aliyun-wan-digital-human

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Category: provider

分类：提供商

Model Studio Digital Human

Model Studio 数字人

Validation

验证

bash

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.

bash

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

通过条件：命令退出码为0，且成功生成

output/aliyun-wan-digital-human/validate.txt

文件。

Output And Evidence

输出与证明

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.

将标准化的请求载荷、选择的分辨率、任务轮询快照保存到
```
output/aliyun-wan-digital-human/
```
目录下。
记录图像/音频URL，以及输入图像是否通过检测。

本技能可实现图像+音频驱动的人物说话、唱歌或演示效果。

Critical model names

关键模型名称

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.

请使用以下准确的模型字符串：

```
wan2.2-s2v-detect
```
```
wan2.2-s2v
```

选择指南：

首先运行
```
wan2.2-s2v-detect
```
验证输入图像是否合规。
使用
```
wan2.2-s2v
```
执行实际的视频生成任务。

Prerequisites

前置条件

China mainland (Beijing) only.

Set

DASHSCOPE_API_KEY

in your environment, or add

dashscope_api_key

~/.alibabacloud/credentials

Input audio should contain clear speech or singing, and input image should depict a clear subject.

仅支持中国大陆（北京）区域。

在环境变量中设置

DASHSCOPE_API_KEY

，或者在

~/.alibabacloud/credentials

文件中添加

dashscope_api_key

配置。

输入音频需包含清晰的语音或歌声，输入图像需呈现清晰的人物主体。

Normalized interface (video.digital_human)

标准化接口（video.digital_human）

Detect Request

检测请求

```
model
```
(string, optional): default
```
wan2.2-s2v-detect
```
```
image_url
```
(string, required)

```
model
```
（字符串，可选）：默认值为
```
wan2.2-s2v-detect
```
```
image_url
```
（字符串，必填）

Generate Request

生成请求

```
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
```

```
model
```
（字符串，可选）：默认值为
```
wan2.2-s2v
```
```
image_url
```
（字符串，必填）
```
audio_url
```
（字符串，必填）
```
resolution
```
（字符串，可选）：可选值为
```
480P
```
或
```
720P
```
```
scenario
```
（字符串，可选）：可选值为
```
talk
```
、
```
sing
```
或
```
perform
```

Response

返回结果

```
task_id
```
(string)
```
task_status
```
(string)
```
video_url
```
(string, when finished)

```
task_id
```
（字符串）
```
task_status
```
（字符串）
```
video_url
```
（字符串，任务完成时返回）

Quick start

快速开始

bash

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

bash

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

操作指南

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.

建议使用人脸清晰、构图稳定的肖像、半身或全身图像。
音频时长需与期望的输出时长匹配，输出视频时长与音频一致，最长不超过模型限制。
图像和音频需为公网可访问的HTTP/HTTPS链接。
如果图像未通过检测，请勿直接发起视频生成请求。

Output location

输出位置

Default output:

output/aliyun-wan-digital-human/request.json

Override base dir with
```
OUTPUT_DIR
```
.

默认输出路径：

output/aliyun-wan-digital-human/request.json

可通过
```
OUTPUT_DIR
```
环境变量覆盖基础输出目录。

References

参考资料

```
references/sources.md
```

```
references/sources.md
```