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Botox Injections (Before & After)
A dataset of photos of individuals with and without Botox for facial classification before and after surgeries
DATASET
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Computer Vision
The ability of a machine to interpret, analyze, and understand visual data
Re-identification
The recognition of the same object in different observations
Classification
The process of recognizing and grouping objects into predefined categories
AR
Machine learning in augmented reality applications
2 000
photos
3 weeks
project duration
Case Description
Collection of photos of individuals obtained through web scraping and crowdsourcing before Botox procedures and after Botox procedures.
Facial classification based on the presence of Botox, with tagging in CVAT. Segmentation for detailed Botox recognition. Involvement of surgeons for expert assessment of facial changes.
The dataset consists of two folders:
View on Kaggle
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APPLICATION AREAS OF THE DATASET
Semantic segmentation of selfies after surgeries to demonstrate expected results of Botox procedures to clients
Cosmetic Industry:
Semantic segmentation and matting of selfies to create advertising masks that visually demonstrate the effects of cosmetic surgeries in real-time
AR:
Crowdsourced evaluations of "before" and "after" surgery photos to assess new cosmetic products
Cosmetic Research:

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Arthur Kazukevich
Python-developer
Wadim Starosotnikow
Sergey Razumny
Senior quality control manager
TeamLead Crowd Solutions
Why
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Enhanced Data Accuracy
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Mitigation of Annotation Biases
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Non-disclosure agreement
Data Encryption
Multiple data storage options
Access Controls and Authentication
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100% post payment
$550 minimum check
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6 years in industry
Variable Workload
Customized Solutions
40+ languages
100+ countries
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