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SnapOtterandGitHub
f858c4cea0
Renames 18 ambiguous or hard-to-search tool names so image tools self-qualify like the other modalities ("Compress" becomes "Compress Image"), and cleans up a few awkward names. Propagated across search (constants.ts), display (en.ts + 20 locales), the OpenAPI base spec + 20 locale specs, and the docs tool-page headings in 21 languages. Removes the duplicate "Normalize Audio" summary shared by the video and audio endpoints. Tool ids and routes are unchanged, so no API paths or bookmarks break.
97 lines
2.8 KiB
Markdown
97 lines
2.8 KiB
Markdown
---
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description: "Deteksi dan buramkan wajah dalam gambar secara otomatis dengan deteksi wajah AI untuk privasi dan anonimisasi yang patuh GDPR."
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i18n_source_hash: 314e3e16a422
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i18n_provenance: human
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i18n_output_hash: a2d660c6993d
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---
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# Blur Wajah & Info Pribadi {#face-pii-blur}
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Deteksi dan buramkan wajah dalam gambar secara otomatis menggunakan deteksi wajah bertenaga AI (MediaPipe).
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## API Endpoint {#api-endpoint}
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`POST /api/v1/tools/image/blur-faces`
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**Pemrosesan:** Asinkron (mengembalikan 202, polling `/api/v1/jobs/{jobId}/progress` untuk status melalui SSE)
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**Bundel model:** `face-detection` (200-300 MB)
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## Parameter {#parameters}
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| Parameter | Tipe | Wajib | Bawaan | Deskripsi |
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|-----------|------|----------|---------|-------------|
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| file | file | Ya | - | Berkas gambar (multipart) |
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| blurRadius | number | Tidak | `30` | Radius blur yang diterapkan pada wajah yang terdeteksi (1-100) |
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| sensitivity | number | Tidak | `0.5` | Sensitivitas deteksi wajah (0-1). Nilai lebih rendah mendeteksi lebih sedikit wajah dengan keyakinan lebih tinggi |
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## Contoh Permintaan {#example-request}
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```bash
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curl -X POST http://localhost:1349/api/v1/tools/image/blur-faces \
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-F "file=@group-photo.jpg" \
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-F 'settings={"blurRadius":40,"sensitivity":0.3}'
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```
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## Respons {#response}
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### Respons Awal (202 Accepted) {#initial-response-202-accepted}
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```json
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{
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"jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
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"async": true
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}
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```
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### Progres (SSE di `/api/v1/jobs/{jobId}/progress`) {#progress-sse-at-api-v1-jobs-jobid-progress}
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```
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event: progress
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data: {"phase":"processing","stage":"Detecting faces...","percent":40}
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```
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### Hasil Akhir (melalui SSE) {#final-result-via-sse}
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```json
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{
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"phase": "complete",
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"percent": 100,
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"result": {
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"jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
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"downloadUrl": "/api/v1/download/{jobId}/group-photo_blurred.jpg",
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"originalSize": 450000,
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"processedSize": 420000,
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"facesDetected": 3,
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"faces": [
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{"x": 100, "y": 50, "w": 80, "h": 80},
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{"x": 300, "y": 60, "w": 75, "h": 75},
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{"x": 500, "y": 55, "w": 85, "h": 85}
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]
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}
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}
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```
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### Tidak Ada Wajah Terdeteksi {#no-faces-detected}
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Jika tidak ada wajah ditemukan, hasil menyertakan peringatan:
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```json
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{
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"phase": "complete",
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"percent": 100,
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"result": {
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"facesDetected": 0,
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"warning": "No faces detected in this image. Try increasing detection sensitivity."
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}
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}
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```
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## Catatan {#notes}
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- Memerlukan bundel model `face-detection` untuk dipasang (200-300 MB).
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- Format keluaran mengikuti format input secara otomatis.
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- Larik `faces` berisi koordinat kotak pembatas (x, y, width, height) untuk setiap wajah yang terdeteksi.
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- Naikkan `sensitivity` (lebih dekat ke 1,0) untuk mendeteksi lebih banyak wajah, termasuk yang sebagian terhalang.
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- Mendukung format input HEIC/HEIF, RAW, TGA, PSD, EXR, dan HDR melalui dekode otomatis.
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