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You're looking at a specific version of this model. Jump to the model overview.
qr2ai /img2paint_controlnet:592691cf
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=qr2ai/img2paint_controlnet
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet 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 qr2ai/img2paint_controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"qr2ai/img2paint_controlnet:592691cf624bb863fe5a01673badff425607ba56dbc499a74bbfdacd3ec0da55",
{
input: {
seed: 7649977190,
image: "https://replicate.delivery/pbxt/Jn9H4XwOEn7reK9HAMsUa1dNkdf7C6oQKFpIb4Q7wD3ldHVv/Al-HamduLillah.jpg",
prompt: "Intricate Floral Fusion: A photorealistic 8k masterpiece featuring vibrant vines and daisies in a fluid gouache painting style. Calligraphy strokes and natural lighting bring out the details, set against a white backdrop.",
condition_scale: 0.63,
negative_prompt: "low quality, bad quality, nsfw",
num_inference_steps: 50
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet 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 replicateRun qr2ai/img2paint_controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"qr2ai/img2paint_controlnet:592691cf624bb863fe5a01673badff425607ba56dbc499a74bbfdacd3ec0da55",
input={
"seed": 7649977190,
"image": "https://replicate.delivery/pbxt/Jn9H4XwOEn7reK9HAMsUa1dNkdf7C6oQKFpIb4Q7wD3ldHVv/Al-HamduLillah.jpg",
"prompt": "Intricate Floral Fusion: A photorealistic 8k masterpiece featuring vibrant vines and daisies in a fluid gouache painting style. Calligraphy strokes and natural lighting bring out the details, set against a white backdrop.",
"condition_scale": 0.63,
"negative_prompt": "low quality, bad quality, nsfw",
"num_inference_steps": 50
}
)
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 qr2ai/img2paint_controlnet 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": "592691cf624bb863fe5a01673badff425607ba56dbc499a74bbfdacd3ec0da55",
"input": {
"seed": 7649977190,
"image": "https://replicate.delivery/pbxt/Jn9H4XwOEn7reK9HAMsUa1dNkdf7C6oQKFpIb4Q7wD3ldHVv/Al-HamduLillah.jpg",
"prompt": "Intricate Floral Fusion: A photorealistic 8k masterpiece featuring vibrant vines and daisies in a fluid gouache painting style. Calligraphy strokes and natural lighting bring out the details, set against a white backdrop.",
"condition_scale": 0.63,
"negative_prompt": "low quality, bad quality, nsfw",
"num_inference_steps": 50
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/qr2ai/img2paint_controlnet@sha256:592691cf624bb863fe5a01673badff425607ba56dbc499a74bbfdacd3ec0da55 \
-i 'seed=7649977190' \
-i 'image="https://replicate.delivery/pbxt/Jn9H4XwOEn7reK9HAMsUa1dNkdf7C6oQKFpIb4Q7wD3ldHVv/Al-HamduLillah.jpg"' \
-i 'prompt="Intricate Floral Fusion: A photorealistic 8k masterpiece featuring vibrant vines and daisies in a fluid gouache painting style. Calligraphy strokes and natural lighting bring out the details, set against a white backdrop."' \
-i 'condition_scale=0.63' \
-i 'negative_prompt="low quality, bad quality, nsfw"' \
-i 'num_inference_steps=50'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/qr2ai/img2paint_controlnet@sha256:592691cf624bb863fe5a01673badff425607ba56dbc499a74bbfdacd3ec0da55curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 7649977190, "image": "https://replicate.delivery/pbxt/Jn9H4XwOEn7reK9HAMsUa1dNkdf7C6oQKFpIb4Q7wD3ldHVv/Al-HamduLillah.jpg", "prompt": "Intricate Floral Fusion: A photorealistic 8k masterpiece featuring vibrant vines and daisies in a fluid gouache painting style. Calligraphy strokes and natural lighting bring out the details, set against a white backdrop.", "condition_scale": 0.63, "negative_prompt": "low quality, bad quality, nsfw", "num_inference_steps": 50 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $0.13. Alternatively, try out our featured models for free.
Sign in with GitHub
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2023-10-30T22:49:43.389344Z",
"created_at": "2023-10-30T22:49:26.081220Z",
"data_removed": false,
"error": null,
"id": "v5zofxlb37tyzbxw2tqm2pvkgq",
"input": {
"seed": 7649977190,
"image": "https://replicate.delivery/pbxt/Jn9H4XwOEn7reK9HAMsUa1dNkdf7C6oQKFpIb4Q7wD3ldHVv/Al-HamduLillah.jpg",
"prompt": "Intricate Floral Fusion: A photorealistic 8k masterpiece featuring vibrant vines and daisies in a fluid gouache painting style. Calligraphy strokes and natural lighting bring out the details, set against a white backdrop.",
"qr_data": null,
"condition_scale": 0.63,
"negative_prompt": "low quality, bad quality, nsfw",
"num_inference_steps": 50
},
"logs": "Using seed: 7649977190\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:00<00:14, 3.38it/s]\n 4%|▍ | 2/50 [00:00<00:14, 3.36it/s]\n 6%|▌ | 3/50 [00:00<00:13, 3.37it/s]\n 8%|▊ | 4/50 [00:01<00:13, 3.37it/s]\n 10%|█ | 5/50 [00:01<00:13, 3.36it/s]\n 12%|█▏ | 6/50 [00:01<00:13, 3.37it/s]\n 14%|█▍ | 7/50 [00:02<00:12, 3.37it/s]\n 16%|█▌ | 8/50 [00:02<00:12, 3.37it/s]\n 18%|█▊ | 9/50 [00:02<00:12, 3.37it/s]\n 20%|██ | 10/50 [00:02<00:11, 3.37it/s]\n 22%|██▏ | 11/50 [00:03<00:11, 3.37it/s]\n 24%|██▍ | 12/50 [00:03<00:11, 3.36it/s]\n 26%|██▌ | 13/50 [00:03<00:11, 3.36it/s]\n 28%|██▊ | 14/50 [00:04<00:10, 3.36it/s]\n 30%|███ | 15/50 [00:04<00:10, 3.36it/s]\n 32%|███▏ | 16/50 [00:04<00:10, 3.36it/s]\n 34%|███▍ | 17/50 [00:05<00:09, 3.36it/s]\n 36%|███▌ | 18/50 [00:05<00:09, 3.36it/s]\n 38%|███▊ | 19/50 [00:05<00:09, 3.36it/s]\n 40%|████ | 20/50 [00:05<00:08, 3.36it/s]\n 42%|████▏ | 21/50 [00:06<00:08, 3.36it/s]\n 44%|████▍ | 22/50 [00:06<00:08, 3.35it/s]\n 46%|████▌ | 23/50 [00:06<00:08, 3.35it/s]\n 48%|████▊ | 24/50 [00:07<00:07, 3.35it/s]\n 50%|█████ | 25/50 [00:07<00:07, 3.35it/s]\n 52%|█████▏ | 26/50 [00:07<00:07, 3.35it/s]\n 54%|█████▍ | 27/50 [00:08<00:06, 3.35it/s]\n 56%|█████▌ | 28/50 [00:08<00:06, 3.35it/s]\n 58%|█████▊ | 29/50 [00:08<00:06, 3.35it/s]\n 60%|██████ | 30/50 [00:08<00:05, 3.35it/s]\n 62%|██████▏ | 31/50 [00:09<00:05, 3.35it/s]\n 64%|██████▍ | 32/50 [00:09<00:05, 3.35it/s]\n 66%|██████▌ | 33/50 [00:09<00:05, 3.35it/s]\n 68%|██████▊ | 34/50 [00:10<00:04, 3.35it/s]\n 70%|███████ | 35/50 [00:10<00:04, 3.34it/s]\n 72%|███████▏ | 36/50 [00:10<00:04, 3.34it/s]\n 74%|███████▍ | 37/50 [00:11<00:03, 3.34it/s]\n 76%|███████▌ | 38/50 [00:11<00:03, 3.34it/s]\n 78%|███████▊ | 39/50 [00:11<00:03, 3.34it/s]\n 80%|████████ | 40/50 [00:11<00:02, 3.34it/s]\n 82%|████████▏ | 41/50 [00:12<00:02, 3.34it/s]\n 84%|████████▍ | 42/50 [00:12<00:02, 3.34it/s]\n 86%|████████▌ | 43/50 [00:12<00:02, 3.34it/s]\n 88%|████████▊ | 44/50 [00:13<00:01, 3.34it/s]\n 90%|█████████ | 45/50 [00:13<00:01, 3.33it/s]\n 92%|█████████▏| 46/50 [00:13<00:01, 3.33it/s]\n 94%|█████████▍| 47/50 [00:14<00:00, 3.34it/s]\n 96%|█████████▌| 48/50 [00:14<00:00, 3.34it/s]\n 98%|█████████▊| 49/50 [00:14<00:00, 3.34it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.34it/s]\n100%|██████████| 50/50 [00:14<00:00, 3.35it/s]",
"metrics": {
"predict_time": 17.335607,
"total_time": 17.308124
},
"output": "https://pbxt.replicate.delivery/mHYOMCayF0ofGC7wyiYPjHlMrDZJfWpDe08pE8rbYywNo8mjA/output.png",
"started_at": "2023-10-30T22:49:26.053737Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/v5zofxlb37tyzbxw2tqm2pvkgq",
"cancel": "https://api.replicate.com/v1/predictions/v5zofxlb37tyzbxw2tqm2pvkgq/cancel"
},
"version": "592691cf624bb863fe5a01673badff425607ba56dbc499a74bbfdacd3ec0da55"
}Generated in
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