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Face Segmentation Dataset – 70,846 Human Face Images for AI Training

face segmentation dataset
human face dataset
facial segmentation images
annotated face dataset
semantic segmentation dataset
AI training data for face segmentation
deep learning face dataset
computer vision human face data

This Human Face Segmentation Dataset contains 70,846 high-quality images featuring diverse subjects with pixel-level annotations. The dataset includes individuals across various age groups—from young children to the elderly—and represents multiple ethnicities, including Asian, Black, and Caucasian. Both males and females are included. The scenes range from indoor to outdoor environments, with pure-color backgrounds also present. Facial expressions vary from neutral to complex, including large-angle head tilts, eye closures, glowers, puckers, open mouths, and more. Each image is precisely annotated on a pixel-by-pixel basis, covering facial regions, five sense organs, body parts, and appendages. This dataset is ideal for applications such as facial recognition, segmentation, and other computer vision tasks involving human face parsing.

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SpecificationsSpecifications
Data size
70,846 images, there is only one face in an image
Population distribution
race distribution: 32,235 images of Asian, 29,501 images of Caucasian, 9,110 images of black race; gender distribution: 34,044 male images and 36,802 female images; age distribution: baby, teenager, young, midlife and senior
Collection environment
including pure color background, indoor scenes and outdoor scenes
Data diversity
multiple scenes, multiple ages, multiple races, complicated expressions (closing eye, glower, pucker, opening mouth, etc.), and multiple appendages
Image Parameter
Data format: the image data is in .jpg or .png format, the annotation file is in .json or .psd format; the human face resolution is not lower than 128*128, and pupillary distance is not less than 60 pixels
Annotation content
segmentation annotation of human face, the five sense organs, body and appendages
Accuracy
the mask edge location errors in x and y directions are less than 3 pixels, which is considered as a qualified annotation; the annotation part (id) is regarded as the unit, the accuracy rate of segmentation annotation shall be more than 97%
Sample Sample
  • Face Segmentation Dataset – 70,846 Human Face Images for AI Training
  • Face Segmentation Dataset – 70,846 Human Face Images for AI Training
  • Face Segmentation Dataset – 70,846 Human Face Images for AI Training
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