Prediction

Model

fermatresearch/flux-controlnet-inpaint:46ae77d1

9gv8ma1xzxrj60cj0jdrjsgp9c

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

1m 32s

Created

about 1 year ago

Webhook

–

Input

prompt: Professional photography of a fox sitting on a bench
conditioning_scale: 0.5
image: https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png
control_image: https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png
mask: https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png
strength: 0.8
guidance_scale: 3.5
enable_hyper_flux_8_step: true
num_inference_steps: 8
output_format: jpg
output_quality: 100
lora_scale: 0.8

{
  "conditioning_scale": 0.5,
  "control_image": "https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png",
  "enable_hyper_flux_8_step": true,
  "guidance_scale": 3.5,
  "image": "https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png",
  "lora_scale": 0.8,
  "mask": "https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png",
  "num_inference_steps": 8,
  "output_format": "jpg",
  "output_quality": 100,
  "prompt": "Professional photography of a fox sitting on a bench",
  "strength": 0.8
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_CxD**********************************

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 fermatresearch/flux-controlnet-inpaint using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fermatresearch/flux-controlnet-inpaint:46ae77d1d148dca1bd61c1215e99ee692c4cf01289a2bba681b14a58c04bda8f",
  {
    input: {
      conditioning_scale: 0.5,
      control_image: "https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png",
      enable_hyper_flux_8_step: true,
      guidance_scale: 3.5,
      image: "https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png",
      lora_scale: 0.8,
      mask: "https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png",
      num_inference_steps: 8,
      output_format: "jpg",
      output_quality: 100,
      prompt: "Professional photography of a fox sitting on a bench",
      strength: 0.8
    }
  }
);

// 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_CxD**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run fermatresearch/flux-controlnet-inpaint using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fermatresearch/flux-controlnet-inpaint:46ae77d1d148dca1bd61c1215e99ee692c4cf01289a2bba681b14a58c04bda8f",
    input={
        "conditioning_scale": 0.5,
        "control_image": "https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png",
        "enable_hyper_flux_8_step": True,
        "guidance_scale": 3.5,
        "image": "https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png",
        "lora_scale": 0.8,
        "mask": "https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png",
        "num_inference_steps": 8,
        "output_format": "jpg",
        "output_quality": 100,
        "prompt": "Professional photography of a fox sitting on a bench",
        "strength": 0.8
    }
)

# 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_CxD**********************************

This is your API token. Keep it to yourself.

Run fermatresearch/flux-controlnet-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": "fermatresearch/flux-controlnet-inpaint:46ae77d1d148dca1bd61c1215e99ee692c4cf01289a2bba681b14a58c04bda8f",
    "input": {
      "conditioning_scale": 0.5,
      "control_image": "https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png",
      "enable_hyper_flux_8_step": true,
      "guidance_scale": 3.5,
      "image": "https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png",
      "lora_scale": 0.8,
      "mask": "https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png",
      "num_inference_steps": 8,
      "output_format": "jpg",
      "output_quality": 100,
      "prompt": "Professional photography of a fox sitting on a bench",
      "strength": 0.8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "9gv8ma1xzxrj60cj0jdrjsgp9c",
  "model": "fermatresearch/flux-controlnet-inpaint",
  "version": "46ae77d1d148dca1bd61c1215e99ee692c4cf01289a2bba681b14a58c04bda8f",
  "input": {
    "conditioning_scale": 0.5,
    "control_image": "https://replicate.delivery/pbxt/LdzOBqGI9FyIIPZOyOBYToYndRLXelYBSqOP1XJlE5Tq5up9/output%20%283%29.png",
    "enable_hyper_flux_8_step": true,
    "guidance_scale": 3.5,
    "image": "https://replicate.delivery/pbxt/LdzOC2USRj4omEK2igawxoYUPG6hJ2RfRZS2TZXiqSEkybYs/output%20%283%29.png",
    "lora_scale": 0.8,
    "mask": "https://replicate.delivery/pbxt/LdzOC0eYgmiQxsZntL8aUwyQlLjtXQuhmMrXrOUbpMESw11v/output%20%282%29.png",
    "num_inference_steps": 8,
    "output_format": "jpg",
    "output_quality": 100,
    "prompt": "Professional photography of a fox sitting on a bench",
    "strength": 0.8
  },
  "logs": "Using seed: 28712\n  0%|          | 0/7 [00:00<?, ?it/s]\n 14%|█▍        | 1/7 [00:00<00:04,  1.37it/s]\n 29%|██▊       | 2/7 [00:01<00:03,  1.53it/s]\n 43%|████▎     | 3/7 [00:01<00:02,  1.58it/s]\n 57%|█████▋    | 4/7 [00:02<00:01,  1.61it/s]\n 71%|███████▏  | 5/7 [00:03<00:01,  1.62it/s]\n 86%|████████▌ | 6/7 [00:03<00:00,  1.63it/s]\n100%|██████████| 7/7 [00:04<00:00,  1.75it/s]\n100%|██████████| 7/7 [00:04<00:00,  1.65it/s]",
  "output": [
    "https://replicate.delivery/yhqm/xhIBrigTM8LAGt3lqX0U6H4adPPU7JBSPN22ehX1bYsJyCvJA/out-0.jpg"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-09-18T10:08:55.807Z",
  "started_at": "2024-09-18T10:10:16.704686Z",
  "completed_at": "2024-09-18T10:10:27.646617Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/9gv8ma1xzxrj60cj0jdrjsgp9c/cancel",
    "get": "https://api.replicate.com/v1/predictions/9gv8ma1xzxrj60cj0jdrjsgp9c",
    "web": "https://replicate.com/p/9gv8ma1xzxrj60cj0jdrjsgp9c"
  },
  "metrics": {
    "predict_time": 10.94193154,
    "total_time": 91.839617
  }
}

Generated in

10.9 seconds

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