usamaehsan/controlnet-1.1-x-realistic-vision-v2.0:542a2f67

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usamaehsan /controlnet-1.1-x-realistic-vision-v2.0:542a2f67

Playground API

Input

image

*file

Input image

prompt

string

Shift + Return to add a new line

Prompt for the model

Default: "Animal"

structure

string

Structure to condition on

Default: "lineart"

num_samples

string

Number of samples (higher values may OOM)

Default: "1"

image_resolution

integer

Resolution of image

Default: 512

ddim_steps

integer

Steps

Default: 10

strength

number

Control strength

Default: 1

scale

number

(minimum: 0.1, maximum: 30)

Scale for classifier-free guidance

Default: 9

seed

integer

Seed

eta

number

Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise

Default: 0

preprocessor

string

preprocessor

Default: "Lineart"

preprocessor_resolution

integer

Preprocessor resolution

Default: 512

a_prompt

string

Shift + Return to add a new line

Additional text to be appended to prompt

Default: "Best quality, extremely detailed"

n_prompt

string

Shift + Return to add a new line

Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low qualityLongbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality

Negative prompt

Default: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality"

guessmode

boolean

Negative prompt

Default: false

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

npx create-replicate --model=usamaehsan/controlnet-1.1-x-realistic-vision-v2.0

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";
import fs from "node:fs";

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

Run usamaehsan/controlnet-1.1-x-realistic-vision-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "usamaehsan/controlnet-1.1-x-realistic-vision-v2.0:542a2f6729906f610b5a0656b4061b6f792f3044f1b86eca7ce7dee3258f025b",
  {
    input: {
      eta: 0,
      image: "https://replicate.delivery/pbxt/IrAdCMSMtw7yHM5RJNl2SQWPfpQIZx5Yog2fV29wB7xpEbyO/ceb71f061de43744a245456771d6f95d.jpg",
      scale: 5.76,
      prompt: "underwater kingdom",
      a_prompt: "Best quality, extremely detailed",
      n_prompt: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
      strength: 0.5,
      guessmode: false,
      structure: "lineart",
      ddim_steps: 10,
      num_samples: "1",
      preprocessor: "Lineart",
      image_resolution: 512,
      preprocessor_resolution: 512
    }
  }
);

// 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 usamaehsan/controlnet-1.1-x-realistic-vision-v2.0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "usamaehsan/controlnet-1.1-x-realistic-vision-v2.0:542a2f6729906f610b5a0656b4061b6f792f3044f1b86eca7ce7dee3258f025b",
    input={
        "eta": 0,
        "image": "https://replicate.delivery/pbxt/IrAdCMSMtw7yHM5RJNl2SQWPfpQIZx5Yog2fV29wB7xpEbyO/ceb71f061de43744a245456771d6f95d.jpg",
        "scale": 5.76,
        "prompt": "underwater kingdom",
        "a_prompt": "Best quality, extremely detailed",
        "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
        "strength": 0.5,
        "guessmode": False,
        "structure": "lineart",
        "ddim_steps": 10,
        "num_samples": "1",
        "preprocessor": "Lineart",
        "image_resolution": 512,
        "preprocessor_resolution": 512
    }
)
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 usamaehsan/controlnet-1.1-x-realistic-vision-v2.0 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": "usamaehsan/controlnet-1.1-x-realistic-vision-v2.0:542a2f6729906f610b5a0656b4061b6f792f3044f1b86eca7ce7dee3258f025b",
    "input": {
      "eta": 0,
      "image": "https://replicate.delivery/pbxt/IrAdCMSMtw7yHM5RJNl2SQWPfpQIZx5Yog2fV29wB7xpEbyO/ceb71f061de43744a245456771d6f95d.jpg",
      "scale": 5.76,
      "prompt": "underwater kingdom",
      "a_prompt": "Best quality, extremely detailed",
      "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
      "strength": 0.5,
      "guessmode": false,
      "structure": "lineart",
      "ddim_steps": 10,
      "num_samples": "1",
      "preprocessor": "Lineart",
      "image_resolution": 512,
      "preprocessor_resolution": 512
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-05-31T12:52:23.964781Z",
  "created_at": "2023-05-31T12:50:12.491286Z",
  "data_removed": false,
  "error": null,
  "id": "rp4lvtjervesfhepem3jinav7y",
  "input": {
    "image": "https://replicate.delivery/pbxt/IrAdCMSMtw7yHM5RJNl2SQWPfpQIZx5Yog2fV29wB7xpEbyO/ceb71f061de43744a245456771d6f95d.jpg",
    "scale": 5.76,
    "prompt": "underwater kingdom",
    "a_prompt": "Best quality, extremely detailed",
    "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
    "strength": 0.5,
    "structure": "lineart",
    "ddim_steps": 10,
    "num_samples": "1",
    "preprocessor": "Lineart",
    "image_resolution": 512,
    "preprocessor_resolution": 512
  },
  "logs": "Global seed set to 422866\nData shape for DDIM sampling is (1, 4, 64, 56), eta 0.0\nRunning DDIM Sampling with 10 timesteps\nDDIM Sampler:   0%|          | 0/10 [00:00<?, ?it/s]\nDDIM Sampler:  10%|█         | 1/10 [00:00<00:01,  5.66it/s]\nDDIM Sampler:  20%|██        | 2/10 [00:00<00:01,  6.12it/s]\nDDIM Sampler:  30%|███       | 3/10 [00:00<00:01,  6.28it/s]\nDDIM Sampler:  40%|████      | 4/10 [00:00<00:00,  6.47it/s]\nDDIM Sampler:  50%|█████     | 5/10 [00:00<00:00,  6.57it/s]\nDDIM Sampler:  60%|██████    | 6/10 [00:00<00:00,  6.62it/s]\nDDIM Sampler:  70%|███████   | 7/10 [00:01<00:00,  6.63it/s]\nDDIM Sampler:  80%|████████  | 8/10 [00:01<00:00,  6.51it/s]\nDDIM Sampler:  90%|█████████ | 9/10 [00:01<00:00,  6.56it/s]\nDDIM Sampler: 100%|██████████| 10/10 [00:01<00:00,  6.72it/s]\nDDIM Sampler: 100%|██████████| 10/10 [00:01<00:00,  6.54it/s]",
  "metrics": {
    "predict_time": 4.951756,
    "total_time": 131.473495
  },
  "output": [
    "https://replicate.delivery/pbxt/lCumeg6SHftNvkNhoPi5YnTKfuziMUHWi3YZawPpE6IPoeEEB/output_0.png",
    "https://replicate.delivery/pbxt/TksbCGtukwZ7BF4rAEe88PSTz3YGxHStKuN8fouoHU6HUPBRA/output_1.png"
  ],
  "started_at": "2023-05-31T12:52:19.013025Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/rp4lvtjervesfhepem3jinav7y",
    "cancel": "https://api.replicate.com/v1/predictions/rp4lvtjervesfhepem3jinav7y/cancel"
  },
  "version": "542a2f6729906f610b5a0656b4061b6f792f3044f1b86eca7ce7dee3258f025b"
}

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