Goku: A Million Scale Universal Dataset and Benchmark for Instruction Based Video Editing GOKU 2M is a large scale, unified instruction based video editing dataset covering 10 editing tasks . Each sample provides a source video, an edited target video, and one or more natural language instructions describing the edit. 📦 Repositories ⚠️ Because a single Hugging Face account has a free storage quota of about 8.7 TB , the dataset is split across two repositories : 🗂️ Repository 💾 Size 🎬 Tasks 🔵 bigfacing/GOKU 2M 5.11 TB add, remove, swap, alter, reference based add, reference based swap, camera motion, style transfer 🟢 Goku 2M/GOKU 2M 4.54 TB subject movement, multi step composite editing Tasks Folder Task Description add Add Add a new object into the scene remove Remove Remove an object from the scene swap alter Swap / Alter Replace an object, or alter its attributes reference add Reference Add Add an object specified by a reference image reference swap Reference Swap Replace an object with one from a reference image camera Camera Motion Apply a camera movement (pan / tilt / zoom / arc / translate) style transfer Style Transfer Restyle the whole video subject mov…
Runs entirely in your browser via DuckDB-Wasm — this dataset's real data file is loaded once, then queried locally. Nothing is sent to a server.
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy