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aliyun-wan-digital-human

aliyun-wan-digital-human

github.com/cinienceCreative & media39693 installsUpdated 11w ago
Repository

About aliyun-wan-digital-human

A provider skill for preparing Model Studio digital-human video requests from an image and audio. It is intended for workflows that create speaking, singing, or presenting characters, with image detection before generation.

Key features

  1. 01Validates images before generation
  2. 02Generates video from image and audio
  3. 03Supports talk, sing, and perform scenarios
  4. 04Selects 480P or 720P resolution

Use cases

  1. 01Creating a speaking character from a portrait and voice clip
  2. 02Producing a singing or performing character video

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/cinience/alicloud-skills --skill aliyun-wan-digital-human

After installing, type/aliyun-wan-digital-humanin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
sources.md
scripts/
prepare_digital_human_request.py

Details

From the project README

Category: provider

Model Studio Digital Human

Validation

mkdir -p output/aliyun-wan-digital-human
python -m py_compile skills/ai/video/aliyun-wan-digital-human/scripts/prepare_digital_human_request.py && echo "py_compile_ok" > output/aliyun-wan-digital-human/validate.txt

Pass criteria: command exits 0 and output/aliyun-wan-digital-human/validate.txt is generated.

Output And Evidence

  • Save normalized request payloads, chosen resolution, and task polling snapshots under output/aliyun-wan-digital-human/.
  • Record image/audio URLs and whether the input image passed detection.

Use this skill for image + audio driven speaking, singing, or presenting characters.

Critical model names

Use these exact model strings:

  • wan2.2-s2v-detect
  • wan2.2-s2v

Selection guidance:

  • Run wan2.2-s2v-detect first to validate the image.
  • Use wan2.2-s2v for the actual video generation job.

Prerequisites

  • China mainland (Beijing) only.
  • Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.
  • Input audio should contain clear speech or singing, and input image should depict a clear subject.

Normalized interface (video.digital_human)

Detect Request
  • model (string, optional): default wan2.2-s2v-detect
  • image_url (string, required)
Generate Request
  • model (string, optional): default wan2.2-s2v
  • image_url (string, required)
  • audio_url (string, required)
  • resolution (string, optional): 480P or 720P
  • scenario (string, optional): talk, sing, or perform
Response
  • task_id (string)
  • task_status (string)
  • video_url (string, when finished)

Quick start

python skills/ai/video/aliyun-wan-digital-human/scripts/prepare_digital_human_request.py \
  --image-url "https://example.com/anchor.png" \
  --audio-url "https://example.com/voice.mp3" \
  --resolution 720P \
  --scenario talk

Operational guidance

  • Use a portrait, half-body, or full-body image with a clear face and stable framing.
  • Match audio length to the desired output duration; the output follows the audio length up to the model limit.
  • Keep image and audio as public HTTP/HTTPS URLs.
  • If the image fails detection, do not proceed directly to video generation.

Output location

  • Default output: output/aliyun-wan-digital-human/request.json
  • Override base dir with OUTPUT_DIR.

References

  • references/sources.md

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