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All 181 docs markdown files translated into 20 languages (apps/docs/<locale>/**). Companion to the i18n code PR; admin-merged because the file count exceeds GitHub's per-PR CI trigger limit. Validated by pnpm i18n:check (all surfaces, 0 stale/missing) and a clean all-locale docs build.
79 lines
2.7 KiB
Markdown
79 lines
2.7 KiB
Markdown
---
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description: "使用 AI 去背(BiRefNet)修正假透明 PNG 以產生真正的 alpha 通道,並附帶去邊緣清理。"
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i18n_source_hash: 7eb748b80f93
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i18n_provenance: human
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i18n_output_hash: 48d860859f01
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---
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# PNG 透明度修正 {#png-transparency-fixer}
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一鍵修正假透明 PNG。使用 AI 去背(BiRefNet HR Matting 模型)產生真正的 alpha 透明度,並以去邊緣後處理清理邊緣。
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## API 端點 {#api-endpoint}
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`POST /api/v1/tools/image/transparency-fixer`
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**處理方式:** 非同步(回傳 202,透過 SSE 輪詢 `/api/v1/jobs/{jobId}/progress` 以取得狀態)
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**模型套件:** `background-removal`(4-5 GB)
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## 參數 {#parameters}
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| 參數 | 型別 | 必填 | 預設值 | 說明 |
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|-----------|------|----------|---------|-------------|
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| file | file | 是 | - | 影像檔案(multipart) |
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| defringe | number | 否 | `30` | 去邊緣強度(0-100)。移除邊緣周圍的半透明邊緣像素 |
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| outputFormat | string | 否 | `"png"` | 輸出格式:`png` 或 `webp` |
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| removeWatermark | boolean | 否 | `false` | 套用浮水印移除前處理(中值濾波) |
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## 範例請求 {#example-request}
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```bash
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curl -X POST http://localhost:1349/api/v1/tools/image/transparency-fixer \
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-F "file=@fake-transparent.png" \
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-F 'settings={"defringe":40,"outputFormat":"png"}'
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```
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## 回應 {#response}
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### 初始回應(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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### 進度(SSE 位於 `/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":"Processing transparency...","percent":50}
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```
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### 最終結果(透過 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}/fake-transparent_fixed.png",
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"originalSize": 180000,
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"processedSize": 150000,
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"filename": "fake-transparent.png"
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}
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}
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```
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## 注意事項 {#notes}
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- 需要安裝 `background-removal` 模型套件(4-5 GB)。
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- 使用 `birefnet-hr-matting` 作為高品質 alpha 去背的主要模型。若 HR 模型記憶體不足,則回退到 `birefnet-general`。
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- `defringe` 選項會移除 AI 去背有時在頭髮、毛皮與細緻邊緣周圍留下的半透明邊緣像素。其運作方式為模糊 alpha 通道並將低信心像素歸零。
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- `removeWatermark` 選項會套用中值濾波前處理步驟。這是基本的浮水印減弱,並非專用的浮水印移除工具。
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- 只輸出 PNG 或無損 WebP(兩者皆支援 alpha 透明度)。
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- 透過自動解碼支援 HEIC/HEIF、RAW、TGA、PSD、EXR 與 HDR 輸入格式。
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