---
title: "Women Hair Loss Segmentation Dataset"
description: "This hair loss dataset features annotated images of women with varying degrees of hair loss, designed for machine learning and deep learning applications focused on…"
url: "https://unidata.pro/datasets/hair-loss-in-women-segmentation-dataset/"
date_modified: "2026-02-03T13:07:41+03:00"
language: "en-US"
---
This hair loss dataset features annotated images of women with varying degrees of hair loss, designed for machine learning and deep learning applications focused on analyzing hair density, scalp conditions, and developing solutions for hair restoration, hair thinning, and alopecia treatment

## Dataset Structure

### The Numbers Section

**Numbered list:**

- **Number:** 108 — **Text:** Images
- **Number:** 54 — **Text:** People

### Tooltips Section

**Tooltip items:**

- **Name:** Computer Vision
- **Name:** Medicine
- **Name:** Classification
- **Name:** Machine Learning
- **Name:** Segmentation

### Dataset Information

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Description | Photos of women with varying degrees of hair loss for segmentation tasks |
| Data types | Image |
| Tasks | Classification, Machine Learning |
| Number of images | 108 |
| Number of files in a set | 2 images for women (image from the top + mask) |
| Total number of people | 54 |
| Labeling | Metadata (gender, age, ethnicity) |
| Age | Min = 18, max = 80, mean = 45 |

**Media Slider:**

- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2025/05/primerfoto1.webp)
- **Image in the slider:** ![](https://unidata.pro/wp-content/uploads/2025/05/primerfoto2.webp)

**Link to the sample:** [Download sample](https://drive.google.com/drive/folders/1qWtWDVZEK92bcoV_Mo4xbn7_fmKdyVbJ?usp=sharing)

### Technical Specifications

**Table with data:**

| Characteristic | Data |
| --- | --- |
| Image Extensions | Png, jpeg |
| Mask Extension | Png |

**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:** Country Distribution — **GIF image:** Country Distribution — **Table with data:**

| Country | COUNTA of country |
| --- | --- |
| RU | 35 |
| MM | 5 |
| UA | 2 |
| PH | 2 |
| BR | 2 |
| VE | 1 |
| TR | 1 |
| NI | 1 |
| NG | 1 |
| IN | 1 |
| CO | 1 |
| BY | 1 |
| BD | 1 |
| Grand Total | 54 |

### Statistics - Charts

**Charts with Titles:** - **Shortcode:** [ays_chart id='61'] — **caption above the graph:** Ethnicity distribution

### Dataset Use Cases - Slider

**Industry Cards:**

- **Industry:** Medical Research & Dermatology — **Title:** Analyzing Hair Loss Patterns in Women — **Text:** Women Hair Loss Dataset provides detailed medical images that help dermatologists study hair thinning, hair density, and scalp conditions. With segmentation masks highlighting affected areas, researchers can track hairs loss progression and evaluate hair loss treatments. This supports early detection of hair disorders and more effective treatment strategies.
- **Industry:** Machine Learning & AI Development — **Title:** Training Models for Hair Loss Segmentation — **Text:** This hair loss segmentation dataset is designed for machine learning and deep learning applications. Containing a carefully annotated bald images dataset, it enables learning models to classify hair textures, measure scalp health, and detect alopecia stages. Models trained with this data achieve accurate diagnosis, helping advance medical AI solutions.
- **Industry:** Pharmaceutical & Cosmetic Industry — **Title:** Developing Hair Restoration and Care Products — **Text:** Cosmetic brands and pharmaceutical companies use the alopecia dataset to evaluate hair restoration products and hair care treatments. By analyzing hair follicles, natural hairs, and scalp health, they design more effective hair transplants, hair growth serums, and thicker hair solutions tailored to different skin types and hair disorders.
- **Industry:** Education & Clinical Training — **Title:** Supporting Training in Dermatology and Diagnosis — **Text:** Medical schools and clinics apply the bald women dataset for teaching students how to identify hair falling, scalp diseases, and alopecia progression. The dataset’s manual segmentation masks allow trainees to practice diagnosing hair conditions, ensuring they gain practical experience in recognizing skin diseases and recommending targeted loss treatments.

### Fact

**FAQs Heading:** FAQs

**List of Questions:**

- **Question:** What types of annotations are provided? — **Answer:** Each image includes a segmentation mask in PNG format that highlights areas of hair thinning or baldness. Metadata annotations cover age, gender, and ethnicity, allowing researchers to study different types of scalp conditions and create models trained with high accuracy.
- **Question:** What age groups are represented in this dataset? — **Answer:** The dataset covers women aged 18 to 80, with an average age of 45 years. This wide age range helps train learning models that can detect hair falling, scalp conditions, and hair density changes across different life stages.
- **Question:** Which AI applications benefit most from this dataset? — **Answer:** The dataset supports semantic segmentation, dermatology AI, treatment monitoring, telemedicine platforms, and computer vision systems that analyze female hair conditions.
- **Question:** What are the sources of data for this dataset? — **Answer:** The images were collected via trusted crowdsourcing platforms with strict quality control measures. All data was ethically sourced, featuring women with different hair loss conditions.
- **Question:** How long does it take to receive the dataset? — **Answer:** Once you submit a request, our team will contact you to review the details and finalize the documents. After signing and payment, Women Hair Loss Segmentation Dataset will be delivered securely within 3–10 days.
- **Question:** Is this a real-world dataset or synthetic data? — **Answer:** This is a real-world dataset. It contains genuine photos of women with varying degrees of hair thinning and alopecia, captured to support hair loss segmentation tasks, scalp condition analysis, and accurate diagnosis of hair disorders.
- **Question:** How are Unidata datasets stored? — **Answer:** Unidata secures datasets on AWS cloud infrastructure, optimized for reliability, growth, and security. Our practices meet ISO 27001 and ISO 27701 requirements, ensuring compliance with international privacy and security management frameworks. This provides customers with peace of mind through safe and trustworthy data handling.
- **Question:** What advantages does segmentation provide over simple hair loss classification? — **Answer:** Segmentation identifies the precise boundaries of hair and scalp regions, enabling quantitative analysis rather than only predicting a hair loss category. This provides richer training data for medical AI and image processing systems.

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