fofr/lcm-animation:2feccdde – Run with an API on Replicate

Version

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fofr /lcm-animation:2feccdde

Input

start_prompt

string

Shift + Return to add a new line

Self-portrait oil painting, a beautiful cyborg with golden hair, 8kSelf-portrait oil painting, a beautiful cyborg with golden hair, 8k

Prompt to start with, if not using an image

Default: "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"

end_prompt

string

Shift + Return to add a new line

Self-portrait watercolour, a beautiful cyborg with purple hair, 8kSelf-portrait watercolour, a beautiful cyborg with purple hair, 8k

Prompt to animate towards

Default: "Self-portrait watercolour, a beautiful cyborg with purple hair, 8k"

image

file

Starting image if not using a prompt

width

integer

Width of output. Lower if out of memory

Default: 512

height

integer

Height of output. Lower if out of memory

Default: 512

iterations

integer

Number of times to repeat the img2img pipeline

Default: 12

prompt_strength

number

(minimum: 0, maximum: 1)

Prompt strength when using img2img. 1.0 corresponds to full destruction of information in image

Default: 0.2

num_inference_steps

integer

(minimum: 1, maximum: 50)

Number of denoising steps. Recommend 1 to 8 steps.

Default: 8

use_canny_control_net

boolean

Use canny edge detection to guide animation

Default: true

controlnet_conditioning_scale

number

(minimum: 0.1, maximum: 4)

Controlnet conditioning scale

Default: 2

control_guidance_start

number

(minimum: 0, maximum: 1)

Controlnet start

Default: 0

control_guidance_end

number

(minimum: 0, maximum: 1)

Controlnet end

Default: 1

canny_low_threshold

number

(minimum: 1, maximum: 255)

Canny low threshold

Default: 100

canny_high_threshold

number

(minimum: 1, maximum: 255)

Canny high threshold

Default: 200

zoom_increment

integer

(minimum: 0, maximum: 4)

Zoom increment percentage for each frame

Default: 0

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 8

seed

integer

Random seed. Leave blank to randomize the seed

return_frames

boolean

Return a tar file with all the frames alongside the video

Default: false

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

npx create-replicate --model=fofr/lcm-animation

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 fofr/lcm-animation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/lcm-animation:2feccddefd495a84462b96ad71bf69cbd4d8ad3cd88f6903a9ddf3383b6df972",
  {
    input: {
      width: 512,
      height: 512,
      end_prompt: "Self-portrait watercolour, a beautiful cyborg with purple hair, 8k",
      iterations: 12,
      start_prompt: "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
      return_frames: false,
      guidance_scale: 8,
      zoom_increment: 0,
      prompt_strength: 0.2,
      canny_low_threshold: 100,
      num_inference_steps: 8,
      canny_high_threshold: 200,
      control_guidance_end: 1,
      use_canny_control_net: true,
      control_guidance_start: 0,
      controlnet_conditioning_scale: 2
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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 fofr/lcm-animation using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/lcm-animation:2feccddefd495a84462b96ad71bf69cbd4d8ad3cd88f6903a9ddf3383b6df972",
    input={
        "width": 512,
        "height": 512,
        "end_prompt": "Self-portrait watercolour, a beautiful cyborg with purple hair, 8k",
        "iterations": 12,
        "start_prompt": "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
        "return_frames": False,
        "guidance_scale": 8,
        "zoom_increment": 0,
        "prompt_strength": 0.2,
        "canny_low_threshold": 100,
        "num_inference_steps": 8,
        "canny_high_threshold": 200,
        "control_guidance_end": 1,
        "use_canny_control_net": True,
        "control_guidance_start": 0,
        "controlnet_conditioning_scale": 2
    }
)
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 fofr/lcm-animation 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": "fofr/lcm-animation:2feccddefd495a84462b96ad71bf69cbd4d8ad3cd88f6903a9ddf3383b6df972",
    "input": {
      "width": 512,
      "height": 512,
      "end_prompt": "Self-portrait watercolour, a beautiful cyborg with purple hair, 8k",
      "iterations": 12,
      "start_prompt": "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
      "return_frames": false,
      "guidance_scale": 8,
      "zoom_increment": 0,
      "prompt_strength": 0.2,
      "canny_low_threshold": 100,
      "num_inference_steps": 8,
      "canny_high_threshold": 200,
      "control_guidance_end": 1,
      "use_canny_control_net": true,
      "control_guidance_start": 0,
      "controlnet_conditioning_scale": 2
    }
  }' \
  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.