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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.
2.7 KiB
2.7 KiB
description, i18n_source_hash, i18n_provenance, i18n_output_hash
| description | i18n_source_hash | i18n_provenance | i18n_output_hash |
|---|---|---|---|
| 使用 AI 人脸检测自动识别并模糊图像中的人脸,用于隐私保护和符合 GDPR 的匿名化。 | 314e3e16a422 | human | 3a0007f60b8a |
模糊人脸和隐私信息
使用 AI 驱动的人脸检测(MediaPipe)自动识别并模糊图像中的人脸。
API Endpoint
POST /api/v1/tools/image/blur-faces
处理方式: 异步(返回 202,通过 SSE 轮询 /api/v1/jobs/{jobId}/progress 获取状态)
模型包: face-detection(200-300 MB)
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| file | file | 是 | - | 图像文件(multipart) |
| blurRadius | number | 否 | 30 |
应用于检测到人脸的模糊半径(1-100) |
| sensitivity | number | 否 | 0.5 |
人脸检测灵敏度(0-1)。值越低,检测到的人脸越少但置信度越高 |
Example Request
curl -X POST http://localhost:1349/api/v1/tools/image/blur-faces \
-F "file=@group-photo.jpg" \
-F 'settings={"blurRadius":40,"sensitivity":0.3}'
Response
Initial Response (202 Accepted)
{
"jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"async": true
}
Progress (SSE at /api/v1/jobs/{jobId}/progress)
event: progress
data: {"phase":"processing","stage":"Detecting faces...","percent":40}
Final Result (via SSE)
{
"phase": "complete",
"percent": 100,
"result": {
"jobId": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
"downloadUrl": "/api/v1/download/{jobId}/group-photo_blurred.jpg",
"originalSize": 450000,
"processedSize": 420000,
"facesDetected": 3,
"faces": [
{"x": 100, "y": 50, "w": 80, "h": 80},
{"x": 300, "y": 60, "w": 75, "h": 75},
{"x": 500, "y": 55, "w": 85, "h": 85}
]
}
}
No Faces Detected
如果未找到人脸,结果会包含一条警告:
{
"phase": "complete",
"percent": 100,
"result": {
"facesDetected": 0,
"warning": "No faces detected in this image. Try increasing detection sensitivity."
}
}
Notes
- 需要安装
face-detection模型包(200-300 MB)。 - 输出格式会自动与输入格式一致。
faces数组包含每个检测到人脸的边界框坐标(x、y、width、height)。- 提高
sensitivity(接近 1.0)可检测更多人脸,包括部分遮挡的人脸。 - 通过自动解码支持 HEIC/HEIF、RAW、TGA、PSD、EXR 和 HDR 输入格式。