Hair Detection & Segmentation Dataset

The dataset consists of images of people for detection and segmentation of hairs within the oval region of the face. It primarily focuses on identifying the presence of hair strands within the facial area and accurately segmenting them for further analysis or applications.

The dataset contains a diverse collection of images depicting people with different hair styles, colors, lengths, and textures. Each image is annotated with annotations that indicate the boundaries and contours of the individual hair strands within the oval of the face.

💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on TrainingData to buy the dataset

The dataset can be utilized for various purposes, such as developing machine learning models or algorithms for hair detection and segmentation. It can also be used for research in facial recognition, virtual try-on applications, hairstyle recommendation systems, and other related areas.

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• Bald People Segmentation Dataset
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• Selfies, ID Images dataset (5591 sets of 15 files)
• Face segmentation

Dataset structure

• images - contains of original images of people
• masks - includes segmentation masks for the original images
• collages - includes original images with colored hairs within the oval of the face
• annotations.xml - contains coordinates of the bounding boxes and labels, created for the original photo

Data Format

Each image from images folder is accompanied by an XML-annotation in the annotations.xml file indicating the coordinates of the bounding boxes and labels for parking spaces. For each point, the x and y coordinates are provided.

Tags for the images:

• is_hair - hair area
• no_hair - area of no hair

Example of XML file structure

Hair Detection & Segmentation might be made in accordance with your requirements.

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset

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