id
uint16
0
29
front
imagewidth (px)
640
4.22k
left_side
imagewidth (px)
640
4.22k
right_side
imagewidth (px)
640
4.22k
type
stringclasses
3 values
0
acne
1
acne
2
acne
3
acne
4
acne
5
acne
6
acne
7
acne
8
acne
9
acne
10
bags
11
bags
12
bags
13
bags
14
bags
15
bags
16
bags
17
bags
18
bags
19
bags
20
redness
21
redness
22
redness
23
redness
24
redness
25
redness
26
redness
27
redness
28
redness
29
redness

Skin Defects Dataset

The dataset contains images of individuals with various skin conditions: acne, skin redness, and bags under the eyes. Each person is represented by 3 images showcasing their specific skin issue. The dataset encompasses diverse demographics, age, ethnicities, and genders.

Types of defects in the dataset: acne, skin redness & bags under the eyes

  • Acne photos: display different severities and types of acne such as whiteheads, blackheads, and cystic acne.
  • Skin redness photos: display individuals with this condition, which may be caused by rosacea or eczema.
  • Bags under the eyes photos: depicts individuals with noticeable bags under their eyes, often associated with lack of sleep, aging, or genetics.

Full version of the dataset includes much more photos of people, leave a request on TrainingData to buy the dataset

The dataset is a valuable resource for researchers, developers, and organizations working at the dermatology, cosmetics and medical sphere to train, evaluate, and fine-tune AI models for real-world applications. It can be applied in various domains like skincare, scientific research and advertising.

Get the Dataset

This is just an example of the data

Leave a request on https://trainingdata.pro/datasets to learn about the price and buy the dataset

Content

The folder files includes:

  • 3 folders with images of people with the conditions mentioned in the name of the folder (acne, skin redness or bags under the eyes)
  • each folder includes sub-folders with 3 images of each person from different angles: front, left side and right side

File with the extension .csv

  • id: id of the person,
  • front: link to access the front photo,
  • left_side: link to access the left side's photo,
  • right_side: link to access the right side's photo,
  • type: type of the defect (acne, skin redness or bags under the eyes)

TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets

TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets

keywords: biometric dataset, face recognition database, face recognition dataset, face detection dataset, facial analysis, dermatology dataset, skin on the face, IGA scale, medical data, whiteheads, blackheads, cystic acne, rosacea, eczema disease dataset, cosmetology, multi-task learning approach, facial acne image dataset, bumps on face, facial skin lesions, skin conditions, skin images, skin characteristics, automatic facial skin defect detection system, human face images, acne marks, stains, skincare, skin problems, skin disease dataset, human images, deep learning, computer vision

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