3.5.0 — Video Watermark + Branding (favicon)
Video Watermark + Branding (favicon)
What's New
Features & Improvements
- Video watermark — automatic watermark overlay on generated videos, with language detection and a UI toggle.
- Per-tab watermark switch — the watermark toggle moves from the task list into each generation tab (Simple / Creative / Manuscript / Anchor), below the subtitle config.
- Project favicon — favicon and apple-touch-icon generated with the Agnes Image API.
- Watermark visuals — repositioned watermark with a branded blue background and more natural informational copy.
Refactoring & Optimizations
- OOM-safe watermarking — the watermark is composited with the ffmpeg
overlayfilter in a streaming pass instead of a MoviePy re-encode, eliminatingKilled: 9out-of-memory failures on long videos. - Relaxed video polling — polling interval raised from 30s to 60s to reduce rate-limit quota consumption.
Bug Fixes
- Watermark switch was hidden behind the progress panel; moved to avoid occlusion.
- Auto-detect video dimensions for watermark placement.
About Agnes Video Generator
A completely free, open-source AI video generator: turn text into multi-scene AI videos with narration and subtitles.
- Free and open source — no payment, no high-end GPU required
- Text-to-video, image-to-video, digital anchor and image generation
- Powered by free Agnes AI models, rendered entirely in the cloud
- Runs via Web UI, Docker or npm, and supports self-hosting
Related Pages
Release Notes
Changelog for Agnes Video Generator: new features, improvements and bug fixes for every release.
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Why you can trust this
Written by a practicing developer and cross-checked against authoritative primary sources such as arXiv papers, vendor technical reports, and the Stanford AI Index.
SandGrid@lcy362
Author of Agnes Video Generator · Full-stack Developer
Independent developer and author of Agnes Video Generator, an open-source (MIT) AI video generation tool built on Agnes AI's free video models. Has helped 1,000+ creators produce AI videos at zero cost. Focused on making video generation models accessible and production-ready; content is based on hands-on practice and primary research.
View on GitHubLast updated：2026-08-21
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