tmcdepix/zone | Run with an API on Replicate

Input

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

npx create-replicate --model=tmcdepix/zone

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";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

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

const output = await replicate.run(
  "tmcdepix/zone:909917dd458bb92e4ed0f28983bcc59c979d8b8345baa45ad316e7beec610473",
  {
    input: {
      prompt: "make the car blue",
      image_path: "https://replicate.delivery/pbxt/KxSjMlxcbwpXWE0G5W6CiMmCLemx5M6m2Sudg8D440JAAnVm/car1.jpg"
    }
  }
);

// 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.

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

output = replicate.run(
    "tmcdepix/zone:909917dd458bb92e4ed0f28983bcc59c979d8b8345baa45ad316e7beec610473",
    input={
        "prompt": "make the car blue",
        "image_path": "https://replicate.delivery/pbxt/KxSjMlxcbwpXWE0G5W6CiMmCLemx5M6m2Sudg8D440JAAnVm/car1.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 tmcdepix/zone 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": "tmcdepix/zone:909917dd458bb92e4ed0f28983bcc59c979d8b8345baa45ad316e7beec610473",
    "input": {
      "prompt": "make the car blue",
      "image_path": "https://replicate.delivery/pbxt/KxSjMlxcbwpXWE0G5W6CiMmCLemx5M6m2Sudg8D440JAAnVm/car1.jpg"
    }
  }' \
  https://api.replicate.com/v1/predictions

To 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 cog

If 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/thf-ai/zone@sha256:909917dd458bb92e4ed0f28983bcc59c979d8b8345baa45ad316e7beec610473 \
  -i 'prompt="make the car blue"' \
  -i 'image_path="https://replicate.delivery/pbxt/KxSjMlxcbwpXWE0G5W6CiMmCLemx5M6m2Sudg8D440JAAnVm/car1.jpg"'

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/thf-ai/zone@sha256:909917dd458bb92e4ed0f28983bcc59c979d8b8345baa45ad316e7beec610473
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "prompt": "make the car blue",
      "image_path": "https://replicate.delivery/pbxt/KxSjMlxcbwpXWE0G5W6CiMmCLemx5M6m2Sudg8D440JAAnVm/car1.jpg"
    }
  }' \
  http://localhost:5000/predictions

To learn more, take a look at the Cog documentation.

Output

{
  "completed_at": "2024-05-21T14:49:01.221145Z",
  "created_at": "2024-05-21T14:44:49.440000Z",
  "data_removed": false,
  "error": null,
  "id": "q7fab4xmm1rgg0cfkeebdnfe08",
  "input": {
    "prompt": "make the car blue",
    "image_path": "https://replicate.delivery/pbxt/KxSjMlxcbwpXWE0G5W6CiMmCLemx5M6m2Sudg8D440JAAnVm/car1.jpg"
  },
  "logs": "0%|          | 0/20 [00:00<?, ?it/s]\n  5%|▌         | 1/20 [00:00<00:08,  2.37it/s]\n 10%|█         | 2/20 [00:00<00:07,  2.54it/s]\n 15%|█▌        | 3/20 [00:01<00:06,  2.60it/s]\n 20%|██        | 4/20 [00:01<00:06,  2.64it/s]\n 25%|██▌       | 5/20 [00:01<00:05,  2.65it/s]\n 30%|███       | 6/20 [00:02<00:05,  2.66it/s]\n 35%|███▌      | 7/20 [00:02<00:04,  2.67it/s]\n 40%|████      | 8/20 [00:03<00:04,  2.67it/s]\n 45%|████▌     | 9/20 [00:03<00:04,  2.67it/s]\n 50%|█████     | 10/20 [00:03<00:03,  2.67it/s]\n 55%|█████▌    | 11/20 [00:04<00:03,  2.67it/s]\n 60%|██████    | 12/20 [00:04<00:02,  2.67it/s]\n 65%|██████▌   | 13/20 [00:04<00:02,  2.67it/s]\n 70%|███████   | 14/20 [00:05<00:02,  2.67it/s]\n 75%|███████▌  | 15/20 [00:05<00:01,  2.67it/s]\n 80%|████████  | 16/20 [00:06<00:01,  2.67it/s]\n 85%|████████▌ | 17/20 [00:06<00:01,  2.67it/s]\n 90%|█████████ | 18/20 [00:06<00:00,  2.68it/s]\n 95%|█████████▌| 19/20 [00:07<00:00,  2.68it/s]\n100%|██████████| 20/20 [00:07<00:00,  2.68it/s]\n100%|██████████| 20/20 [00:07<00:00,  2.66it/s]\nstart generating masks...\n2.941328287124634\nBest Segmentation IOU: 0.15, seg_ratio:0.15\nFine mask prediction used 3.01 s\n--------------------  Inference completed  --------------------",
  "metrics": {
    "predict_time": 13.244161,
    "total_time": 251.781145
  },
  "output": "https://replicate.delivery/pbxt/YQASffc5yhh50kvLfuIUTInOvQshSAwSre0jeDfylcpNXmptE/output.png",
  "started_at": "2024-05-21T14:48:47.976984Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/q7fab4xmm1rgg0cfkeebdnfe08",
    "cancel": "https://api.replicate.com/v1/predictions/q7fab4xmm1rgg0cfkeebdnfe08/cancel"
  },
  "version": "909917dd458bb92e4ed0f28983bcc59c979d8b8345baa45ad316e7beec610473"
}

Generated in

13.3 seconds

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Examples

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Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

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tmcdepix / zone

Input

Output

Examples

Run time and cost

Readme

Logs (q7fab4xmm1rgg0cfkeebdnfe08)