Community tool for long-video batch processing with SAM2 (simple-sam2)

Hi SAM2 team,

I built a lightweight wrapper around SAM2 video predictor that solves
long-video segmentation - SAM2 currently loads the entire video into
memory which makes it unusable for longer clips.

simple-sam2 adds:
- Batch processing :- only `batch_size` frames in memory at once, keeping
GPU/CPU memory usage constant regardless of video length

- Unified prompt API :- mask, points, and box in a single call (SAM2 natively
requires mask OR points+box separately)

- Direct video file input:- pass any .mp4/.avi/.mov directly, frames are
extracted automatically via OpenCV, no manual preprocessing needed

- Selective frame range processing :- specify `start_frame_idx` and `end_frame_idx`
to segment only a portion of the video instead of processing the entire clip,
useful for long videos where only a specific segment is of interest

- Persistent storage layout :- extracted frames and output masks are organized
under a canonical directory structure, so re-runs skip re-extraction and
masks are always easy to locate

- Carry-over mask mechanism :- object identity is maintained across batch
boundaries by propagating the last frame's mask as the seed for the next batch

PyPI: https://pypi.org/project/simple-sam2/
GitHub: https://github.com/varun-kolluru/simple_sam2

Sharing here in case it's useful to others in the community. Happy to
answer questions or take feedback.

Review the linked simple_sam2 GitHub project and PyPI package first; the issue does not identify a SAM2 repository file, test, or entry point to change. No repository change or completion condition is specified, so clarify whether this is intended as an integration, documentation link, or community-tool announcement.

Written by the indexing model from the issue text.