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TAPNet is the official Google DeepMind repository for Tracking Any Point (TAP), bundling datasets, models, benchmarks, and demos for precise point tracking in videos. The project includes the TAP-Vid and TAPVid-3D benchmarks, which evaluate long-range tracking of arbitrary points in 2D and 3D across diverse real and synthetic videos. Its flagship models—TAPIR, BootsTAPIR, and the latest TAPNext—use matching plus temporal refinement or next-token style propagation to achieve state-of-the-art...

Gonzo is an open source, Go-based terminal UI for real-time log analysis. It lets developers and SREs analyze live log streams directly in the terminal using an interactive dashboard with charts, filters, and structured views. It supports multiple input sources, including files, stdin, and OpenTelemetry streams, while automatically detecting formats such as JSON and logfmt. Users can explore logs through a k9s-inspired layout, combining visualizations like heatmaps, severity distributions,...

The OpenClaw Mobile Dashboard. Monitor agent's real-time thoughts, actions, track token costs, and manage tasks from anywhere using your pocket-sized Mission Control.

Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform...