front_img
image
| selfie_img
image
| side_img
image
| arm_circumference_cm
string
| arm_length_cm
string
| back_build_cm
string
| calf_circumference_cm
string
| chest_circumference_cm
string
| crotch_height_cm
string
| front_build_cm
string
| hips_circumference_cm
string
| leg_length_cm
string
| neck_circumference_cm
string
| neck_pelvis_length_front_cm
string
| neck_waist_length_back_cm
string
| neck_waist_length_front_cm
string
| pelvis_circumference_cm
string
| shoulder_length_cm
string
| shoulder_width_cm
string
| thigh_circumference_cm
string
| under_chest_circumference_cm
string
| upper_arm_length_cm
string
| waist_circumference_cm
string
| height
string
| weight
string
| age
string
| gender
string
| race
string
| profession
string
| arm_circumference
image
| arm_length
image
| back_build
image
| calf_circumference
image
| chest_circumference
image
| crotch_height
image
| front_build
image
| hips_circumference
image
| leg_length
image
| neck_circumference
image
| neck_pelvis_length_front
image
| neck_waist_length_back
image
| neck_waist_length_front
image
| pelvis_circumference
image
| shoulder_length
image
| shoulder_width
image
| thigh_circumference
image
| under_chest_circumference
image
| upper_arm_length
image
| waist_circumference
image
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
 |  |  | "24.0" | "55.0" | "33.0" | "34.0" | "79.0" | "77.0" | "31.0" | "70.0_tbr" | "95.0" | "33.0" | "54.0" | "41.0" | "44.0" | "88.0" | "14.0" | "40.0" | "49.0" | "71.0" | "29.0" | "68.0" | "159.0" | "49.0" | "34" | "female" | "latino" | "Employees" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "27.0" | "55.0" | "33.0" | "36.0" | "93.0" | "73.0_tbr" | "30.0_tbr" | "100.0" | "90.0_tbr" | "34.0" | "57.0_tbr" | "40.0_tbr" | "46.0_tbr" | "106.0" | "16.0_tbr" | "44.0_tbr" | "61.0" | "79.0" | "28.0_tbr" | "79.0" | "157.0" | "64.0" | "33" | "female" | "latino" | "Executives" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "29.0_tbr" | "64.0_tbr" | "39.0" | "38.0_tbr" | "112.0_tbr" | "85.0_tbr" | "32.0_tbr" | "98.0_tbr" | "103.0_tbr" | "36.0_tbr" | "60.0_tbr" | "46.0_tbr" | "43.0_tbr" | "113.0_tbr" | "15.0_tbr" | "42.0_tbr" | "48.0_tbr" | "87.0_tbr" | "27.0" | "88.0_tbr" | "163.0" | "78.0" | "16" | "male" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "25.0" | "55.0" | "32.0" | "34.0" | "86.0" | "68.0_tbr" | "27.0" | "84.0" | "88.0" | "35.0" | "58.0" | "41.0" | "42.0" | "88.0_tbr" | "13.0" | "15.0_tbr" | "55.0" | "75.0" | "28.0_tbr" | "65.0" | "163.0" | "53.0" | "23" | "female" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "25.0" | "55.0" | "36.0" | "34.0" | "90.0" | "79.0" | "32.0_tbr" | "76.0" | "102.0" | "36.0" | "57.0" | "38.0" | "46.0_tbr" | "101.0" | "13.0" | "38.0" | "56.0" | "79.0" | "29.0" | "73.0" | "165.0" | "60.0" | "37" | "female" | "caucasian" | "Executives" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "32.0_tbr" | "60.0_tbr" | "41.0_tbr" | "34.0_tbr" | "105.0_tbr" | "80.0_tbr" | "33.0_tbr" | "102.0_tbr" | "86.0_tbr" | "38.0_tbr" | "65.0_tbr" | "50.0_tbr" | "55.0_tbr" | "103.0_tbr" | "10.0_tbr" | "41.0_tbr" | "52.0_tbr" | "94.0_tbr" | "33.0_tbr" | "102.0_tbr" | "155.0" | "99.0" | "34" | "male" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "25.0" | "58.0" | "36.0" | "33.0" | "86.0_tbr" | "80.0_tbr" | "34.0_tbr" | "80.0" | "96.0_tbr" | "31.0" | "56.0_tbr" | "41.0_tbr" | "41.0_tbr" | "96.0" | "15.0" | "42.0_tbr" | "55.0" | "72.0" | "30.0" | "77.0" | "172.0" | "58.0" | "36" | "female" | "black" | "Employees" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "34.0_tbr" | "60.0_tbr" | "40.0" | "38.0_tbr" | "103.0_tbr" | "66.0_tbr" | "38.0_tbr" | "99.0_tbr" | "95.0_tbr" | "43.0_tbr" | "65.0_tbr" | "53.0" | "55.0_tbr" | "101.0_tbr" | "20.0" | "40.0_tbr" | "54.0_tbr" | "95.0_tbr" | "30.0" | "101.0_tbr" | "168.0" | "76.0" | "39" | "male" | "indian" | "Intermediate_prof" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "32.0_tbr" | "58.0_tbr" | "42.0" | "39.0" | "107.0" | "75.0" | "42.0" | "93.0" | "90.0_tbr" | "41.0" | "65.0_tbr" | "45.0" | "48.0_tbr" | "103.0" | "20.0" | "46.0_tbr" | "56.0" | "99.0" | "35.0" | "92.0" | "175.0" | "80.0" | "28" | "male" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "27.0" | "59.0" | "34.0" | "35.0" | "90.0" | "81.0_tbr" | "31.0_tbr" | "90.0" | "91.0_tbr" | "30.0" | "56.0_tbr" | "42.0_tbr" | "53.0_tbr" | "102.0" | "15.0_tbr" | "44.0_tbr" | "56.0" | "85.0" | "29.0" | "73.0_tbr" | "170.0" | "61.0" | "29" | "female" | "caucasian" | "Manual" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "33.0" | "64.0" | "39.0" | "42.0" | "110.0" | "79.0" | "48.0_tbr" | "50.0_tbr" | "110.0" | "43.0" | "67.0_tbr" | "50.0" | "54.0_tbr" | "111.0" | "15.0" | "39.0" | "61.0" | "102.0" | "31.0" | "99.0" | "190.0" | "100.0" | "42" | "male" | "caucasian" | "Executives" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "26.0" | "66.0" | "36.0" | "34.0" | "90.0" | "80.0" | "39.0" | "84.0" | "105.0" | "34.0" | "69.0" | "49.0" | "45.0" | "92.0" | "15.0" | "41.0" | "48.0" | "78.0" | "32.0" | "70.0" | "176.0" | "60.0" | "18" | "male" | "black" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "34.0" | "57.0" | "40.0" | "37.0" | "103.0" | "74.0_tbr" | "32.0_tbr" | "95.0" | "99.0" | "40.0" | "55.0_tbr" | "31.0_tbr" | "40.0_tbr" | "100.0" | "16.0" | "46.0_tbr" | "60.0" | "95.0" | "30.0" | "93.0_tbr" | "165.0" | "78.0" | "32" | "male" | "indian" | "Farmers" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "32.0" | "65.0_tbr" | "38.0" | "33.0" | "93.0" | "79.0" | "41.0_tbr" | "86.0" | "108.0" | "37.0" | "65.0" | "50.0" | "49.0" | "92.0" | "17.0" | "42.0" | "49.0" | "84.0" | "29.0" | "84.0" | "172.0" | "70.0" | "42" | "male" | "black" | "Intermediate_prof" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "23.0_tbr" | "62.0_tbr" | "30.0_tbr" | "28.0" | "80.0" | "72.0" | "28.0_tbr" | "70.0" | "95.0" | "34.0" | "57.0" | "42.0" | "49.0" | "74.0" | "14.0_tbr" | "37.0" | "42.0" | "74.0" | "29.0_tbr" | "63.0" | "152.0" | "43.0" | "19" | "male" | "indian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "29.0" | "60.0" | "44.0" | "40.0" | "108.0" | "74.0" | "42.0" | "98.0" | "96.0" | "42.0" | "72.0" | "40.0" | "53.0" | "104.0" | "17.0" | "45.0" | "61.0" | "101.0" | "31.0" | "98.0_tbr" | "176.0" | "83.0" | "23" | "male" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "34.0" | "51.0" | "36.0" | "47.0" | "104.0" | "71.0" | "38.0" | "110.0" | "91.0" | "36.0" | "60.0_tbr" | "42.0" | "49.0" | "133.0" | "15.0" | "44.0_tbr" | "68.0" | "92.0" | "26.0" | "91.0_tbr" | "159.0" | "89.0" | "55" | "female" | "caucasian" | "Employees" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "26.0" | "52.0" | "35.0" | "36.0" | "85.0" | "71.0" | "30.0_tbr" | "71.0" | "92.0" | "32.0" | "55.0" | "34.0" | "43.0" | "92.0" | "13.0_tbr" | "35.0" | "54.0" | "76.0" | "28.0" | "69.0" | "155.0" | "54.0" | "18" | "female" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "27.0_tbr" | "54.0" | "34.0" | "34.0_tbr" | "84.0" | "76.0_tbr" | "34.0_tbr" | "78.0_tbr" | "91.0_tbr" | "34.0" | "54.0" | "37.0_tbr" | "36.0_tbr" | "92.0" | "15.0" | "40.0_tbr" | "52.0_tbr" | "74.0_tbr" | "26.0" | "73.0_tbr" | "161.0" | "55.0" | "13" | "male" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "24.0_tbr" | "54.0" | "34.0" | "36.0" | "81.0" | "82.0" | "31.0" | "84.0" | "92.0" | "32.0" | "55.0" | "42.0" | "48.0_tbr" | "93.0" | "15.0" | "40.0_tbr" | "53.0" | "71.0" | "29.0" | "69.0" | "167.0" | "55.0" | "18" | "female" | "caucasian" | "Others" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
 |  |  | "31.0_tbr" | "63.0" | "45.0" | "34.0" | "101.0" | "80.0" | "39.0" | "91.0" | "96.0" | "40.0" | "64.0_tbr" | "53.0_tbr" | "53.0" | "100.0" | "21.0_tbr" | "45.0_tbr" | "54.0" | "99.0" | "29.0_tbr" | "86.0" | "165.0" | "75.0" | "30" | "male" | "black" | "Farmers" |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |
Body Measurements Dataset
The dataset consists of a compilation of people's photos along with their corresponding body measurements. It is designed to provide information and insights into the physical appearances and body characteristics of individuals. The dataset includes a diverse range of subjects representing different age groups, genders, and ethnicities.
The photos are captured in a standardized manner, depicting individuals in a front and side positions. The images aim to capture the subjects' physical appearance using appropriate lighting and angles that showcase their body proportions accurately.
The dataset serves various purposes, including:
- research projects
- body measurement analysis
- fashion or apparel industry applications
- fitness and wellness studies
- anthropometric studies for ergonomic design in various fields
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Get the dataset
This is just an example of the data
Leave a request on https://trainingdata.pro/data-market to discuss your requirements, learn about the price and buy the dataset.
Content
Folders
- files: includes folders with photos and measurements of people
- proofs: contains subfolders, corresponding to the original photos in
filesfolder and includes additional photos of people taking measurements - .pdf file: includes information about photos in
proofsfolder
"Files" folder includes 3 images of a person and json file with measurements:
- selfie - the person is looking to the camera; face, neck and shoulders are clearly seen,
- front photo - the person stands in front of the camera, all body parts are clearly seen,
- side photo - the person turned sideways to the camera, all body parts are clearly seen
- json file - includes 22 measurements (weight, height, hips circumference, leg length etc.) and 4 additional characteristics (age, gender, race, profession) of a person, depicted in photos in the subfolder
File with the extension .csv
includes the following information for each media file:
- selfie: link to the selfie,
- front: link to the front photo,
- side: link to the side photo,
- measurements: link to the json file with measurements
Body Measurements might be collected in accordance with your requirements.
**TrainingData**
More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets
TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets
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