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Cinematography Three Point Lighting

Community
geegl
cinematography-three-point-lighting

用户提到布光、灯光设置、三点照明、灯光比、主光/补光/背光

Overview

Publishergeegl
Repositorydirectorskills
Skill namecinematography-three-point-lighting
Stars
68
Forks
7
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by geegl on GitHub. Read the source before you install it.

Installation

Install the Cinematography Three Point Lighting AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/geegl/directorskills/tree/main/output/books/cinematography-brown/cinematography-three-point-lighting
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/geegl/directorskills.git /tmp/directorskills
mkdir -p .claude/skills
cp -r /tmp/directorskills/output/books/cinematography-brown/cinematography-three-point-lighting .claude/skills/cinematography-three-point-lighting
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cinematography Three Point Lighting in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cinematography Three Point Lighting on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cinematography Three Point Lighting is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

三点布光系统

R — 原文 (Reading)

主光：打在人物或物体上的关键光线，是场景中的"主要"灯光。补充光：照亮主光照不到的阴影部分的光线。背光：从人物或物体背后射来的光，会在主体边缘形成一圈亮边，令人脸的暗部从深色背景中分隔出来。 — Brown, 第7章, p.g_0035

I — 方法论骨架 (Interpretation)

三点布光是电影摄影最基础的灯光拓扑结构，由三个功能明确的光源组成：

  1. 主光（Key Light）：场景中最主要的光源，定义照明方向、阴影位置和整体明暗分布。主光的方向是布光中最关键的决策。

  2. 补光（Fill Light）：控制阴影深度。主光与补光的强度比（灯光比）决定了场景的对比度和情绪基调。高比值（如4:1、8:1）=低调/戏剧性；低比值（如2:1）=高调/轻快。

  3. 背光（Rim/Back Light）：从主体后方照射，在边缘形成一圈亮边，将主体从背景中分离出来，增加立体感和深度感。

三点布光的核心价值不在于"三盏灯"，而在于将灯光分解为三个独立可控的功能层。每一层都可以独立调整强度、方向、品质（硬/软）和颜色。理解这个框架后，你可以用两盏灯、一盏灯加反光板、甚至只用自然光来实现同样的功能分离。

A1 — 书中的应用 (Past Application)

案例：黑色电影的三点布光变体

  • 问题：黑色电影需要高对比度的戏剧性灯光，同时保持人物从暗背景中的可辨识性。
  • 方法论的使用：黑色电影将三点布光极端化——主光从侧面或后方打（创造大面积阴影），补光几乎取消（高灯光比），背光强烈（将剪影般的人物从黑暗中分离）。如《欲海情魔》中的画面，侧光创造了经典的明暗对比效果。
  • 结论：三点布光不是固定的灯光配方，而是一个可按需调整的框架。极端调整任何一盏灯都能创造特定的风格。
  • 结果：黑色电影成为电影史上最具辨识度的视觉风格之一。

案例：高清录像中的三点布光简化

  • 问题：高清摄影机对阴影的感知能力比胶片更强，是否还需要传统的补光？
  • 方法论的使用：布朗指出，现代高速胶片和高清摄影机能在阴影中"看到"更多细节，因此补光的使用正在逐渐减少。即使完全没有补光，强聚光（Kicker）也能够很好地照亮脸庞暗部。
  • 结论：三点布光的功能分离仍然有效，但各层的强度比例可以随技术进步而调整。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 用户需要为AI生成的画面设计灯光描述——"我想让这个场景看起来有电影感，灯光怎么描述？"
  2. 用户在实际拍摄中需要设置灯光——"对话场景怎么打光？"
  3. 用户想要理解电影中的灯光效果——"这个画面的灯光是怎么做的？"

语言信号

  • "怎么布光"、"灯光怎么设置"、"三点照明"
  • "主光放哪里"、"补光多少"、"要不要背光"
  • "灯光比"、"高调/低调"、"戏剧性灯光"
  • "AI画面灯光描述"、"prompt里灯光怎么写"

与相邻 skill 的区分

  • 与 light-direction-mood 的区别：三点布光是"有哪些灯"的结构框架，灯光方向是"灯放哪里"的方向决策。
  • 与 back-lighting 的区别：从后场打光是三点布光中主光方向的首选原则。
  • 与 light-as-symbol 的区别：灯光象征是叙事层面的框架，三点布光是技术层面的框架。

E — 可执行步骤 (Execution)

  1. 确定主光方向和品质

    • 根据场景情绪选择主光方向（参考 light-direction-mood）
    • 确定主光品质：硬光（小光源）还是软光（大光源）
    • 完成标准：能回答"主光从哪个方向打？硬还是软？"

  2. 设定灯光比（主光/补光比）

    • 高调场景（时尚/喜剧）：2:1 或更低
    • 中性场景（剧情/日常）：3:1 到 4:1
    • 低调场景（悬疑/黑色电影）：8:1 或更高
    • 完成标准：用测光表分别测量亮面和暗面，确认比值

  3. 添加背光分离主体

    • 背光从主体后方照射，可以在过曝状态下工作

    • 男性用较硬的背光，女性用较软的

    • 完成标准：主体边缘有可见的亮边，从背景中分离出来

    • 🔴 判停条件: 若人物看起来太平（缺乏立体感）或阴影太重（看不清表情），说明三点光比失衡——调整主光/补光的光比（通常2:1到4:1），检查背光是否过曝

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • 用户已经在讨论灯光的象征意义和叙事功能（使用 light-as-symbol）
  • 用户在讨论单光源场景（如蜡烛光场景）的特殊布光（使用 back-lighting 的叠光技术）
  • 用户在问色彩问题而非灯光问题

作者在书中警告的失败模式

  • 正面平光陷阱（e01）：将主光放在摄影机附近会产生扁平无立体感的画面。主光应从侧面或后方打来。
  • 忽略灯光品质：三点布光不只是三盏灯的位置，每盏灯的硬/软品质同样重要。
  • 灯光比一刀切：不同场景需要不同的灯光比，没有"万能"的比例。

反模式与常见错误

  • 机械套用三灯位置：三点布光的核心是三个功能层（主光/补光/背光），不是"必须用三盏灯"，用一盏灯加反光板同样可以实现功能分离
  • 灯光比一刀切：不同场景需要不同的灯光比（高调2:1、低调8:1），没有万能比例，用同一个比值拍所有场景是懒惰的错误
  • 忽略每盏灯的硬/软品质：只关注灯的位置而忽略品质选择，同样的三点结构用硬光和软光会产生完全不同的效果

作者的盲点 / 时代局限

Blain Brown 的分析框架源自传统胶片摄影，对数字传感器的特性（如动态范围、高光滚降、暗部噪声）讨论不足。他假设摄影团队有充足的设备和时间，独立制作或低预算场景的应对策略覆盖较少。案例库以好莱坞和欧洲艺术片为主，对亚洲、拉美等非西方电影传统的摄影风格涉及有限。

此外，三点照明作为经典布光方案，Brown 的讨论偏重静态场景，对运动场景中三点光的动态调整（如演员走位导致的光比变化）讨论不足。他未充分质疑三点照明在现代数字摄影中是否仍是最佳起点——自然光 + 反光板的简化方案可能更适合独立制作。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cinematography Three Point Lighting AI skill do?

用户提到布光、灯光设置、三点照明、灯光比、主光/补光/背光

Why use Cinematography Three Point Lighting on TypingMind?

Because you install it once and use it with any model. Cinematography Three Point Lighting is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cinematography Three Point Lighting in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/geegl/directorskills/tree/main/output/books/cinematography-brown/cinematography-three-point-lighting. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cinematography Three Point Lighting?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cinematography Three Point Lighting?

As many as you like. As long as a model supports skills, you can use Cinematography Three Point Lighting with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cinematography Three Point Lighting AI skill free?

Yes. It is published on GitHub by geegl under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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