andreasjansson/wan-1.3b-inpaint:e1357540 – Run with an API on Replicate

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andreasjansson /wan-1.3b-inpaint:e1357540

Playground API

Input

prompt

*string

Shift + Return to add a new line

Prompt for inpainting the masked area

input_video

*file

Original video to be inpainted

mask_video

file

Mask video (white areas will be inpainted). Leave blank for video-to-video

negative_prompt

string

Shift + Return to add a new line

Negative prompt

Default: ""

strength

number

(minimum: 0, maximum: 1)

Strength of inpainting effect, 1.0 is full regeneration

Default: 0.8

guide_scale

number

(minimum: 1, maximum: 15)

Guidance scale for prompt adherence

Default: 5

sampling_steps

integer

(minimum: 20, maximum: 100)

Number of sampling steps

Default: 50

inpaint_fixup_steps

integer

(minimum: 0, maximum: 10)

Number of steps for final inpaint fixup. Ignored when in video-to-video mode (when mask_video is empty)

Default: 0

expand_mask

integer

(minimum: 0, maximum: 100)

Expand the mask by a number of pixels

Default: 10

frames_per_second

integer

(minimum: 5, maximum: 30)

Output video FPS

Default: 16

seed

integer

Random seed. Leave blank for random

Default: -1

Run this model in Node.js with one line of code:

npx create-replicate --model=andreasjansson/wan-1.3b-inpaint

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run andreasjansson/wan-1.3b-inpaint using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/wan-1.3b-inpaint:e13575409c367ae13791da4093927e7ef5e6b309f89d62b71d5fb6885bf04ee2",
  {
    input: {
      seed: -1,
      strength: 0.8,
      expand_mask: 10,
      guide_scale: 5,
      sampling_steps: 50,
      negative_prompt: "",
      frames_per_second: 16,
      inpaint_fixup_steps: 0
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run andreasjansson/wan-1.3b-inpaint using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/wan-1.3b-inpaint:e13575409c367ae13791da4093927e7ef5e6b309f89d62b71d5fb6885bf04ee2",
    input={
        "seed": -1,
        "strength": 0.8,
        "expand_mask": 10,
        "guide_scale": 5,
        "sampling_steps": 50,
        "negative_prompt": "",
        "frames_per_second": 16,
        "inpaint_fixup_steps": 0
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run andreasjansson/wan-1.3b-inpaint using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "e13575409c367ae13791da4093927e7ef5e6b309f89d62b71d5fb6885bf04ee2",
    "input": {
      "seed": -1,
      "strength": 0.8,
      "expand_mask": 10,
      "guide_scale": 5,
      "sampling_steps": 50,
      "negative_prompt": "",
      "frames_per_second": 16,
      "inpaint_fixup_steps": 0
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

No output yet! Press "Submit" to start a prediction.