bxclib2/flux_img2img – Run with an API on Replicate

Input

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

npx create-replicate --model=bxclib2/flux_img2img

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 bxclib2/flux_img2img using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "bxclib2/flux_img2img:0ce45202d83c6bd379dfe58f4c0c41e6cadf93ebbd9d938cc63cc0f2fcb729a5",
  {
    input: {
      seed: 0,
      image: "https://replicate.delivery/pbxt/LNejsmEhVDfW7iRdapoqzUhIyctYDkubGPAJKSruGY3XokjO/1.png",
      steps: 20,
      denoising: 0.75,
      scheduler: "simple",
      sampler_name: "euler",
      positive_prompt: "anime style"
    }
  }
);

// 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 bxclib2/flux_img2img using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "bxclib2/flux_img2img:0ce45202d83c6bd379dfe58f4c0c41e6cadf93ebbd9d938cc63cc0f2fcb729a5",
    input={
        "seed": 0,
        "image": "https://replicate.delivery/pbxt/LNejsmEhVDfW7iRdapoqzUhIyctYDkubGPAJKSruGY3XokjO/1.png",
        "steps": 20,
        "denoising": 0.75,
        "scheduler": "simple",
        "sampler_name": "euler",
        "positive_prompt": "anime style"
    }
)
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 bxclib2/flux_img2img 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": "0ce45202d83c6bd379dfe58f4c0c41e6cadf93ebbd9d938cc63cc0f2fcb729a5",
    "input": {
      "seed": 0,
      "image": "https://replicate.delivery/pbxt/LNejsmEhVDfW7iRdapoqzUhIyctYDkubGPAJKSruGY3XokjO/1.png",
      "steps": 20,
      "denoising": 0.75,
      "scheduler": "simple",
      "sampler_name": "euler",
      "positive_prompt": "anime style"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2024-08-03T10:04:07.835299Z",
  "created_at": "2024-08-03T09:58:43.499000Z",
  "data_removed": false,
  "error": null,
  "id": "h3z0sejy5drgj0ch2ypvj7k6g4",
  "input": {
    "seed": 0,
    "image": "https://replicate.delivery/pbxt/LNejsmEhVDfW7iRdapoqzUhIyctYDkubGPAJKSruGY3XokjO/1.png",
    "steps": 20,
    "denoising": 0.75,
    "scheduler": "simple",
    "sampler_name": "euler",
    "positive_prompt": "anime style"
  },
  "logs": "1222009109159122718\nRequested to load FluxClipModel_\nLoading 1 new model\nRequested to load AutoencodingEngine\nLoading 1 new model\nRequested to load Flux\nLoading 1 new model\n  0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:11,  1.59it/s]\n 10%|█         | 2/20 [00:01<00:14,  1.24it/s]\n 15%|█▌        | 3/20 [00:02<00:14,  1.16it/s]\n 20%|██        | 4/20 [00:03<00:14,  1.12it/s]\n 25%|██▌       | 5/20 [00:04<00:13,  1.11it/s]\n 30%|███       | 6/20 [00:05<00:12,  1.09it/s]\n 35%|███▌      | 7/20 [00:06<00:11,  1.09it/s]\n 40%|████      | 8/20 [00:07<00:11,  1.08it/s]\n 45%|████▌     | 9/20 [00:08<00:10,  1.08it/s]\n 50%|█████     | 10/20 [00:09<00:09,  1.07it/s]\n 55%|█████▌    | 11/20 [00:09<00:08,  1.07it/s]\n 60%|██████    | 12/20 [00:10<00:07,  1.07it/s]\n 65%|██████▌   | 13/20 [00:11<00:06,  1.07it/s]\n 70%|███████   | 14/20 [00:12<00:05,  1.07it/s]\n 75%|███████▌  | 15/20 [00:13<00:04,  1.07it/s]\n 80%|████████  | 16/20 [00:14<00:03,  1.07it/s]\n 85%|████████▌ | 17/20 [00:15<00:02,  1.07it/s]\n 90%|█████████ | 18/20 [00:16<00:01,  1.07it/s]\n 95%|█████████▌| 19/20 [00:17<00:00,  1.07it/s]\n100%|██████████| 20/20 [00:18<00:00,  1.07it/s]\n100%|██████████| 20/20 [00:18<00:00,  1.09it/s]",
  "metrics": {
    "predict_time": 22.895329983,
    "total_time": 324.336299
  },
  "output": "https://replicate.delivery/pbxt/vwtFRvPZCEp4H5cwOzpKrqUuIdNRwC1X17vQj4inubilyuzE/out.png",
  "started_at": "2024-08-03T10:03:44.939969Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/h3z0sejy5drgj0ch2ypvj7k6g4",
    "cancel": "https://api.replicate.com/v1/predictions/h3z0sejy5drgj0ch2ypvj7k6g4/cancel"
  },
  "version": "0ce45202d83c6bd379dfe58f4c0c41e6cadf93ebbd9d938cc63cc0f2fcb729a5"
}

Generated in

22.9 seconds

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Run time and cost

This model costs approximately $0.030 to run on Replicate, or 33 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 31 seconds. The predict time for this model varies significantly based on the inputs.