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face-transform

face-transform

Analyze and transform faces via AceDataCloud API. Use when detecting face keypoints, beautifying portraits, aging/de-aging faces, swapping genders, replacing faces between photos, creating cartoon avatars, or detecting liveness. Provides 7 specialized face APIs.

Independent GitHub snapshot · Automated classification · Original documentation governs

Aacedatacloud / skillsApache-2.0

Documentation de la Skill

GitHub

name: face-transform description: Analyze and transform faces via AceDataCloud API. Use when detecting face keypoints, beautifying portraits, aging/de-aging faces, swapping genders, replacing faces between photos, creating cartoon avatars, or detecting liveness. Provides 7 specialized face APIs. license: Apache-2.0 metadata: author: acedatacloud version: "1.0" compatibility: Requires ACEDATACLOUD_API_TOKEN in .env file (get an API key at https://platform.acedata.cloud/console/applications).

Face Transform

Analyze and transform faces through AceDataCloud's Face API suite.

First-time setup

  1. Install the official Skill with clawhub install @acedatacloud/face-transform. Check that the ClawHub publisher is @acedatacloud.
  2. Sign in at AceDataCloud → Applications, open General application, and check Face Transform access, balance, and current pricing. Copy its API key, or select Manage Keys → Create for a separate key. Copy the key value without Bearer ; a platform-... management token is not a service API key.
  3. If you enable Allowed APIs restrictions, include /face/analyze for the first example; other face actions need their own access. Advanced workflows below may call additional routes.
  4. On the OpenClaw Gateway host, put ACEDATACLOUD_API_TOKEN=your_api_key_here in ~/.openclaw/.env, then restart the Gateway and start a new session. For a direct terminal test, run export ACEDATACLOUD_API_TOKEN="your_api_key_here" in that shell. Never put the key in a prompt or commit an .env file.
  5. Run the Quick Start below. If this workflow returns a task ID, query that same task until it finishes; do not submit the same billable request again just to check progress.

Illustrated key setup, first run, and troubleshooting · Token details

Quick Start

curl -X POST https://api.acedata.cloud/face/analyze \
  -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"image_url": "https://cdn.acedata.cloud/lrbtcn.jpg"}'

Available APIs

EndpointPurposeDescription
POST /face/analyzeFace DetectionDetect face keypoints (90+ points per face)
POST /face/beautifyBeautificationApply beauty/decoration effects
POST /face/change-ageAge TransformMake a face look older or younger
POST /face/change-genderGender SwapTransform facial gender characteristics
POST /face/swapFace SwapReplace one person's face with another
POST /face/cartoonCartoon StyleConvert portrait to animated/cartoon style
POST /face/detect-liveLiveness CheckDetect if a face image is from a live person

Workflows

1. Face Analysis

Detect faces and extract 90+ keypoints per face.

POST /face/analyze
{
  "image_url": "https://example.com/photo.jpg"
}

Response includes detailed keypoints: nose, mouth, left_eye, right_eye, left_eyebrow, right_eyebrow, contour — each as arrays of {x, y} coordinates.

2. Face Beautification

POST /face/beautify
{
  "image_url": "https://example.com/portrait.jpg"
}

3. Age Transformation

age_infos is required — one entry per face, each carrying the target age.

POST /face/change-age
{
  "image_url": "https://example.com/portrait.jpg",
  "age_infos": [{ "age": 60 }]
}

4. Gender Swap

gender_infos is required. gender is 0 to turn a male face female, 1 for the reverse.

POST /face/change-gender
{
  "image_url": "https://example.com/portrait.jpg",
  "gender_infos": [{ "gender": 1 }]
}

5. Face Swap

Replace the face in the target image with the face from the source.

POST /face/swap
{
  "source_image_url": "https://example.com/source-face.jpg",
  "target_image_url": "https://example.com/target-person.jpg"
}

6. Cartoon Style

POST /face/cartoon
{
  "image_url": "https://example.com/portrait.jpg"
}

7. Liveness Detection

POST /face/detect-live
{
  "image_url": "https://example.com/face-photo.jpg"
}

Parameters

Common

ParameterRequiredDescription
image_urlYes (all except /face/swap)Source face image URL

/face/change-age

ParameterRequiredDescription
age_infosYesArray of { "age": <number> }, one per face. Omitting it returns 400 age_infos is required

/face/change-gender

ParameterRequiredDescription
gender_infosYesArray of { "gender": 0|1 } — 0 male→female, 1 female→male. Each entry also accepts an optional face_rect

/face/swap

ParameterRequiredDescription
source_image_urlYesURL of the face to use (replaces the face)
target_image_urlYesURL of the image to put the face onto
callback_urlNoWebhook URL for async delivery
timeoutNoMax wait time in seconds (default: 120)

/face/beautify

ParameterRequiredDescription
image_urlYesImage URL
smoothingNoSkin smoothing 0–100 (default: 10)
whiteningNoWhitening 0–100 (default: 30)
face_liftingNoFace slimming 0–100 (default: 70)
eye_enlargingNoEye enlarging 0–100 (default: 70)

/face/analyze

ParameterRequiredDescription
image_urlYesImage URL
modeNo0 = all faces (default), 1 = largest face only
face_model_versionNoAlgorithm version (recommended: 3.0)
need_rotate_detectionNo0 = disabled (default), 1 = enabled

Gotchas

  • All face APIs return results synchronously. /face/swap additionally supports an optional callback_url parameter for async delivery (pass it to receive the result via webhook instead of waiting inline)
  • Face analyze returns 90+ keypoints per detected face, supporting multiple faces in one image
  • Face swap uses source_image_url (the face to apply) and target_image_url (the body to apply it to)
  • All APIs are currently in Alpha stage — interfaces may evolve
  • Images should contain clearly visible, front-facing faces for best results
  • Liveness detection helps distinguish live photos from printed/screen photos
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