Input

Run this model in Node.js with one line of code:

npx create-replicate --model=catacolabs/cartoonify

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set 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 catacolabs/cartoonify using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "catacolabs/cartoonify:f109015d60170dfb20460f17da8cb863155823c85ece1115e1e9e4ec7ef51d3b",
  {
    input: {
      seed: 2862431,
      image: "https://replicate.delivery/pbxt/JbiN55mmFQztbsQphxEk0vZyySVuWJdKCJSSIf9BIr58J19O/puppy.jpg"
    }
  }
);
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 replicate

Set 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 replicate

Run catacolabs/cartoonify using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "catacolabs/cartoonify:f109015d60170dfb20460f17da8cb863155823c85ece1115e1e9e4ec7ef51d3b",
    input={
        "seed": 2862431,
        "image": "https://replicate.delivery/pbxt/JbiN55mmFQztbsQphxEk0vZyySVuWJdKCJSSIf9BIr58J19O/puppy.jpg"
    }
)
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 catacolabs/cartoonify 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": "f109015d60170dfb20460f17da8cb863155823c85ece1115e1e9e4ec7ef51d3b",
    "input": {
      "seed": 2862431,
      "image": "https://replicate.delivery/pbxt/JbiN55mmFQztbsQphxEk0vZyySVuWJdKCJSSIf9BIr58J19O/puppy.jpg"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

{
  "completed_at": "2023-09-30T05:31:04.310575Z",
  "created_at": "2023-09-30T05:30:54.454194Z",
  "data_removed": false,
  "error": null,
  "id": "vlr7wnlbfleo2xkkns4aeryste",
  "input": {
    "seed": 2862431,
    "image": "https://replicate.delivery/pbxt/JbiN55mmFQztbsQphxEk0vZyySVuWJdKCJSSIf9BIr58J19O/puppy.jpg"
  },
  "logs": "Using seed: 2862431\nAspect Ratio: 1.00\n  0%|          | 0/55 [00:00<?, ?it/s]\n 47%|████▋     | 26/55 [00:00<00:00, 256.00it/s]\n 96%|█████████▋| 53/55 [00:00<00:00, 263.07it/s]\n100%|██████████| 55/55 [00:00<00:00, 264.05it/s]\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['- res photo, sitting relax and happy, sitting on green grass']\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['- res photo, sitting relax and happy, sitting on green grass']\n  0%|          | 0/32 [00:00<?, ?it/s]\n  6%|▋         | 2/32 [00:00<00:04,  6.81it/s]\n  9%|▉         | 3/32 [00:00<00:04,  5.93it/s]\n 12%|█▎        | 4/32 [00:00<00:05,  5.56it/s]\n 16%|█▌        | 5/32 [00:00<00:05,  5.36it/s]\n 19%|█▉        | 6/32 [00:01<00:04,  5.23it/s]\n 22%|██▏       | 7/32 [00:01<00:04,  5.16it/s]\n 25%|██▌       | 8/32 [00:01<00:04,  5.11it/s]\n 28%|██▊       | 9/32 [00:01<00:04,  5.09it/s]\n 31%|███▏      | 10/32 [00:01<00:04,  5.06it/s]\n 34%|███▍      | 11/32 [00:02<00:04,  5.04it/s]\n 38%|███▊      | 12/32 [00:02<00:03,  5.03it/s]\n 41%|████      | 13/32 [00:02<00:03,  5.02it/s]\n 44%|████▍     | 14/32 [00:02<00:03,  5.01it/s]\n 47%|████▋     | 15/32 [00:02<00:03,  5.01it/s]\n 50%|█████     | 16/32 [00:03<00:03,  5.01it/s]\n 53%|█████▎    | 17/32 [00:03<00:02,  5.00it/s]\n 56%|█████▋    | 18/32 [00:03<00:02,  5.00it/s]\n 59%|█████▉    | 19/32 [00:03<00:02,  5.01it/s]\n 62%|██████▎   | 20/32 [00:03<00:02,  5.01it/s]\n 66%|██████▌   | 21/32 [00:04<00:02,  5.01it/s]\n 69%|██████▉   | 22/32 [00:04<00:01,  5.01it/s]\n 72%|███████▏  | 23/32 [00:04<00:01,  5.01it/s]\n 75%|███████▌  | 24/32 [00:04<00:01,  5.01it/s]\n 78%|███████▊  | 25/32 [00:04<00:01,  5.01it/s]\n 81%|████████▏ | 26/32 [00:05<00:01,  5.00it/s]\n 84%|████████▍ | 27/32 [00:05<00:01,  5.00it/s]\n 88%|████████▊ | 28/32 [00:05<00:00,  5.00it/s]\n 91%|█████████ | 29/32 [00:05<00:00,  5.00it/s]\n 94%|█████████▍| 30/32 [00:05<00:00,  5.00it/s]\n 97%|█████████▋| 31/32 [00:06<00:00,  5.00it/s]\n100%|██████████| 32/32 [00:06<00:00,  5.00it/s]\n100%|██████████| 32/32 [00:06<00:00,  5.09it/s]",
  "metrics": {
    "predict_time": 9.851499,
    "total_time": 9.856381
  },
  "output": "https://pbxt.replicate.delivery/65PPr5heBJQnOCN3owkapbr91J7Bai642X9t46faXcKXSWpRA/output.png",
  "started_at": "2023-09-30T05:30:54.459076Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/vlr7wnlbfleo2xkkns4aeryste",
    "cancel": "https://api.replicate.com/v1/predictions/vlr7wnlbfleo2xkkns4aeryste/cancel"
  },
  "version": "f109015d60170dfb20460f17da8cb863155823c85ece1115e1e9e4ec7ef51d3b"
}

Generated in

9.9 seconds

Tweak itReport

Using seed: 2862431
Aspect Ratio: 1.00
  0%|          | 0/55 [00:00<?, ?it/s]
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 96%|█████████▋| 53/55 [00:00<00:00, 263.07it/s]
100%|██████████| 55/55 [00:00<00:00, 264.05it/s]
The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['- res photo, sitting relax and happy, sitting on green grass']
The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['- res photo, sitting relax and happy, sitting on green grass']
  0%|          | 0/32 [00:00<?, ?it/s]
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Examples

View more examples

Run time and cost

This model costs approximately $0.0056 to run on Replicate, or 178 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 6 seconds.

Readme

About

This is a custom model, and is my attempt at tackling the challenge of: turning your pet image into a cartoon

Its a super simple, but quick hack that I threw together.

Follow my work on X/Twitter @lucataco93