#image annotation

LabelImg, an open source image annotation tool, is designed in Python with a Qt interface. It supports PASCAL VOC, YOLO, and CreateML formats, aiding machine learning through efficient image labeling. Despite LabelImg's development integration with Label Studio, it remains a fundamental tool for image annotation, available on PyPI for Python 3+. It includes features for annotation visualization, class pre-definition, and hotkey usage, and supports Docker deployments. Compatible with multiple platforms, it requires minimal setup with Python and PyQt.

Explore MyVision, an online tool for image annotation that facilitates computer vision tasks by enhancing productivity through features like bounding box and polygon drawing, advanced polygon manipulation, and automatic annotation via pre-trained ML models. It ensures secure, local data processing and supports easy import or conversion of datasets. Available in English and Mandarin, MyVision offers a seamless labeling experience with no setup required, ideal for creating high-quality machine learning training data.

VoTT is an open-source resource designed for annotating and labeling image and video assets, perfect for machine learning workflows. This React and Redux-based web application, written in TypeScript, supports extensible models for importing and exporting data from local or cloud storage, enhancing project flexibility. It offers features such as image and video labeling, integration with Azure Blob Storage and local file systems, and exporting capabilities to formats like TensorFlow and CSV. Ideal for 'Bring Your Own Data' projects, VoTT simplifies the process of training machine learning models.

Labelme is a graphical image annotation tool that supports Python users in creating polygonal annotations with various shapes like rectangles, circles, and lines. It offers image and video annotation capabilities and allows GUI customization for intuitive use. The tool supports exporting to VOC and COCO formats suitable for semantic and instance segmentation. Comprehensive guides ensure it is accessible to users across different operating systems, making it ideal for developing precise image annotations in machine learning applications.

This repository features a straightforward image annotation tool for deep learning, optimizing with minimal setup. The lite version specializes in bounding box annotations and integrates with BMW’s TensorFlow and YOLO systems. It enhances productivity by allowing model connections for label suggestions, supports easy navigation and runs on Windows or Ubuntu using Docker. Features like zoom, brightness control, and efficient label management simplify AI training enhancement.