{
"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"
}npm install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_4jy**********************************
This is your API token. Keep it to yourself.
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.
pip install replicate
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_4jy**********************************
This is your API token. Keep it to yourself.
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.
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.
{
"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
}
}

