1 repo
Hooks for visualizing tracking results on video frames.
Distinguishing note: Focuses on drawing masks and boxes for tracking outputs.
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This project is a modular research toolkit designed for developing, training, and evaluating deep learning models for object detection, segmentation, and video instance tracking. It provides a flexible training engine that manages complex neural network execution, including distributed training, custom lifecycle hooks, and weight optimization. The framework is built around a hierarchical configuration system that allows users to define architectures, data pipelines, and training hyperparameters through composable, inheritable files. The project distinguishes itself through its highly modular
Visualizes detection and tracking results by drawing bounding boxes and masks on images.