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Img2ppt Lite
Turn a slide mockup image into an editable PPTX: native text + semantic draggable sprites + inpainted background. Agent-as-VLM skill for Claude Code / Codex / any CLI agent.
概览
Turn a slide mockup image into an editable PPTX: native text + semantic draggable sprites + inpainted background. Agent-as-VLM skill for Claude Code / Codex / any CLI agent.
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img2ppt-lite
把一张 PPT 效果图(PNG/JPG)还原成高保真、可编辑的 PPTX。
Turn a slide mockup image (e.g. generated by GPT-image / Midjourney / any design tool) into an editable PowerPoint file: native text boxes + semantically-split draggable sprites + inpainted clean background. Built as an agent skill — the executing AI (Claude Code / Codex / any CLI agent with vision) acts as the VLM, deterministic Python scripts do everything else.
左:合成样张源图 · 右:管线重建后由 PowerPoint 渲染回的图(文字全部为原生可编辑文本框,图表/图标为独立贴图)
它解决什么问题
AI 出图工具能生成非常漂亮的 PPT 效果图,但那只是一张图片。想拿它当真正的工作底稿,你需要:
- 文字可编辑——改标题、改数据是最高频操作;
- 元素可拖拽——每个图标、图表、色块都是独立对象,能单独移动缩放;
- 视觉尽量 1:1——还原完的页面和效果图肉眼几乎一致。
传统"图转 PPT"路线要么把整页塞成一张图(完全不可编辑),要么全原生重建(图标丑、收敛循环极慢)。img2ppt-lite 走中间路线,并把速度做到了单页 3-5 分钟(脚本部分约 40-60 秒)。
核心设计
可编辑 PPTX = 干净底图 (inpaint 去前景)
+ 语义元素贴图 (每个图标/图表一张独立 picture,可拖拽)
+ 原生文本框 (PIL 墨水高度反解字号,可编辑)
+ 纯色矩形原生化 (KPI 条/按钮/色块 → 可改色的原生 shape)
三个反直觉的关键决策:
- 视觉一致性的最大敌人恰恰是"原生重建"。 从原图裁出来的贴图天然 100% 一致;会漂的只有文本层——而文本字号可以用 PIL 按墨水高度离线反解,不需要"渲染→对比→调整"的收敛循环。这是比前代管线快一个量级的根本原因。
- 执行 agent 自身就是 VLM。 不调外部视觉 API:agent 看图产出一份
elements.json(文本/色块/图形的语义标注),脚本吃 JSON 确定性完成其余一切。LLM 参与固定 2 次(标注 + 终检),零额外 token 成本。 - 测量代替猜测。 字号、文字颜色、卡片填充色、渐变、行首 marker 全部从像素实测,agent 只负责语义;每个测量器都经过阳性+阴性用例双验。
环境要求
- Windows(PowerPoint COM 用于渲染回读验证;没有 PowerPoint 也能出 PPTX,只是跳过渲染验证)
- Python 3.10+
pip install -r requirements.txt
装好后先跑自检(生成合成样张走全链路,含 marker 正/负回归用例):
python scripts/pipeline.py --selftest
使用方式
作为 agent skill(推荐)
把本仓库放进你的 agent skill 目录(如 Claude Code 的 ~/.claude/skills/img2ppt-lite/),agent 会按 SKILL.md 的 5 步工作流执行:
1. pipeline.py --run <run> --seed # OCR 冷启动,产出待审阅的文本骨架
2. [agent 看图] 校对 seed、补图形/色块标注 → elements.json
3. pipeline.py --run <run> # OCR校准 → 切图 → 装配 → COM 渲染验收
4. [agent 看图] 对比 compare.png,必要时改 JSON 秒级重跑
5. 交付 pptx + 验收报告(修补硬上限 2 轮,禁无限迭代)
手动使用
不用 agent 也可以:
查看原始文本
# img2ppt-lite
**把一张 PPT 效果图(PNG/JPG)还原成高保真、可编辑的 PPTX。**
Turn a slide mockup image (e.g. generated by GPT-image / Midjourney / any design tool) into an editable PowerPoint file: native text boxes + semantically-split draggable sprites + inpainted clean background. Built as an agent skill — the executing AI (Claude Code / Codex / any CLI agent with vision) acts as the VLM, deterministic Python scripts do everything else.

*左:合成样张源图 · 右:管线重建后由 PowerPoint 渲染回的图(文字全部为原生可编辑文本框,图表/图标为独立贴图)*
## 它解决什么问题
AI 出图工具能生成非常漂亮的 PPT 效果图,但那只是一张图片。想拿它当真正的工作底稿,你需要:
- **文字可编辑**——改标题、改数据是最高频操作;
- **元素可拖拽**——每个图标、图表、色块都是独立对象,能单独移动缩放;
- **视觉尽量 1:1**——还原完的页面和效果图肉眼几乎一致。
传统"图转 PPT"路线要么把整页塞成一张图(完全不可编辑),要么全原生重建(图标丑、收敛循环极慢)。img2ppt-lite 走中间路线,并把速度做到了**单页 3-5 分钟**(脚本部分约 40-60 秒)。
## 核心设计
```
可编辑 PPTX = 干净底图 (inpaint 去前景)
+ 语义元素贴图 (每个图标/图表一张独立 picture,可拖拽)
+ 原生文本框 (PIL 墨水高度反解字号,可编辑)
+ 纯色矩形原生化 (KPI 条/按钮/色块 → 可改色的原生 shape)
```
三个反直觉的关键决策:
1. **视觉一致性的最大敌人恰恰是"原生重建"。** 从原图裁出来的贴图天然 100% 一致;会漂的只有文本层——而文本字号可以用 PIL 按墨水高度离线反解,**不需要"渲染→对比→调整"的收敛循环**。这是比前代管线快一个量级的根本原因。
2. **执行 agent 自身就是 VLM。** 不调外部视觉 API:agent 看图产出一份 `elements.json`(文本/色块/图形的语义标注),脚本吃 JSON 确定性完成其余一切。LLM 参与固定 2 次(标注 + 终检),零额外 token 成本。
3. **测量代替猜测。** 字号、文字颜色、卡片填充色、渐变、行首 marker 全部从像素实测,agent 只负责语义;每个测量器都经过阳性+阴性用例双验。
## 环境要求
- Windows(PowerPoint COM 用于渲染回读验证;**没有 PowerPoint 也能出 PPTX**,只是跳过渲染验证)
- Python 3.10+
```bash
pip install -r requirements.txt
```
装好后先跑自检(生成合成样张走全链路,含 marker 正/负回归用例):
```bash
python scripts/pipeline.py --selftest
```
## 使用方式
### 作为 agent skill(推荐)
把本仓库放进你的 agent skill 目录(如 Claude Code 的 `~/.claude/skills/img2ppt-lite/`),agent 会按 `SKILL.md` 的 5 步工作流执行:
```
1. pipeline.py --run <run> --seed # OCR 冷启动,产出待审阅的文本骨架
2. [agent 看图] 校对 seed、补图形/色块标注 → elements.json
3. pipeline.py --run <run> # OCR校准 → 切图 → 装配 → COM 渲染验收
4. [agent 看图] 对比 compare.png,必要时改 JSON 秒级重跑
5. 交付 pptx + 验收报告(修补硬上限 2 轮,禁无限迭代)
```
### 手动使用
不用 agent 也可以:查看并核实来源
获取价格与运行成本
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- 许可证
- MIT
- 价格未确认
- 我们尚未确认此 Skill 的价格,现有来源与安装入口仍可使用。
免费获取不代表免费运行,价格标签不代表安全评级。 提交价格信息 →
来源需要复核
已跟踪的来源发生变化或同步失败,请在安装前复核当前来源。
安装前审查: 避免自动安装
许可证: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 23 GitHub stars
- Stars/forks activity: 23 stars, 4 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
工具列表来自元数据,并非已测试的兼容性;Agent 提示词是建议的交接方式。
从一个小任务开始
- 1阅读来源,确认输入、预期输出、依赖和权限。
- 2先让 Agent 提出计划,批准环境配置和费用,再进行隔离的小规模测试。
- 3检查输出和变更文件,只报告实际执行结果,并保留来源版本以便复现。
请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。
来源与使用须知
仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。
- 来源仓库
- TianLin0509/img2ppt-lite
- 许可证
- MIT
- 版本
- 1.0.0
- 最近 GitHub 推送
- 2026年7月24日
- 目录更新于
- 2026年9月10日
- 技能指令路径
- 来源结构待验证
版本来自目录元数据,使用前请核实来源发布记录。
质量
71/100
强
信任
59/100
Do not auto-install
审计
75/100
需审查
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Low GitHub adoption signal
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 23 GitHub stars
- Stars/forks activity: 23 stars, 4 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- 结果
- —
复制不等于安装。安装数需有成功安装回报,不代表全面的质量保证。
Agent 接入
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
更多详情
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"skill": {
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"name": "Img2ppt Lite",
"description": "Turn a slide mockup image into an editable PPTX: native text + semantic draggable sprites + inpainted background. Agent-as-VLM skill for Claude Code / Codex / any CLI agent.",
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"python"
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"GitHub adoption: 23 GitHub stars",
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"supply": {
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"scenario": "Design and creative",
"maintenance": "3mo since push",
"risk": "Needs review"
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"alternative_skills": [
{
"slug": "vox-director",
"name": "Vox Director",
"url": "https://www.openagentskill.com/skills/vox-director",
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"Permission surface may require sandboxing",
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"eval": "https://www.openagentskill.com/api/agent/evals?slug=tianlin0509-img2ppt-lite&task=Use%20Img2ppt%20Lite%20in%20an%20agent%20workflow&max_risk=medium",
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"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20Img2ppt%20Lite%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/tianlin0509-img2ppt-lite/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/tianlin0509-img2ppt-lite"
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}创作者工具
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将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/tianlin0509-img2ppt-lite?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/tianlin0509-img2ppt-lite?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/tianlin0509-img2ppt-lite/audit)
[](https://www.openagentskill.com/skills/tianlin0509-img2ppt-lite?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
