webp)
- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2025/08/makeup-detection-dataset-female-images0a-primerfoto1-scaled.webp)

**Link to the sample:** [Download sample](https://drive.google.com/drive/folders/1yb39Spegxawss79BIwqKXPZ1KXCgAry8?usp=sharing)

### Statistics - Charts

**Charts with Titles:**

- **Diagram:** ![](https://unidata.pro/wp-content/uploads/2025/08/makeup-detection-dataset-female-images0a-image1.webp) — **caption above the graph:** Distribution by country
- **Diagram:** ![](https://unidata.pro/wp-content/uploads/2025/08/makeup-detection-dataset-female-images0a-image2.webp) — **caption above the graph:** Distribution by gender

### Technical Specifications

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Image extension | JPG |

**Source and data collection methodology:** Source and collection methodology: Data was collected via crowdsourcing platforms.

### Dataset Use Cases - Slider

**Industry Cards:**

- **Industry:** Beauty Technology — **Title:** Training AI for Makeup Detection — **Text:** 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.
- **Industry:** Facial Recognition Research — **Title:** Improving Recognition Accuracy Across Makeup Variations — **Text:** 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.
- **Industry:** Cosmetics Industry — **Title:** Developing Virtual Try-On and Makeup Transfer Tools — **Text:** 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.
- **Industry:** AI Ethics and Bias Studies — **Title:** Evaluating Fairness in Facial Recognition Systems — **Text:** 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.

### Fact

**FAQs Heading:** FAQs

**List of Questions:**

- **Question:** Can I request a sample of the dataset before purchasing? — **Answer:** 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.
- **Question:** How was the data collected? — **Answer:** 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.
- **Question:** How are Unidata datasets licensed? — **Answer:** 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.
- **Question:** Do Unidata datasets follow GDPR or other data privacy regulations? — **Answer:** 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.
- **Question:** How are Unidata datasets stored? — **Answer:** 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.
- **Question:** How long does it take to receive the dataset? — **Answer:** 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.
- **Question:** Is this real-world or synthetic data? — **Answer:** 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.
- **Question:** Why are paired images important for makeup detection research? — **Answer:** Paired images allow AI models to compare the same individual before and after makeup application without introducing identity-related differences. This makes it easier to isolate cosmetic changes and improve model performance.
- **Question:** Why is demographic metadata valuable for makeup detection models? — **Answer:** Metadata such as age, country, gender, and device model allows researchers to evaluate model performance across different user groups and image capture conditions. This helps develop fairer and more robust AI systems.

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