USE CASE
Pigs Detection Image Annotation
100,000 photos and descriptions of people in these photos. Descriptions in the dataset are unique and do not repeat
Computer Vision
Ability to recognize and analyze images and videos
Agribusiness
Using machine learning in the agro-industry
Object Detection
Defining the object position by Bounding Box marking
Data Labeling
Highlighting objects in a photo to train the system to recognise and interpret them
1000
images
7
weeks
Our Partners
CASE DESCRIPTION
Pig detection in farm photographs using Bounding Box in CVAT
Additional classification of pigs by health and breed type
The data is used for monitoring animal health, controlling population numbers, and automating record-keeping on farms
APPLICATION AREAS OF THE DATASET
Farming and livestock:
Detection for automatic identification and counting of pigs during transportation
Improving security on the farm:
Classification to determine abnormal animal behavior and the presence of foreign objects on the farm
Breeding process optimization:
Computer vision and classification to optimize the ratio of pigs of various ages and genders on the farm
Livestock monitoring system:
Computer vision for automatic tracking of the number of pigs on the farm and planning of feeding and veterinary care
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Why
Training Data
- Quality Assurance:
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Enhanced Data Accuracy
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Consistency in Labels
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Reliable Ground Truth
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Mitigation of Annotation Biases
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Cost and Time Efficiency
- Data Security and Confidentiality:
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GDPR Compliance
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Non-disclosure agreement
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Data Encryption
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Multiple data storage options
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Access Controls and Authentication
- Expert Team:
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6 years in industry
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35 top project managers
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40+ languages
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100+ countries
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250k+ assessors
- Flexible and Scalable Solutions:
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24/7 availability of customer service
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100% post payment
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$550 minimum check
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Variable Workload
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Customized Solutions
Team leads project
Sergey Razumny
TeamLead Crowd Solutions
Arthur Kazukevich
Python-developer
Wadim Starosotnikow
Senior quality control manager