This is the Linux app named Tracking Any Point (TAP) whose latest release can be downloaded as tapnetsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Tracking Any Point (TAP) with OnWorks for free.
Befolgen Sie diese Anweisungen, um diese App auszuführen:
- 1. Diese Anwendung auf Ihren PC heruntergeladen.
- 2. Geben Sie in unserem Dateimanager https://www.onworks.net/myfiles.php?username=XXXXX den gewünschten Benutzernamen ein.
- 3. Laden Sie diese Anwendung in einem solchen Dateimanager hoch.
- 4. Starten Sie den OnWorks Linux-Online- oder Windows-Online-Emulator oder den MACOS-Online-Emulator von dieser Website.
- 5. Rufen Sie vom gerade gestarteten OnWorks Linux-Betriebssystem aus unseren Dateimanager https://www.onworks.net/myfiles.php?username=XXXXX mit dem gewünschten Benutzernamen auf.
- 6. Laden Sie die Anwendung herunter, installieren Sie sie und führen Sie sie aus.
SCREENSHOTS
Ad
Tracking Any Point (TAP)
BESCHREIBUNG
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 accuracy and speed on TAP-Vid. RoboTAP demonstrates how TAPIR-style tracks can drive real-world robot manipulation via efficient imitation, and ships with a dataset of annotated robotics videos. The repo provides JAX and PyTorch checkpoints, Colab demos, and a real-time live demo that runs on a GPU to let you select and track points interactively.
Eigenschaften
- Clear coordinate conventions and standardized metrics for fair, reproducible comparisons
- Training and evaluation pipelines, plus Kubric utilities for generating point tracks
- Colab notebooks and an offline/online real-time demo for quick experimentation
- RoboTAP benchmark and clustering demo for robotics manipulation from point tracks
- High-performance models including TAPIR, BootsTAPIR, and TAPNext with JAX and PyTorch checkpoints
- TAP-Vid and TAPVid-3D datasets and evaluation metrics for point tracking
Programmiersprache
Python, Unix-Shell
Kategorien
This is an application that can also be fetched from https://sourceforge.net/projects/tap.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
