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camenduru /colorize-line-art:59575cca
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run camenduru/colorize-line-art using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"camenduru/colorize-line-art:59575cca43435fec91bf2016648a36db03ab0c1556490974e3c483274076a6ec",
{
input: {
det: "None",
eta: 1,
seed: 12345,
scale: 9,
prompt: "",
a_prompt: "masterpiece, best quality, ultra-detailed, illustration, disheveled hair",
n_prompt: "longbody, lowres, bad anatomy, bad hands, missing fingers, pubic hair,extra digit, fewer digits, cropped, worst quality, low quality",
strength: 1,
ddim_steps: 20,
input_image: "https://replicate.delivery/pbxt/Klnr9AV290Zjuw8QmJaVEbOvVhG4svc0CFLBqobIA9apatJ3/326152.png",
image_resolution: 512,
detect_resolution: 512
}
}
);
// 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.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run camenduru/colorize-line-art using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"camenduru/colorize-line-art:59575cca43435fec91bf2016648a36db03ab0c1556490974e3c483274076a6ec",
input={
"det": "None",
"eta": 1,
"seed": 12345,
"scale": 9,
"prompt": "",
"a_prompt": "masterpiece, best quality, ultra-detailed, illustration, disheveled hair",
"n_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, pubic hair,extra digit, fewer digits, cropped, worst quality, low quality",
"strength": 1,
"ddim_steps": 20,
"input_image": "https://replicate.delivery/pbxt/Klnr9AV290Zjuw8QmJaVEbOvVhG4svc0CFLBqobIA9apatJ3/326152.png",
"image_resolution": 512,
"detect_resolution": 512
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run camenduru/colorize-line-art 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": "camenduru/colorize-line-art:59575cca43435fec91bf2016648a36db03ab0c1556490974e3c483274076a6ec",
"input": {
"det": "None",
"eta": 1,
"seed": 12345,
"scale": 9,
"prompt": "",
"a_prompt": "masterpiece, best quality, ultra-detailed, illustration, disheveled hair",
"n_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, pubic hair,extra digit, fewer digits, cropped, worst quality, low quality",
"strength": 1,
"ddim_steps": 20,
"input_image": "https://replicate.delivery/pbxt/Klnr9AV290Zjuw8QmJaVEbOvVhG4svc0CFLBqobIA9apatJ3/326152.png",
"image_resolution": 512,
"detect_resolution": 512
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
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Output
{
"completed_at": "2024-04-18T18:39:38.964303Z",
"created_at": "2024-04-18T18:37:35.168000Z",
"data_removed": false,
"error": null,
"id": "53v1bbzj81rgm0cey9zvtd8azr",
"input": {
"det": "None",
"eta": 1,
"seed": 12345,
"scale": 9,
"prompt": "",
"a_prompt": "masterpiece, best quality, ultra-detailed, illustration, disheveled hair",
"n_prompt": "longbody, lowres, bad anatomy, bad hands, missing fingers, pubic hair,extra digit, fewer digits, cropped, worst quality, low quality",
"strength": 1,
"ddim_steps": 20,
"input_image": "https://replicate.delivery/pbxt/Klnr9AV290Zjuw8QmJaVEbOvVhG4svc0CFLBqobIA9apatJ3/326152.png",
"image_resolution": 512,
"detect_resolution": 512
},
"logs": "Global seed set to 12345\nData shape for DDIM sampling is (1, 4, 96, 64), eta 1.0\nRunning DDIM Sampling with 20 timesteps\nDDIM Sampler: 0%| | 0/20 [00:00<?, ?it/s]\nDDIM Sampler: 5%|▌ | 1/20 [00:00<00:08, 2.22it/s]\nDDIM Sampler: 10%|█ | 2/20 [00:00<00:06, 2.81it/s]\nDDIM Sampler: 15%|█▌ | 3/20 [00:01<00:05, 3.07it/s]\nDDIM Sampler: 20%|██ | 4/20 [00:01<00:04, 3.21it/s]\nDDIM Sampler: 25%|██▌ | 5/20 [00:01<00:04, 3.29it/s]\nDDIM Sampler: 30%|███ | 6/20 [00:01<00:04, 3.34it/s]\nDDIM Sampler: 35%|███▌ | 7/20 [00:02<00:03, 3.37it/s]\nDDIM Sampler: 40%|████ | 8/20 [00:02<00:03, 3.40it/s]\nDDIM Sampler: 45%|████▌ | 9/20 [00:02<00:03, 3.41it/s]\nDDIM Sampler: 50%|█████ | 10/20 [00:03<00:02, 3.42it/s]\nDDIM Sampler: 55%|█████▌ | 11/20 [00:03<00:02, 3.42it/s]\nDDIM Sampler: 60%|██████ | 12/20 [00:03<00:02, 3.43it/s]\nDDIM Sampler: 65%|██████▌ | 13/20 [00:03<00:02, 3.43it/s]\nDDIM Sampler: 70%|███████ | 14/20 [00:04<00:01, 3.43it/s]\nDDIM Sampler: 75%|███████▌ | 15/20 [00:04<00:01, 3.43it/s]\nDDIM Sampler: 80%|████████ | 16/20 [00:04<00:01, 3.44it/s]\nDDIM Sampler: 85%|████████▌ | 17/20 [00:05<00:00, 3.43it/s]\nDDIM Sampler: 90%|█████████ | 18/20 [00:05<00:00, 3.44it/s]\nDDIM Sampler: 95%|█████████▌| 19/20 [00:05<00:00, 3.43it/s]\nDDIM Sampler: 100%|██████████| 20/20 [00:05<00:00, 3.43it/s]\nDDIM Sampler: 100%|██████████| 20/20 [00:05<00:00, 3.35it/s]",
"metrics": {
"predict_time": 7.869944,
"total_time": 123.796303
},
"output": "https://replicate.delivery/pbxt/r9f6FkzsQetzKUWDrJg4cNlILCshUtyCwAD8eliqsSZTXjXlA/output.png",
"started_at": "2024-04-18T18:39:31.094359Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/53v1bbzj81rgm0cey9zvtd8azr",
"cancel": "https://api.replicate.com/v1/predictions/53v1bbzj81rgm0cey9zvtd8azr/cancel"
},
"version": "59575cca43435fec91bf2016648a36db03ab0c1556490974e3c483274076a6ec"
}
Global seed set to 12345
Data shape for DDIM sampling is (1, 4, 96, 64), eta 1.0
Running DDIM Sampling with 20 timesteps
DDIM Sampler: 0%| | 0/20 [00:00<?, ?it/s]
DDIM Sampler: 5%|▌ | 1/20 [00:00<00:08, 2.22it/s]
DDIM Sampler: 10%|█ | 2/20 [00:00<00:06, 2.81it/s]
DDIM Sampler: 15%|█▌ | 3/20 [00:01<00:05, 3.07it/s]
DDIM Sampler: 20%|██ | 4/20 [00:01<00:04, 3.21it/s]
DDIM Sampler: 25%|██▌ | 5/20 [00:01<00:04, 3.29it/s]
DDIM Sampler: 30%|███ | 6/20 [00:01<00:04, 3.34it/s]
DDIM Sampler: 35%|███▌ | 7/20 [00:02<00:03, 3.37it/s]
DDIM Sampler: 40%|████ | 8/20 [00:02<00:03, 3.40it/s]
DDIM Sampler: 45%|████▌ | 9/20 [00:02<00:03, 3.41it/s]
DDIM Sampler: 50%|█████ | 10/20 [00:03<00:02, 3.42it/s]
DDIM Sampler: 55%|█████▌ | 11/20 [00:03<00:02, 3.42it/s]
DDIM Sampler: 60%|██████ | 12/20 [00:03<00:02, 3.43it/s]
DDIM Sampler: 65%|██████▌ | 13/20 [00:03<00:02, 3.43it/s]
DDIM Sampler: 70%|███████ | 14/20 [00:04<00:01, 3.43it/s]
DDIM Sampler: 75%|███████▌ | 15/20 [00:04<00:01, 3.43it/s]
DDIM Sampler: 80%|████████ | 16/20 [00:04<00:01, 3.44it/s]
DDIM Sampler: 85%|████████▌ | 17/20 [00:05<00:00, 3.43it/s]
DDIM Sampler: 90%|█████████ | 18/20 [00:05<00:00, 3.44it/s]
DDIM Sampler: 95%|█████████▌| 19/20 [00:05<00:00, 3.43it/s]
DDIM Sampler: 100%|██████████| 20/20 [00:05<00:00, 3.43it/s]
DDIM Sampler: 100%|██████████| 20/20 [00:05<00:00, 3.35it/s]