geeklee/srt-whiteboard-animation

将 SRT 字幕做成暖米黄纸张底的流式笔迹白板手绘动画 skill:mask 分区遮罩编排 + stream 连续笔迹(ink→color)。

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Summary Information

Updated 52 minutes ago
Added to GitGenius on September 20th, 2026
Created on July 27th, 2026
Open Issues & Pull Requests: 6 (+0)
GitHub issues: Enabled
Number of forks: 559
Total Stargazers: 3,389 (+0)
Total Subscribers: 13 (+0)

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Open issues: 2
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 32 days
Stale 30+ days: 0
Stale 90+ days: 0

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Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

SRT Whiteboard Animation is a Python tool that converts SRT subtitles into hand-drawn whiteboard animation videos with a warm cream-colored paper background.

The tool solves the problem of creating narrative-driven animated explainers by combining subtitle-driven sequencing with continuous ink-stroke rendering. It parses SRT files, breaks them into scenes of recommended length, and generates animations where each visual element appears in narrative order rather than by spatial coordinates. Elements are drawn with flowing pen strokes that first lay down line art, then add color, all synchronized to subtitle timing. The workflow emphasizes staged confirmation at each step—from storyboard planning through line art generation, annotation, preview adjustment, and final rendering—to avoid wasting render time on unfinalized designs.

The tool suits projects that need to transform knowledge explanations, story narration, course subtitles, or short-form video scripts into hand-drawn animations. It enforces a specific visual language: minimalist hand-drawn style with deep gray sketch lines, warm cream backgrounds, and restrained use of red, orange, and blue for conceptual accents. The annotation system uses pixel coordinates tied to subtitle events, with support for protected regions to manage overlapping elements. A browser-based preview interface lets creators adjust regions, drawing order, timing, and subtitle associations before committing to rendering. The tool supports both single-scene and multi-scene projects with frame-by-frame or batch rendering to MP4.

The project maintains an independent Python virtual environment setup to ensure dependency isolation across renders. Development activity shows ongoing refinement of the annotation and preview workflow, with the tool designed to handle iterative adjustments without re-rendering completed work. The codebase emphasizes semantic organization of drawing sequences tied to narrative events rather than visual positioning, and includes quality-check utilities for validating region layouts before animation generation.