Video segmentation with Segment Anything 2 (SAM2)

Segment Anything Model 2 (SAM 2) is an advanced model designed for video and image segmentation, addressing challenges such as object motion, occlusion, and lighting changes. It offers improved accuracy and speed, requiring three times fewer interactions for video segmentation compared to previous models. SAM 2 is available in four sizes, with the largest model processing around 30 frames per second. To use SAM 2 for video segmentation, users must clone the repository, install dependencies, and load the model with the appropriate configuration files. The model utilizes memory to maintain context across frames, enhancing mask predictions.

For segmentation, frames must be saved in JPEG format, and the model requires initialization of an inference state. Users can segment and track objects by providing positive and negative point prompts, refining predictions as needed. SAM 2 can also propagate prompts across video frames, allowing for efficient tracking of multiple objects. However, it may struggle with shot changes, crowded scenes, and objects with fine details. Despite these limitations, SAM 2 represents a significant advancement in segmentation technology, with potential applications across various industries. The model's release has inspired further research and development in the field, indicating a growing interest in enhancing segmentation capabilities.