Java User Group Hamburg - GitHub Actions

Wed, 12 Jun 2024 00:00:00 +0000

DataGym.ai

Sun, 15 Mar 2020 00:00:00 +0000

DataGym.ai is a modern, web-based workbench for labeling images and videos. I built this tool to streamline the process of creating high-quality training data for machine learning models.

What it does

The platform allows teams to manage annotation projects end-to-end: organize datasets, label data with various annotation types, control quality through built-in review workflows, and export labeled data for model training.

Key Features

Multi-format support - Works with images (JPEG, PNG) and videos (MP4), including high-resolution assets
Rich annotation tools - Points, lines, bounding boxes, polygons, image segmentation, and video object tracking with linear interpolation
Quality control - Integrated review process with task lifecycle management (backlog → in progress → completed → reviewed)
Flexible storage - Direct uploads, public URLs, or AWS S3 integration
API-first design - Full REST API with Python SDK for integration into ML pipelines
Data portability - JSON import/export for labeled data and configurations

Tech Stack

Built with Java/Spring Boot on the backend and Angular on the frontend. The entire stack runs via Docker Compose for easy local deployment.

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Java User Group Hamburg - GitHub Actions

DataGym.ai

What it does

Key Features

Tech Stack