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Home > All Category Datasets > Computer Vision Datasets > Facial Skin Defects Dataset – 7,262 Images with Acne, Moles, Scars, and Freckles

Facial Skin Defects Dataset – 7,262 Images with Acne, Moles, Scars, and Freckles

facial skin defects dataset

acne detection dataset

skin disease dataset

facial skin dataset

dermatology AI dataset

mole detection dataset

scar detection dataset

freckles detection dataset

This dataset contains 7,262 facial images with 2,499,771 annotated boxes. The data includes the following seven types of facial skin defects: acne, moles, scars, herpes (sores), speckles, freckles, and others. This data can be used for tasks such as skin defects detection, dermatology AI, and medical image analysis.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Specifications

Data size

2,499,771 boxes 7,262 images (one image per person)

Race (Country) distribution

1597 people of Asian（excluding Chinese people）, 2075 people of Caucasian, 1756 people of Black, 109 people of Brown, 1739 people of Indian

Gender distribution

3812 males, 3450 females

Age distribution

multi-age

Skin defects

acne, moles, scars, herpes (sores), speckles, freckles, and others

Collecting environment

including indoor and outdoor scenes

Data diversity

different skin defects, countries, ages and scenes

Device

cellphone

Data format

.jpg, json

Sample

Sample

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What types of computer vision applications can Nexdata’s datasets support?

Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.

Can Nexdata customize Computer Vision datasets based on our specific requirements?

Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.

How does Nexdata ensure the quality and scalability of its Computer Vision datasets?

Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.

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