Commercial
Women Hair Loss Segmentation Dataset
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
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- Images
- 1 080
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- People
- 540
- Computer Vision
- Medicine
- Classification
- Machine Learning
- Segmentation
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- Images
- 1 080
-
- People
- 540
Dataset Info
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 | 1 080 |
Number of files in a set | 2 images for women (image from the top + mask) |
Total number of people | 540 |
Labeling | Metadata (gender, age, ethnicity) |
Age | Min = 18, max = 80, mean = 45 |
Technical
Characteristics
Characteristic | Data |
Image Extensions | Png, jpeg |
Mask Extension | Png |
Dataset Use Cases
FAQs
What is included in Women Hair Loss Segmentation Dataset?
It consists of 1,080 images from 540 women, each set containing a photo from the top view and a corresponding segmentation mask. Additionally, it includes metadata files with details such as age, gender, and ethnicity, supporting scalp condition analysis and AI training datasets.
What types of annotations are provided?
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.
What age groups are represented in this dataset?
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.
What are the sources of data for this dataset?
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.
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