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Legs Segmentation
Case
A dataset for training a neural network in the tasks of segmenting parts of the legs using original photographs and corresponding masks with segmentation
Кейс Сегментация ног
Computer Vision
The ability to recognize and analyze images and video
E - Commerce
Using machine learning in online trading
Segmentation
Разделение изображения на семантически независимые сегменты для определения границ объектов
Data Labeling
Highlighting objects in photos for training the system to recognize and interpret them
5 000
photos
2 weeks
project duration
Case Description
Collection of foot photographs through crowdsourcing platforms
Segmentation: foot and the rest of the leg
The dataset consists of two folders:
Data were collected on international crowdsourcing platforms and by an internal team of AI trainers. The collection rate is estimated at 25,000 photographs per month
LABELING AND METADATA
Segmentation into two classes: the foot and the rest of the leg
0 - heel
1 - big toe
2 - Achilles
3 - bone beneath little toe
4 - bone beneath the big toe
5 - end of heel (side)
6 - bottom of the shin (straight line from points 5 and 12 up)
1 - big toe
2 - Achilles
3 - bone beneath little toe
4 - bone beneath the big toe
5 - end of heel (side)
6 - bottom of the shin (straight line from points 5 and 12 up)
7 - top of foot arch
8 - 2nd toe
9 - middle toe
10 - 4th toe
11 - pinky toe
12 - ankle
13 - inside of leg above the ankle
8 - 2nd toe
9 - middle toe
10 - 4th toe
11 - pinky toe
12 - ankle
13 - inside of leg above the ankle
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THE FINAL COST OF THE PROJECT IS INFLUENCED BY:
Scope of work
Markup complexity
Timing
Markup quality
Our data quality guarantee is 95%. When ordering markup with quality above 95%, we offer enterprise solutions
APPLICATION AREAS OF THE DATASET
Medicine:
Computer Vision for analysis and diagnosis of various diseases of the foot and shin, determining wounds, ulcers, pressure sores, and other problems related to the foot
/01
Training and Education:
Segmentation for teaching students and medical professionals to analyze and diagnose foot-related problems
/03
E-commerce
Visualization and Animation:
Segmentation and computer vision for automatic shoe size determination and selection of suitable products for customers
Segmentation and Keypoint labeling for use in computer graphics and animation to create realistic models of the foot and its movements
/04
/02
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