Prediction

Model

fermatresearch/sdxl-controlnet-lora-inpaint:35c927ab

pj64fk3bquejd7edypyrsl63bm

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

4m 18s

Created

over 1 year ago

Webhook

–

Input

prompt: a dog with a red collar
negative_prompt: worst quality, low quality
image: https://replicate.delivery/pbxt/KeDO2j9Xbw1LHuXU4jqAfh2WUpKji1AlfR5dFkSkLPiGqYWN/dog2.png
mask: https://replicate.delivery/pbxt/KeDO2hmJs2QCyQjUpz7UNmuC8vTuILV4d9pZEhEgvyXzbvK3/dog2%20mask.png
prompt_strength: 0.8
condition_scale: 0.5
num_outputs: 1
scheduler: DDIM
num_inference_steps: 35
guidance_scale: 7
lora_scale: 0.6

{
  "condition_scale": 0.5,
  "guidance_scale": 7,
  "image": "https://replicate.delivery/pbxt/KeDO2j9Xbw1LHuXU4jqAfh2WUpKji1AlfR5dFkSkLPiGqYWN/dog2.png",
  "lora_scale": 0.6,
  "mask": "https://replicate.delivery/pbxt/KeDO2hmJs2QCyQjUpz7UNmuC8vTuILV4d9pZEhEgvyXzbvK3/dog2%20mask.png",
  "negative_prompt": "worst quality, low quality",
  "num_inference_steps": 35,
  "num_outputs": 1,
  "prompt": "a dog with a red collar",
  "prompt_strength": 0.8,
  "scheduler": "DDIM"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_4jy**********************************

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

const output = await replicate.run(
  "fermatresearch/sdxl-controlnet-lora-inpaint:35c927ab69062f7cc3fdd0ad4367832b08fdd98c60e5907651a6e03f4bb5d927",
  {
    input: {
      condition_scale: 0.5,
      guidance_scale: 7,
      image: "https://replicate.delivery/pbxt/KeDO2j9Xbw1LHuXU4jqAfh2WUpKji1AlfR5dFkSkLPiGqYWN/dog2.png",
      lora_scale: 0.6,
      mask: "https://replicate.delivery/pbxt/KeDO2hmJs2QCyQjUpz7UNmuC8vTuILV4d9pZEhEgvyXzbvK3/dog2%20mask.png",
      negative_prompt: "worst quality, low quality",
      num_inference_steps: 35,
      num_outputs: 1,
      prompt: "a dog with a red collar",
      prompt_strength: 0.8,
      scheduler: "DDIM"
    }
  }
);

// 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_4jy**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

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

output = replicate.run(
    "fermatresearch/sdxl-controlnet-lora-inpaint:35c927ab69062f7cc3fdd0ad4367832b08fdd98c60e5907651a6e03f4bb5d927",
    input={
        "condition_scale": 0.5,
        "guidance_scale": 7,
        "image": "https://replicate.delivery/pbxt/KeDO2j9Xbw1LHuXU4jqAfh2WUpKji1AlfR5dFkSkLPiGqYWN/dog2.png",
        "lora_scale": 0.6,
        "mask": "https://replicate.delivery/pbxt/KeDO2hmJs2QCyQjUpz7UNmuC8vTuILV4d9pZEhEgvyXzbvK3/dog2%20mask.png",
        "negative_prompt": "worst quality, low quality",
        "num_inference_steps": 35,
        "num_outputs": 1,
        "prompt": "a dog with a red collar",
        "prompt_strength": 0.8,
        "scheduler": "DDIM"
    }
)

# 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_4jy**********************************

This is your API token. Keep it to yourself.

Run fermatresearch/sdxl-controlnet-lora-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/sdxl-controlnet-lora-inpaint:35c927ab69062f7cc3fdd0ad4367832b08fdd98c60e5907651a6e03f4bb5d927",
    "input": {
      "condition_scale": 0.5,
      "guidance_scale": 7,
      "image": "https://replicate.delivery/pbxt/KeDO2j9Xbw1LHuXU4jqAfh2WUpKji1AlfR5dFkSkLPiGqYWN/dog2.png",
      "lora_scale": 0.6,
      "mask": "https://replicate.delivery/pbxt/KeDO2hmJs2QCyQjUpz7UNmuC8vTuILV4d9pZEhEgvyXzbvK3/dog2%20mask.png",
      "negative_prompt": "worst quality, low quality",
      "num_inference_steps": 35,
      "num_outputs": 1,
      "prompt": "a dog with a red collar",
      "prompt_strength": 0.8,
      "scheduler": "DDIM"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "id": "pj64fk3bquejd7edypyrsl63bm",
  "model": "fermatresearch/sdxl-controlnet-lora-inpaint",
  "version": "35c927ab69062f7cc3fdd0ad4367832b08fdd98c60e5907651a6e03f4bb5d927",
  "input": {
    "condition_scale": 0.5,
    "guidance_scale": 7,
    "image": "https://replicate.delivery/pbxt/KeDO2j9Xbw1LHuXU4jqAfh2WUpKji1AlfR5dFkSkLPiGqYWN/dog2.png",
    "lora_scale": 0.6,
    "mask": "https://replicate.delivery/pbxt/KeDO2hmJs2QCyQjUpz7UNmuC8vTuILV4d9pZEhEgvyXzbvK3/dog2%20mask.png",
    "negative_prompt": "worst quality, low quality",
    "num_inference_steps": 35,
    "num_outputs": 1,
    "prompt": "a dog with a red collar",
    "prompt_strength": 0.8,
    "scheduler": "DDIM"
  },
  "logs": "Using seed: 34850\nPrompt: a dog with a red collar\nOriginal width:1024, height:1024\nAspect Ratio: 1.00\nnew_width:1024, new_height:1024\nOriginal width:1024, height:1024\nAspect Ratio: 1.00\nnew_width:1024, new_height:1024\n  0%|          | 0/28 [00:00<?, ?it/s]\n  4%|▎         | 1/28 [00:00<00:09,  2.77it/s]\n  7%|▋         | 2/28 [00:00<00:08,  3.10it/s]\n 11%|█         | 3/28 [00:00<00:07,  3.22it/s]\n 14%|█▍        | 4/28 [00:01<00:07,  3.27it/s]\n 18%|█▊        | 5/28 [00:01<00:06,  3.30it/s]\n 21%|██▏       | 6/28 [00:01<00:06,  3.32it/s]\n 25%|██▌       | 7/28 [00:02<00:06,  3.34it/s]\n 29%|██▊       | 8/28 [00:02<00:05,  3.34it/s]\n 32%|███▏      | 9/28 [00:02<00:05,  3.34it/s]\n 36%|███▌      | 10/28 [00:03<00:05,  3.34it/s]\n 39%|███▉      | 11/28 [00:03<00:05,  3.35it/s]\n 43%|████▎     | 12/28 [00:03<00:04,  3.35it/s]\n 46%|████▋     | 13/28 [00:03<00:04,  3.35it/s]\n 50%|█████     | 14/28 [00:04<00:04,  3.35it/s]\n 54%|█████▎    | 15/28 [00:04<00:03,  3.35it/s]\n 57%|█████▋    | 16/28 [00:04<00:03,  3.36it/s]\n 61%|██████    | 17/28 [00:05<00:03,  3.37it/s]\n 64%|██████▍   | 18/28 [00:05<00:02,  3.37it/s]\n 68%|██████▊   | 19/28 [00:05<00:02,  3.38it/s]\n 71%|███████▏  | 20/28 [00:06<00:02,  3.38it/s]\n 75%|███████▌  | 21/28 [00:06<00:02,  3.38it/s]\n 79%|███████▊  | 22/28 [00:06<00:01,  3.38it/s]\n 82%|████████▏ | 23/28 [00:06<00:01,  3.37it/s]\n 86%|████████▌ | 24/28 [00:07<00:01,  3.37it/s]\n 89%|████████▉ | 25/28 [00:07<00:00,  3.37it/s]\n 93%|█████████▎| 26/28 [00:07<00:00,  3.37it/s]\n 96%|█████████▋| 27/28 [00:08<00:00,  3.37it/s]\n100%|██████████| 28/28 [00:08<00:00,  3.37it/s]\n100%|██████████| 28/28 [00:08<00:00,  3.34it/s]",
  "output": [
    "https://replicate.delivery/pbxt/6nYFmW4FYlo6O9SbngCZ1u1HoBF4QlWnvpKpHa3MnAUeSXSJA/out-0.png"
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-03-28T09:20:56.644443Z",
  "started_at": "2024-03-28T09:25:02.352547Z",
  "completed_at": "2024-03-28T09:25:14.574965Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/pj64fk3bquejd7edypyrsl63bm/cancel",
    "get": "https://api.replicate.com/v1/predictions/pj64fk3bquejd7edypyrsl63bm"
  },
  "metrics": {
    "predict_time": 12.222418,
    "total_time": 257.930522
  }
}

Generated in

12.2 seconds

Tweak it Report

Using seed: 34850 Prompt: a dog with a red collar Original width:1024, height:1024 Aspect Ratio: 1.00 new_width:1024, new_height:1024 Original width:1024, height:1024 Aspect Ratio: 1.00 new_width:1024, new_height:1024 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:09, 2.77it/s] 7%|▋ | 2/28 [00:00<00:08, 3.10it/s] 11%|█ | 3/28 [00:00<00:07, 3.22it/s] 14%|█▍ | 4/28 [00:01<00:07, 3.27it/s] 18%|█▊ | 5/28 [00:01<00:06, 3.30it/s] 21%|██▏ | 6/28 [00:01<00:06, 3.32it/s] 25%|██▌ | 7/28 [00:02<00:06, 3.34it/s] 29%|██▊ | 8/28 [00:02<00:05, 3.34it/s] 32%|███▏ | 9/28 [00:02<00:05, 3.34it/s] 36%|███▌ | 10/28 [00:03<00:05, 3.34it/s] 39%|███▉ | 11/28 [00:03<00:05, 3.35it/s] 43%|████▎ | 12/28 [00:03<00:04, 3.35it/s] 46%|████▋ | 13/28 [00:03<00:04, 3.35it/s] 50%|█████ | 14/28 [00:04<00:04, 3.35it/s] 54%|█████▎ | 15/28 [00:04<00:03, 3.35it/s] 57%|█████▋ | 16/28 [00:04<00:03, 3.36it/s] 61%|██████ | 17/28 [00:05<00:03, 3.37it/s] 64%|██████▍ | 18/28 [00:05<00:02, 3.37it/s] 68%|██████▊ | 19/28 [00:05<00:02, 3.38it/s] 71%|███████▏ | 20/28 [00:06<00:02, 3.38it/s] 75%|███████▌ | 21/28 [00:06<00:02, 3.38it/s] 79%|███████▊ | 22/28 [00:06<00:01, 3.38it/s] 82%|████████▏ | 23/28 [00:06<00:01, 3.37it/s] 86%|████████▌ | 24/28 [00:07<00:01, 3.37it/s] 89%|████████▉ | 25/28 [00:07<00:00, 3.37it/s] 93%|█████████▎| 26/28 [00:07<00:00, 3.37it/s] 96%|█████████▋| 27/28 [00:08<00:00, 3.37it/s] 100%|██████████| 28/28 [00:08<00:00, 3.37it/s] 100%|██████████| 28/28 [00:08<00:00, 3.34it/s]