Label Studio

Label Studio is the leading open-source data labeling and annotation platform with over 27,000 GitHub stars, built by HumanSignal to make training data creation fast, flexible, and collaborative. The platform supports every major data type including text, images, audio, video, HTML, time series, and multi-modal combinations, making it the most versatile labeling tool available. With customizable labeling interfaces, ML-assisted annotation, and integrations with popular machine learning frameworks, Label Studio has become essential infrastructure for teams building AI and ML models.

Common Use Cases

Machine learning teams use Label Studio to create training datasets for computer vision models, annotating images with bounding boxes, polygons, keypoints, and semantic segmentation masks. NLP teams label text for named entity recognition, sentiment analysis, text classification, and relation extraction with customizable annotation schemas. Audio and speech teams transcribe recordings, label speaker diarization, and annotate audio segments for speech recognition model training. Research teams manage large-scale annotation projects with multiple labelers, using inter-annotator agreement metrics to ensure data quality.

Key Features

• Support for text, image, audio, video, time series, and multi-modal data labeling
• Customizable labeling interfaces with 50+ template types
• ML backend integration for prediction-assisted labeling
• Project management with task assignment and team collaboration
• Active learning workflows that prioritize uncertain samples
• Export to COCO, VOC, YOLO, and other popular ML formats
• Data import from cloud storage (S3, GCS, Azure Blob)
• Inter-annotator agreement and quality metrics
• REST API for programmatic access and automation
• Webhooks for integration with ML training pipelines

Why deploy Label Studio on Hostinger VPS

Deploying Label Studio on a Hostinger VPS gives you a private data labeling platform where sensitive training data never leaves your infrastructure, critical for projects involving medical images, financial documents, or proprietary business data. Self-hosting eliminates per-user pricing and annotation limits of managed labeling services, making it cost-effective for teams with many annotators. With PostgreSQL for reliable storage of projects and annotations, Label Studio on Hostinger VPS handles large datasets and concurrent labelers efficiently. The dedicated resources ensure smooth annotation experiences even with high-resolution images and complex labeling schemas.