This repository contains a custom image annotation dataset created using Label Studio.
The dataset focuses on multi-class object detection and segmentation, covering a wide range of real-world objects such as animals, vehicles, kitchen items, furniture, and outdoor scenes.
The annotations were manually created using both Rectangle and Polygon tools for higher precision, making it suitable for machine learning models involving:
- Object Detection (bounding boxes)
- Image Segmentation (polygon masks)
- Label Studio → for annotation
- Python / Google Colab → for visualization & dataset checks
- GitHub → for version control & sharing
- VS Code → for editing label configuration and dataset structure
-image-annotation-dataset/ ├── images/ # Original image files used for annotation ├── annotations/ # Exported annotations (COCO / JSON format) ├── label_config.xml # Label Studio configuration file (this project’s setup) └── README.md # Documentation for the dataset