---
title: "Female Hair Loss Dataset"
description: "This hair loss dataset provides alopecia images of women captured from the top and front sides, labeled into three classes based on the Ludwig scale,…"
url: "https://unidata.pro/datasets/hair-loss-female-ludwig-scale/"
date_modified: "2026-03-23T13:40:54+03:00"
language: "en-US"
---
This hair loss dataset provides alopecia images of women captured from the top and front sides, labeled into three classes based on the Ludwig scale, with metadata (age, gender, ethnicity) to support machine learning, deep learning, and AI models for hair loss detection, early diagnosis, and research on hair thinning and scalp health.

## Dataset Structure

### The Numbers Section

**Numbered list:**

- **Number:** 552 — **Text:** Images
- **Number:** 276 — **Text:** People

### Tooltips Section

**Tooltip items:**

- **Name:** Medicine
- **Name:** Classification
- **Name:** Machine Learning
- **Name:** Computer Vision
- **Name:** Data Labeling

### Dataset Information

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Description | Photos of people with varying degrees of hair loss for alopecia classification |
| Data types | Image |
| Tasks | Classification, Machine Learning |
| Number of images | 552 |
| Number of files in a set | 2 images (top and front) and txt file of Ludwig scale |
| Total number of people | 276 |
| Labeling | Metadata (gender, age, ethnicity) |
| Age | Min = 18, max = 80, mean = 45 |

**Media Slider:**

- **Image in the slider:** ![female hair loss dataset](https://unidata.pro/wp-content/uploads/2025/05/front.webp)
- **Image in the slider:** ![female hair loss dataset](https://unidata.pro/wp-content/uploads/2025/05/top-down.webp)

**Link to the sample:** [Download sample](https://drive.google.com/drive/folders/16cUu1Sd_HAdkNKYH3nKhIyxJ5tIomx6p?usp=sharing)

### Technical Specifications

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Image extensions | Png, jpeg |
| Extension of labeling file | txt |

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

### LLM Languages

**Section Title:** Statistics

**List of Statistics:**

- **Filter by:** Age Distribution — **GIF image:** Age Distribution — **Table with data:**

| Age | Count |
| --- | --- |
| Under 18 | 13 |
| 19-25 | 70 |
| 26-32 | 59 |
| 33-39 | 49 |
| 40-46 | 25 |
| 47-53 | 19 |
| 54-59 | 14 |
| 60-66 | 16 |
| 67+ | 11 |

### Statistics - Charts

**Charts with Titles:** - **Shortcode:** [ays_chart id="60"] — **caption above the graph:** Ethnicity Distribution

### Dataset Use Cases - Slider

**Industry Cards:**

- **Industry:** Medical Research & Dermatology — **Title:** Studying Hair Thinning and Scalp Conditions — **Text:** Female Hair Loss Dataset provides valuable medical images that help dermatologists and researchers analyze hair thinning, hair density, and scalp health. With images categorized by the Ludwig scale, specialists can study alopecia areata and other hair disorders, supporting better early detection, diagnosis, and effective treatment planning.
- **Industry:** Machine Learning & AI Development — **Title:** Training Models for Hair Loss Detection — **Text:** This alopecia dataset supports machine learning and deep learning projects focused on detecting hair falling and hair thinning patterns. Models trained on these training datasets can achieve accurate diagnosis of scalp conditions, classify different skin types, and evaluate hair textures, helping researchers improve learning algorithms and medical AI applications.
- **Industry:** Pharmaceutical & Cosmetic Industry — **Title:** Developing Hair Restoration and Care Solutions — **Text:** Pharmaceutical companies and cosmetic brands can use this hair loss dataset to assess the effectiveness of hair restoration products and loss treatments. By analyzing hair follicles, scalp conditions, and natural hairs, this data helps in creating new hair transplants, hair care, and hair growth solutions that target healthier and thicker hair outcomes.
- **Industry:** Education & Clinical Training — **Title:** Supporting Medical Training and Diagnosis Practice — **Text:** Medical schools and training centers apply the bald women dataset to teach students how to recognize hair disorders, scalp diseases, and alopecia stages. The dataset contains diverse human skin and hair textures, enabling future dermatologists to practice diagnosing hair conditions and recommend personalized hair loss treatments with higher precision and reliability.

### Fact

**FAQs Heading:** FAQs

**List of Questions:**

- **Question:** What types of annotations are provided in the dataset? — **Answer:** Annotations include Ludwig scale classification for different stages of hair loss, along with metadata describing subject age, gender, and ethnicity. This helps improve the performance of trained models in early diagnosis and hair density analysis.
- **Question:** What is the image format and file structure? — **Answer:** Female Hair Loss Dataset provides PNG and JPEG image files for compatibility with most computer vision frameworks. Each subject has two images (top and front views) plus a labeling .txt file, ensuring consistency in training sets and segmentation tasks.
- **Question:** How does this dataset support medical research? — **Answer:** The dataset is useful for developing AI systems that assist in diagnosing hair disorders, monitoring scalp conditions, and evaluating hair loss treatments. It enables neural networks and learning models to achieve higher precision in medical imaging and alopecia classification.
- **Question:** Can I request a sample of the dataset before purchasing or downloading it? — **Answer:** Yes, Unidata provides dataset samples upon request. This allows you to evaluate the image quality, metadata structure, and annotation style before investing in the complete hair loss segmentation dataset.
- **Question:** How long does it take to receive Female Hair Loss Dataset? — **Answer:** Once you submit a request, we will reach out to you to review the details and complete the necessary documents. After signing and payment, the dataset will be delivered within 3–10 days.
- **Question:** How long does it take to receive the dataset? — **Answer:** Unidata datasets adhere to a dual licensing model: sample datasets are free to test, while full access is granted only by purchase.
- **Question:** Do Unidata datasets follow GDPR or other data privacy regulations? — **Answer:** Yes. All datasets comply with GDPR and relevant data protection regulations. Information is sourced from lawful channels to guarantee ethical and responsible use.
- **Question:** How is the Ludwig Scale represented in this dataset? — **Answer:** Each participant includes top and front scalp images together with a TXT label indicating the corresponding Ludwig Scale stage. This structure supports machine learning models for female hair loss classification and severity estimation.
- **Question:** Why are both top and front views included? — **Answer:** Different stages of female pattern hair loss become visible from different perspectives. Combining top and frontal images enables AI models to evaluate scalp coverage and hair thinning more reliably.

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