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Landing: - Preload the Bricolage display font (LCP heading) to cut first paint - Cap tool-page meta descriptions at ~160 chars via whole-sentence truncation, so SERP snippets no longer overflow or cut mid-phrase - Drop dead HowTo + FAQPage JSON-LD from tool pages (Google removed HowTo rich results in 2023 and FAQ rich results in 2026); the visible content stays. Breadcrumb + WebApplication schema retained - Shorten 22 tool titles that exceeded the ~60-char SERP limit - Add an optional h1 override to tool SEO data - Rewrite adjust-colors, smart-crop, and ringtone-maker to match real Search Console query intent (saturation; object-aware cropping; convert audio to ringtone), with query-matched H1s and FAQs Docs: - Add meta descriptions to 20 pages missing frontmatter Repo: - Ignore local credential JSON files (.secrets/, *client_secret*, *service_account*)
94 lines
3.3 KiB
Markdown
94 lines
3.3 KiB
Markdown
---
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description: Subject-, face-, and entropy-aware cropping that frames images intelligently using Sharp and AI face detection.
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---
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# Smart Crop
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Smart subject-aware, face-aware, or trim-based cropping. Uses Sharp's attention/entropy strategies and AI face detection for intelligent framing.
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## API Endpoint
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`POST /api/v1/tools/image/smart-crop`
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**Processing:** Asynchronous (returns 202, poll `/api/v1/jobs/{jobId}/progress` for status via SSE)
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**Model bundle:** `face-detection` (200-300 MB) - required only for `face` mode
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## Parameters
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| Parameter | Type | Required | Default | Description |
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|-----------|------|----------|---------|-------------|
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| file | file | Yes | - | Image file (multipart) |
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| mode | string | No | `"subject"` | Crop mode: `subject`, `face`, `trim`. (Legacy values `attention` and `content` map to `subject` and `trim`) |
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| strategy | string | No | `"attention"` | Strategy for subject mode: `attention` or `entropy` |
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| width | integer | No | - | Target width in pixels |
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| height | integer | No | - | Target height in pixels |
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| padding | integer | No | `0` | Padding percentage around subject (0-50) |
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| facePreset | string | No | `"head-shoulders"` | Face framing preset: `closeup`, `head-shoulders`, `upper-body`, `half-body` |
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| sensitivity | number | No | `0.5` | Face detection sensitivity (0-1) |
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| threshold | integer | No | `30` | Trim mode threshold for background detection (0-255) |
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| padToSquare | boolean | No | `false` | Pad trimmed result to a square |
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| padColor | string | No | `"#ffffff"` | Background color for padding |
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| targetSize | integer | No | - | Target size for padded output (pixels) |
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| quality | integer | No | - | Output quality (1-100) |
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## Example Request
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```bash
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curl -X POST http://localhost:1349/api/v1/tools/image/smart-crop \
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-F "file=@portrait.jpg" \
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-F 'settings={"mode":"face","width":1080,"height":1080,"facePreset":"head-shoulders"}'
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```
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## Response
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### 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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### 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","percent":50}
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```
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### 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}/portrait_smartcrop.jpg",
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"originalSize": 500000,
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"processedSize": 320000
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}
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}
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```
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## Modes
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### Subject Mode
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Uses Sharp's attention or entropy strategy to find the most visually interesting region and crops around it.
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### Face Mode
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Detects faces using AI, then frames the crop around detected faces using the specified `facePreset`. Falls back to subject mode (attention strategy) if no faces are detected.
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### Trim Mode
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Removes uniform borders/background from the image. Optionally pads the result to a square with a specified background color and target size.
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## Notes
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- This tool uses the `createToolRoute` factory with `executionHint: "long"`, so it returns 202 with SSE progress.
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- Face mode requires the `face-detection` model bundle (200-300 MB).
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- Subject and trim modes work without any AI model bundle.
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- The `facePreset` determines how tightly the crop frames detected faces: `closeup` is the tightest, `half-body` is the widest.
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- If no width/height are specified, defaults to 1080x1080.
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