Open Source Deep Learning Frameworks

Computer Vision Annotation Tool (CVAT) is a free and open source, interactive online tool for annotating videos and images for Computer Vision algorithms. It offers many powerful features, including automatic annotation using deep learning models, interpolation of bounding boxes between key frames, LDAP and more. It is being used by its own professional data annotation team to annotate millions of objects with different properties. The UX and UI were also specially developed by the team for computer vision tasks. CVAT supports several annotation formats. Format selection can be done after clicking on the Upload annotation and Dump annotation buttons.

A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training through advanced filtering. We provide PyTorch, PyTorch Lightning and PyTorch Lightning distributed examples for each of the models to kickstart your project. Lightly requires Python 3.6+ but we recommend using Python 3.7+. We recommend installing Lightly in a Linux or OSX environment. With lightly, you can use the latest self-supervised learning methods in a modular way using the full power of PyTorch. Experiment with different backbones, models, and loss functions.