Prediction

Model

adirik/t2i-adapter-sdxl-openpose:6e87d127

gk2lem3bosrbmdz5itfokdtvhe

Status

Succeeded

Source

Web

Hardware

A40

Total duration

1m 56s

Created

about 2 years ago

Webhook

–

Input

image: https://replicate.delivery/pbxt/JbnAELoOIkMhteHqHJnRfB0ATKgRdZqLjdIgcZB34WlRNCNF/people.jpg
prompt: A couple, 4k photo, highly detailed
negative_prompt: anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured
num_inference_steps: 30
adapter_conditioning_scale: 0.9
adapter_conditioning_factor: 0.9
guidance_scale: 7.5
num_samples: 1
scheduler: K_EULER_ANCESTRAL

{
  "adapter_conditioning_factor": 0.9,
  "adapter_conditioning_scale": 0.9,
  "guidance_scale": 7.5,
  "image": "https://replicate.delivery/pbxt/JbnAELoOIkMhteHqHJnRfB0ATKgRdZqLjdIgcZB34WlRNCNF/people.jpg",
  "negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
  "num_inference_steps": 30,
  "num_samples": 1,
  "prompt": "A couple, 4k photo, highly detailed",
  "scheduler": "K_EULER_ANCESTRAL"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_BZQ**********************************

This is your API token. Keep it to yourself.

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 adirik/t2i-adapter-sdxl-openpose using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "adirik/t2i-adapter-sdxl-openpose:6e87d127eb184d446b8cec0c2b034b3c7b24d08e211ec28247cdeb2e0a460670",
  {
    input: {
      adapter_conditioning_factor: 0.9,
      adapter_conditioning_scale: 0.9,
      guidance_scale: 7.5,
      image: "https://replicate.delivery/pbxt/JbnAELoOIkMhteHqHJnRfB0ATKgRdZqLjdIgcZB34WlRNCNF/people.jpg",
      negative_prompt: "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
      num_inference_steps: 30,
      num_samples: 1,
      prompt: "A couple, 4k photo, highly detailed",
      scheduler: "K_EULER_ANCESTRAL"
    }
  }
);

// 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=r8_BZQ**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run adirik/t2i-adapter-sdxl-openpose using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "adirik/t2i-adapter-sdxl-openpose:6e87d127eb184d446b8cec0c2b034b3c7b24d08e211ec28247cdeb2e0a460670",
    input={
        "adapter_conditioning_factor": 0.9,
        "adapter_conditioning_scale": 0.9,
        "guidance_scale": 7.5,
        "image": "https://replicate.delivery/pbxt/JbnAELoOIkMhteHqHJnRfB0ATKgRdZqLjdIgcZB34WlRNCNF/people.jpg",
        "negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
        "num_inference_steps": 30,
        "num_samples": 1,
        "prompt": "A couple, 4k photo, highly detailed",
        "scheduler": "K_EULER_ANCESTRAL"
    }
)

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

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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=r8_BZQ**********************************

This is your API token. Keep it to yourself.

Run adirik/t2i-adapter-sdxl-openpose 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": "adirik/t2i-adapter-sdxl-openpose:6e87d127eb184d446b8cec0c2b034b3c7b24d08e211ec28247cdeb2e0a460670",
    "input": {
      "adapter_conditioning_factor": 0.9,
      "adapter_conditioning_scale": 0.9,
      "guidance_scale": 7.5,
      "image": "https://replicate.delivery/pbxt/JbnAELoOIkMhteHqHJnRfB0ATKgRdZqLjdIgcZB34WlRNCNF/people.jpg",
      "negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
      "num_inference_steps": 30,
      "num_samples": 1,
      "prompt": "A couple, 4k photo, highly detailed",
      "scheduler": "K_EULER_ANCESTRAL"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "gk2lem3bosrbmdz5itfokdtvhe",
  "model": "adirik/t2i-adapter-sdxl-openpose",
  "version": "6e87d127eb184d446b8cec0c2b034b3c7b24d08e211ec28247cdeb2e0a460670",
  "input": {
    "adapter_conditioning_factor": 0.9,
    "adapter_conditioning_scale": 0.9,
    "guidance_scale": 7.5,
    "image": "https://replicate.delivery/pbxt/JbnAELoOIkMhteHqHJnRfB0ATKgRdZqLjdIgcZB34WlRNCNF/people.jpg",
    "negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured",
    "num_inference_steps": 30,
    "num_samples": 1,
    "prompt": "A couple, 4k photo, highly detailed",
    "scheduler": "K_EULER_ANCESTRAL"
  },
  "logs": "0%|          | 0/30 [00:00<?, ?it/s]\n  3%|▎         | 1/30 [00:00<00:04,  6.05it/s]\n  7%|▋         | 2/30 [00:00<00:06,  4.50it/s]\n 10%|█         | 3/30 [00:00<00:06,  4.12it/s]\n 13%|█▎        | 4/30 [00:00<00:06,  3.97it/s]\n 17%|█▋        | 5/30 [00:01<00:06,  3.89it/s]\n 20%|██        | 6/30 [00:01<00:06,  3.83it/s]\n 23%|██▎       | 7/30 [00:01<00:06,  3.80it/s]\n 27%|██▋       | 8/30 [00:02<00:05,  3.78it/s]\n 30%|███       | 9/30 [00:02<00:05,  3.77it/s]\n 33%|███▎      | 10/30 [00:02<00:05,  3.76it/s]\n 37%|███▋      | 11/30 [00:02<00:05,  3.74it/s]\n 40%|████      | 12/30 [00:03<00:04,  3.74it/s]\n 43%|████▎     | 13/30 [00:03<00:04,  3.74it/s]\n 47%|████▋     | 14/30 [00:03<00:04,  3.73it/s]\n 50%|█████     | 15/30 [00:03<00:04,  3.73it/s]\n 53%|█████▎    | 16/30 [00:04<00:03,  3.73it/s]\n 57%|█████▋    | 17/30 [00:04<00:03,  3.73it/s]\n 60%|██████    | 18/30 [00:04<00:03,  3.72it/s]\n 63%|██████▎   | 19/30 [00:04<00:02,  3.73it/s]\n 67%|██████▋   | 20/30 [00:05<00:02,  3.72it/s]\n 70%|███████   | 21/30 [00:05<00:02,  3.72it/s]\n 73%|███████▎  | 22/30 [00:05<00:02,  3.72it/s]\n 77%|███████▋  | 23/30 [00:06<00:01,  3.73it/s]\n 80%|████████  | 24/30 [00:06<00:01,  3.72it/s]\n 83%|████████▎ | 25/30 [00:06<00:01,  3.72it/s]\n 87%|████████▋ | 26/30 [00:06<00:01,  3.72it/s]\n 90%|█████████ | 27/30 [00:07<00:00,  3.71it/s]\n 93%|█████████▎| 28/30 [00:07<00:00,  3.72it/s]\n 97%|█████████▋| 29/30 [00:07<00:00,  3.72it/s]\n100%|██████████| 30/30 [00:07<00:00,  3.72it/s]\n100%|██████████| 30/30 [00:07<00:00,  3.78it/s]",
  "output": [
    "https://pbxt.replicate.delivery/zLV4rptJWbKOKpMauzP4ASa0ZwMhs29NYD4Ckdy3uhSpUoaE/out-preprocessed.png",
    "https://pbxt.replicate.delivery/nuE2A9YWRkLaN1ptkgad1JeHtYJwUWAt6p7Bie0fYDcNlCVjA/out-0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-10-03T18:49:23.572065Z",
  "started_at": "2023-10-03T18:51:06.68795Z",
  "completed_at": "2023-10-03T18:51:19.116216Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/gk2lem3bosrbmdz5itfokdtvhe/cancel",
    "get": "https://api.replicate.com/v1/predictions/gk2lem3bosrbmdz5itfokdtvhe"
  },
  "metrics": {
    "predict_time": 12.428266,
    "total_time": 115.544151
  }
}

Generated in

12.4 seconds

Tweak it Report