Awesome GitHub RepositoriesInstance Segmentation Tracking

pysot is a computer vision framework designed for single object tracking. It provides a platform for implementing and evaluating algorithms that locate and follow specific target objects across sequences of video frames. The project includes implementations of the SiamRPN architecture for region proposal network based localization and the SiamMask model, which combines tracking with binary mask generation to provide pixel-level segmentation of objects. The framework also contains a visual tracking evaluation toolkit used to measure the accuracy and reliability of tracking algorithms against

mmtracking is a PyTorch video perception framework designed for training and deploying computer vision models that analyze sequential image data. It provides specialized tools for multi-object tracking, video instance segmentation, and a configuration-driven system for managing deep learning models. The project utilizes a deep learning model registry and a configuration-driven pipeline to swap model backbones and detectors without modifying the core codebase. This modular approach allows for the development of custom perception architectures by combining various components and configurations.