Audio Transcription
Datasets and Services for Training LLM
Image Annotation USE CASE
Botox Before/After Image Collection
A dataset of photos of individuals with and without Botox for facial classification before and after surgeries
Computer Vision The ability of a machine to interpret, analyze, and understand visual data
Classification The process of recognizing and grouping objects into predefined categories
Re-identification The recognition of the same object in different observations
AR Machine learning in augmented reality applications
2 000
photos
3 weeks
project duration
Our Partners
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
APPLICATION AREAS OF THE DATASET
Cosmetic Industry:
Semantic segmentation of selfies after surgeries to demonstrate expected results of Botox procedures to clients
Cosmetic Research:
Crowdsourced evaluations of "before" and "after" surgery photos to assess new cosmetic products
AR:
Semantic segmentation and matting of selfies to create advertising masks that visually demonstrate the effects of cosmetic surgeries in real-time
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Why
Training Data
- Quality Assurance:
- Enhanced Data Accuracy
- Consistency in Labels
- Reliable Ground Truth
- Mitigation of Annotation Biases
- Cost and Time Efficiency
- Data Security and Confidentiality:
- GDPR Compliance
- Non-disclosure agreement
- Data Encryption
- Multiple data storage options
- Access Controls and Authentication
- Expert Team:
- 6 years in industry
- 35 top project managers
- 40+ languages
- 100+ countries
- 250k+ assessors
- Flexible and Scalable Solutions:
- 24/7 availability of customer service
- 100% post payment
- $550 minimum check
- Variable Workload
- Customized Solutions
Team leads project
Sergey Razumny
TeamLead Crowd Solutions
Arthur Kazukevich
Python-developer
Wadim Starosotnikow
Senior quality control manager