BMW-Labeltool-Lite
A Docker-based image annotation tool for bounding box labeling with auto-labeling support, designed for deep learning training.
What is BMW-Labeltool-Lite?
LabelTool Lite is a lightweight, Docker-based image annotation tool designed for creating bounding box labels to train deep learning models. It simplifies the data labeling process with an intuitive web interface and supports auto-labeling by connecting pre-trained models to suggest annotations. The tool is built to integrate seamlessly with BMW's TensorFlow and YOLO training frameworks.
Deep learning practitioners, computer vision researchers, and data annotation teams who need to prepare labeled datasets for object detection models. It's especially useful for those working with YOLO or TensorFlow pipelines.
Developers choose LabelTool Lite for its minimal setup, Dockerized deployment, and auto-labeling capabilities that significantly reduce manual annotation time. Its direct integration with BMW's training repositories ensures a smooth workflow from labeling to model training.
Overview
This repository provides you with an easy-to-use labeling tool for State-of-the-art Deep Learning training purposes. It supports Auto-Labeling.
Use Cases
Best For
- Creating bounding box datasets for object detection models like YOLO and TensorFlow
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