Depth Anything V2 is a research codebase for monocular depth estimation, providing both relative and metric depth models. It builds on a DINOv2 encoder with a DPT decoder, offering four model scales (Small, Base, Large, Giant). The repository includes inference scripts for images and videos, a Gradio demo, and a subdirectory for fine-tuning on metric depth estimation using Hypersim (indoor) and Virtual KITTI 2 (outdoor) datasets. It also defines the DA-2K evaluation benchmark for relative depth. The code is well-structured with reusable transform utilities and evaluation metrics, but reproducibility is limited due to hardcoded dataset paths and unpinned dependencies. This is primarily a research project with a hybrid nature due to the included demo application.