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免费在 GitHub 公开中文介绍

manim-video

将数学概念、公式推导和算法执行过程制作成动画解说视频。使用Manim Community Edition,从内容规划、场景绘制到视频拼接,以图形辅助理解。

原文查看原文说明

Manim CE animations: 3Blue1Brown math/algo videos.

AI 评分90分/ 100查看安装方法

适用场景

  • 用图形解释数学概念
  • 逐步展示公式推导
  • 可视化算法执行过程
  • 将研究成果制作成解说视频

中文介绍

功能

使用Manim Community Edition,将数学和技术内容制作成图形与公式动态呈现的解说视频。可表现概念、公式推导、算法执行过程、数据比较、系统架构图和三维形状。流程包括在plan.md中整理内容结构,在script.py中创建各个场景,渲染后将片段拼接成final.mp4。

适用场景

适合仅靠公式难以讲清数学思路,或需要直观展示处理顺序的情况。制作时会考虑先展示图形再引入公式,并安排配色、文字大小和停顿,便于逐个场景组织教材或研究内容的讲解。

使用示例

  • “通过图形运动制作一段帮助理解傅里叶级数的视频。”
  • “展示这个算法的执行过程,以及数据结构的变化。”
  • “用动画解释这篇论文的主要研究结果。”

注意事项

需要Python 3.10或更高版本、Manim Community Edition v0.20或更高版本、LaTeX和ffmpeg。支持Linux、macOS和Windows,无需GPU。旁白为可选项,资料介绍了使用ElevenLabs或Qwen3-TTS的配置。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

客观评估

AI 仅根据 SKILL.md 的内容,从 4 个方面进行了评估。星标数和热度不计入评估。

指令清晰度能否看出何时使用、做什么
A良好明确列出数学解说、公式推导和算法可视化等用途,并说明输出视频。
步骤具体性步骤、输入输出和示例是否具体
A良好流程明确列出plan.md、script.py、渲染命令及拼接为final.mp4的步骤。
安全性发送数据、删除文件、执行命令等是否有说明
B部分不足要求运行scripts/setup.sh,但所提供资料未说明脚本的具体操作。
安装难易度所需工具和 API 密钥是否少且有说明
A良好列出Python和Manim版本、LaTeX、ffmpeg,并提供安装示例及依赖检查方法。

总分按每项 A=25 分、B=15 分、C=5 分相加。 由 AI(OpenAI Codex)于 2026年10月19日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

包含的文件(17)

  • SKILL.md11.9 KB
  • README.md886 B
  • references/animation-design-thinking.md7.0 KB
  • references/animations.md8.6 KB
  • references/camera-and-3d.md4.0 KB
  • references/decorations.md4.9 KB
  • references/equations.md5.9 KB
  • references/graphs-and-data.md4.5 KB
  • references/mobjects.md9.5 KB
  • references/paper-explainer.md9.1 KB
  • references/production-quality.md5.8 KB
  • references/rendering.md5.2 KB
  • references/scene-planning.md2.7 KB
  • references/troubleshooting.md4.2 KB
  • references/updaters-and-trackers.md8.3 KB
  • references/visual-design.md4.7 KB
  • scripts/setup.sh921 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Manim Video Production Pipeline

When to use

Use when users request: animated explanations, math animations, concept visualizations, algorithm walkthroughs, technical explainers, 3Blue1Brown style videos, or any programmatic animation with geometric/mathematical content. Creates 3Blue1Brown-style explainer videos, algorithm visualizations, equation derivations, architecture diagrams, and data stories using Manim Community Edition.

Creative Standard

This is educational cinema. Every frame teaches. Every animation reveals structure.

Before writing a single line of code, articulate the narrative arc. What misconception does this correct? What is the "aha moment"? What visual story takes the viewer from confusion to understanding? The user's prompt is a starting point — interpret it with pedagogical ambition.

Geometry before algebra. Show the shape first, the equation second. Visual memory encodes faster than symbolic memory. When the viewer sees the geometric pattern before the formula, the equation feels earned.

First-render excellence is non-negotiable. The output must be visually clear and aesthetically cohesive without revision rounds. If something looks cluttered, poorly timed, or like "AI-generated slides," it is wrong.

Opacity layering directs attention. Never show everything at full brightness. Primary elements at 1.0, contextual elements at 0.4, structural elements (axes, grids) at 0.15. The brain processes visual salience in layers.

Breathing room. Every animation needs self.wait() after it. The viewer needs time to absorb what just appeared. Never rush from one animation to the next. A 2-second pause after a key reveal is never wasted.

Cohesive visual language. All scenes share a color palette, consistent typography sizing, matching animation speeds. A technically correct video where every scene uses random different colors is an aesthetic failure.

Prerequisites

Run scripts/setup.sh to verify all dependencies. Requires: Python 3.10+, Manim Community Edition v0.20+ (pip install manim), LaTeX (texlive-full on Linux, mactex on macOS), and ffmpeg. Reference docs tested against Manim CE v0.20.1.

Modes

ModeInputOutputReference
Concept explainerTopic/conceptAnimated explanation with geometric intuitionreferences/scene-planning.md
Equation derivationMath expressionsStep-by-step animated proofreferences/equations.md
Algorithm visualizationAlgorithm descriptionStep-by-step execution with data structuresreferences/graphs-and-data.md
Data storyData/metricsAnimated charts, comparisons, countersreferences/graphs-and-data.md
Architecture diagramSystem descriptionComponents building up with connectionsreferences/mobjects.md
Paper explainerResearch paperKey findings and methods animatedreferences/scene-planning.md
3D visualization3D conceptRotating surfaces, parametric curves, spatial geometryreferences/camera-and-3d.md

Stack

Single Python script per project. No browser, no Node.js, no GPU required.

LayerToolPurpose
CoreManim Community EditionScene rendering, animation engine
MathLaTeX (texlive/MiKTeX)Equation rendering via MathTex
Video I/OffmpegScene stitching, format conversion, audio muxing
TTSElevenLabs / Qwen3-TTS (optional)Narration voiceover

Pipeline

PLAN --> CODE --> RENDER --> STITCH --> AUDIO (optional) --> REVIEW
  1. PLAN — Write plan.md with narrative arc, scene list, visual elements, color palette, voiceover script
  2. CODE — Write script.py with one class per scene, each independently renderable
  3. RENDER — manim -ql script.py Scene1 Scene2 ... for draft, -qh for production
  4. STITCH — ffmpeg concat of scene clips into final.mp4
  5. AUDIO (optional) — Add voiceover and/or background music via ffmpeg. See references/rendering.md
  6. REVIEW — Render preview stills, verify against plan, adjust

Project Structure

project-name/
  plan.md                # Narrative arc, scene breakdown
  script.py              # All scenes in one file
  concat.txt             # ffmpeg scene list
  final.mp4              # Stitched output
  media/                 # Auto-generated by Manim
    videos/script/480p15/

Creative Direction

Color Palettes

PaletteBackgroundPrimarySecondaryAccentUse case
Classic 3B1B#1C1C1C#58C4DD (BLUE)#83C167 (GREEN)#FFFF00 (YELLOW)General math/CS
Warm academic#2D2B55#FF6B6B#FFD93D#6BCB77Approachable
Neon tech#0A0A0A#00F5FF#FF00FF#39FF14Systems, architecture
Monochrome#1A1A2E#EAEAEA#888888#FFFFFFMinimalist

Animation Speed

Contextrun_timeself.wait() after
Title/intro appear1.5s1.0s
Key equation reveal2.0s2.0s
Transform/morph1.5s1.5s
Supporting label0.8s0.5s
FadeOut cleanup0.5s0.3s
"Aha moment" reveal2.5s3.0s

Typography Scale

RoleFont sizeUsage
Title48Scene titles, opening text
Heading36Section headers within a scene
Body30Explanatory text
Label24Annotations, axis labels
Caption20Subtitles, fine print

Fonts

Use monospace fonts for all text. Manim's Pango renderer produces broken kerning with proportional fonts at all sizes. See references/visual-design.md for full recommendations.

MONO = "Menlo"  # define once at top of file

Text("Fourier Series", font_size=48, font=MONO, weight=BOLD)  # titles
Text("n=1: sin(x)", font_size=20, font=MONO)                  # labels
MathTex(r"\nabla L")                                            # math (uses LaTeX)

Minimum font_size=18 for readability.

Per-Scene Variation

Never use identical config for all scenes. For each scene:

  • Different dominant color from the palette
  • Different layout — don't always center everything
  • Different animation entry — vary between Write, FadeIn, GrowFromCenter, Create
  • Different visual weight — some scenes dense, others sparse

Workflow

Step 1: Plan (plan.md)

Before any code, write plan.md. See references/scene-planning.md for the comprehensive template.

Step 2: Code (script.py)

One class per scene. Every scene is independently renderable.

from manim import *

BG = "#1C1C1C"
PRIMARY = "#58C4DD"
SECONDARY = "#83C167"
ACCENT = "#FFFF00"
MONO = "Menlo"

class Scene1_Introduction(Scene):
    def construct(self):
        self.camera.background_color = BG
        title = Text("Why Does This Work?", font_size=48, color=PRIMARY, weight=BOLD, font=MONO)
        self.add_subcaption("Why does this work?", duration=2)
        self.play(Write(title), run_time=1.5)
        self.wait(1.0)
        self.play(FadeOut(title), run_time=0.5)

Key patterns:

  • Subtitles on every animation: self.add_subcaption("text", duration=N) or subcaption="text" on self.play()
  • Shared color constants at file top for cross-scene consistency
  • self.camera.background_color set in every scene
  • Clean exits — FadeOut all mobjects at scene end: self.play(FadeOut(Group(*self.mobjects)))

Step 3: Render

manim -ql script.py Scene1_Introduction Scene2_CoreConcept  # draft
manim -qh script.py Scene1_Introduction Scene2_CoreConcept  # production

Step 4: Stitch

cat > concat.txt << 'EOF'
file 'media/videos/script/480p15/Scene1_Introduction.mp4'
file 'media/videos/script/480p15/Scene2_CoreConcept.mp4'
EOF
ffmpeg -y -f concat -safe 0 -i concat.txt -c copy final.mp4

Step 5: Review

manim -ql --format=png -s script.py Scene2_CoreConcept  # preview still

Critical Implementation Notes

Raw Strings for LaTeX

# WRONG: MathTex("\frac{1}{2}")
# RIGHT:
MathTex(r"\frac{1}{2}")

buff >= 0.5 for Edge Text

label.to_edge(DOWN, buff=0.5)  # never < 0.5

FadeOut Before Replacing Text

self.play(ReplacementTransform(note1, note2))  # not Write(note2) on top

Never Animate Non-Added Mobjects

self.play(Create(circle))  # must add first
self.play(circle.animate.set_color(RED))  # then animate

Performance Targets

QualityResolutionFPSSpeed
-ql (draft)854x480155-15s/scene
-qm (medium)1280x7203015-60s/scene
-qh (production)1920x10806030-120s/scene

Always iterate at -ql. Only render -qh for final output.

References

FileContents
references/animations.mdCore animations, rate functions, composition, .animate syntax, timing patterns
references/mobjects.mdText, shapes, VGroup/Group, positioning, styling, custom mobjects
references/visual-design.md12 design principles, opacity layering, layout templates, color palettes
references/equations.mdLaTeX in Manim, TransformMatchingTex, derivation patterns
references/graphs-and-data.mdAxes, plotting, BarChart, animated data, algorithm visualization
references/camera-and-3d.mdMovingCameraScene, ThreeDScene, 3D surfaces, camera control
references/scene-planning.mdNarrative arcs, layout templates, scene transitions, planning template
references/rendering.mdCLI reference, quality presets, ffmpeg, voiceover workflow, GIF export
references/troubleshooting.mdLaTeX errors, animation errors, common mistakes, debugging
references/animation-design-thinking.mdWhen to animate vs show static, decomposition, pacing, narration sync
references/updaters-and-trackers.mdValueTracker, add_updater, always_redraw, time-based updaters, patterns
references/paper-explainer.mdTurning research papers into animations — workflow, templates, domain patterns
references/decorations.mdSurroundingRectangle, Brace, arrows, DashedLine, Angle, annotation lifecycle
references/production-quality.mdPre-code, pre-render, post-render checklists, spatial layout, color, tempo

Creative Divergence (use only when user requests experimental/creative/unique output)

If the user asks for creative, experimental, or unconventional explanatory approaches, select a strategy and reason through it BEFORE designing the animation.

  • SCAMPER — when the user wants a fresh take on a standard explanation
  • Assumption Reversal — when the user wants to challenge how something is typically taught

SCAMPER Transformation

Take a standard mathematical/technical visualization and transform it:

  • Substitute: replace the standard visual metaphor (number line → winding path, matrix → city grid)
  • Combine: merge two explanation approaches (algebraic + geometric simultaneously)
  • Reverse: derive backward — start from the result and deconstruct to axioms
  • Modify: exaggerate a parameter to show why it matters (10x the learning rate, 1000x the sample size)
  • Eliminate: remove all notation — explain purely through animation and spatial relationships

Assumption Reversal

  1. List what's "standard" about how this topic is visualized (left-to-right, 2D, discrete steps, formal notation)
  2. Pick the most fundamental assumption
  3. Reverse it (right-to-left derivation, 3D embedding of a 2D concept, continuous morphing instead of steps, zero notation)
  4. Explore what the reversal reveals that the standard approach hides

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