Muscling | Trending Video Effects API

Muscling Effect

Requirements

Number of Images

Mandatory
Only one image upload supported

Number of People

Supports realistic style single person photos

Image Requirements

The effect is better when the person is half body, not showing hands, and the clothing is non high necked

Prompt

Mandatory
Format should remain unchanged as much as possible
If custom requirements exist, modify the prompt without altering the structure and majority of the content

Effect Boundaries

When a character wears high necked clothes or multiple pieces of clothing stacked together, there may be situations where they undress uncleanly
When the character exposes their hands, there may be blurred undressing movements or broken hands in the final frame

Best Practices

Use clear, front-facing photos
Ensure subject is clearly visible
Use half-body shots without showing hands
Avoid high-necked clothing
Keep the default prompt structure

Muscling API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/video-effects/muscling with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Muscling below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/video-effects/muscling" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "image": "https://example.com/your-input.jpg"
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("video-effects/muscling", {
        "image": "https://example.com/your-input.jpg"
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "video-effects/muscling",
    {
    "image": "https://example.com/your-input.jpg"
}
)

print(output["outputs"][0])  # → URL of the generated output

Muscling API — Frequently asked questions

What is the Muscling API?

Muscling is a Video Effects model for AI inference, exposed as a REST API on WaveSpeedAI. Turn photos into 3s Image-to-Video muscle-effect clips with realistic anatomy, natural motion, and expressive emotion. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Muscling API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/video-effects/video-effects-muscling.

How much does Muscling cost per run?

Muscling starts at $0.20 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Muscling accept?

Key inputs: `image`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/video-effects/video-effects-muscling.

How long does Muscling take to generate?

Average end-to-end generation time on WaveSpeedAI is around 98 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Muscling outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Video Effects). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

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