Diindeks komunitas
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.
Ringkasan
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.
Baca dokumentasi lengkap
Dokumentasi sumber, bukan instruksi untuk situs ini. Periksa izin sebelum menjalankan perintah.
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:
Lihat teks asli
# 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:Tinjau sumber
Harga dan biaya penggunaan
- Dapatkan skill
- Harga belum dikonfirmasi
- Jalankan
- Persyaratan belum dikonfirmasi. Periksa biaya agen, API, dan layanan di sumbernya.
- Lisensi
- MIT
- Harga belum dikonfirmasi
- Harga belum dikonfirmasi. Tautan sumber dan instalasi yang ada tetap tersedia.
Gratis diperoleh bukan berarti gratis dijalankan. Harga bukan penilaian keamanan. Kirim informasi harga →
Sumber perlu ditinjau
Sumber berubah atau gagal disinkronkan. Tinjau sumber terbaru sebelum memasang.
Tinjau sebelum memasang: Hindari pemasangan otomatis
Lisensi: 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
Daftar alat adalah petunjuk metadata, bukan kompatibilitas teruji. Prompt adalah saran.
Mulai dengan tugas kecil
- 1Baca sumber dan pastikan masukan, keluaran, dependensi, serta izin.
- 2Minta rencana dari agent. Setujui pengaturan dan biaya sebelum uji terisolasi.
- 3Periksa hasil dan berkas yang berubah. Laporkan hanya yang dijalankan dan simpan revisi sumber.
Periksa dependensi, kunci API, dan biaya layanan pihak ketiga pada sumber. Repositori publik tidak berarti semua layanan gratis.
Sumber dan catatan penggunaan
Metadata dan tinjauan bersifat saran. Popularitas, penemuan sumber, dan keberhasilan eksekusi adalah fakta berbeda.
- Repositori sumber
- TianLin0509/img2ppt-lite
- Lisensi
- MIT
- Versi
- 1.0.0
- Push GitHub terakhir
- 24 Jul 2026
- Direktori diperbarui
- 10 Sep 2026
- Jalur instruksi
- Struktur sumber belum diverifikasi
Versi dilaporkan dalam metadata direktori; periksa rilis sumber.
Kualitas
71/100
Kuat
Kepercayaan
59/100
Do not auto-install
Audit
75/100
Perlu ditinjau
- 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
- —
- Hasil
- —
Menyalin bukan memasang. Jumlah instalasi memerlukan laporan berhasil dan bukan jaminan kualitas menyeluruh.
Akses agent
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Detail lainnya
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"label": "Strong"
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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": [
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"slug": "vox-director",
"name": "Vox Director",
"url": "https://www.openagentskill.com/skills/vox-director",
"stars": 2259,
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"manifest": "https://www.openagentskill.com/api/registry/manifest/tianlin0509-img2ppt-lite"
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}Untuk kreator
Sumber listing
Diindeks komunitas
Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.
- Kreator
- TianLin0509
- Sumber
- TianLin0509/img2ppt-lite
- Diindeks oleh
- Indeks komunitas OpenAgentSkill
Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.
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Listing Diindeks komunitas ini dikaitkan dengan TianLin0509, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.
Kit berbagi
Kit backlink kreator
Tambahkan badge bukti ke README Anda
Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.
[](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)Sinyal komunitas
Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.
