aaronjmars/triposg:14bcf0ef – Run with an API on Replicate

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aaronjmars /triposg:14bcf0ef

Playground API

Input

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

npx create-replicate --model=aaronjmars/triposg

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

const output = await replicate.run(
  "aaronjmars/triposg:14bcf0ef5a1d638ef5cd78c30a72efb32344cdd9280efb5819fd15275cec85e3",
  {
    input: {
      seed: 42,
      image: "https://replicate.delivery/pbxt/MkfWaszeUKdynXaueF7QDkCW3dfdIOdAfFE4SJeB3QCVOwTa/133.png",
      guidance_scale: 7,
      num_inference_steps: 50
    }
  }
);

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

output = replicate.run(
    "aaronjmars/triposg:14bcf0ef5a1d638ef5cd78c30a72efb32344cdd9280efb5819fd15275cec85e3",
    input={
        "seed": 42,
        "image": "https://replicate.delivery/pbxt/MkfWaszeUKdynXaueF7QDkCW3dfdIOdAfFE4SJeB3QCVOwTa/133.png",
        "guidance_scale": 7,
        "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 aaronjmars/triposg 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": "aaronjmars/triposg:14bcf0ef5a1d638ef5cd78c30a72efb32344cdd9280efb5819fd15275cec85e3",
    "input": {
      "seed": 42,
      "image": "https://replicate.delivery/pbxt/MkfWaszeUKdynXaueF7QDkCW3dfdIOdAfFE4SJeB3QCVOwTa/133.png",
      "guidance_scale": 7,
      "num_inference_steps": 50
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

output.obj

{
  "completed_at": "2025-03-30T21:56:32.611607Z",
  "created_at": "2025-03-30T21:50:55.709000Z",
  "data_removed": false,
  "error": null,
  "id": "et79cm2cvnrma0cnx44v0ky2pc",
  "input": {
    "seed": 42,
    "image": "https://replicate.delivery/pbxt/MkfWaszeUKdynXaueF7QDkCW3dfdIOdAfFE4SJeB3QCVOwTa/133.png",
    "guidance_scale": 7,
    "num_inference_steps": 50
  },
  "logs": "Processing input image: /tmp/tmpytlyzxxw133.png\nUsing 50 inference steps\nUsing guidance scale of 7.0\nUsing seed: 42\n  0%|          | 0/50 [00:00<?, ?it/s]\n  2%|▏         | 1/50 [00:00<00:07,  6.50it/s]\n  6%|▌         | 3/50 [00:00<00:04, 11.46it/s]\n 10%|█         | 5/50 [00:00<00:04, 10.75it/s]\n 14%|█▍        | 7/50 [00:00<00:04, 10.49it/s]\n 18%|█▊        | 9/50 [00:00<00:03, 10.35it/s]\n 22%|██▏       | 11/50 [00:01<00:03, 10.27it/s]\n 26%|██▌       | 13/50 [00:01<00:03, 10.21it/s]\n 30%|███       | 15/50 [00:01<00:03, 10.18it/s]\n 34%|███▍      | 17/50 [00:01<00:03, 10.16it/s]\n 38%|███▊      | 19/50 [00:01<00:03, 10.14it/s]\n 42%|████▏     | 21/50 [00:02<00:02, 10.13it/s]\n 46%|████▌     | 23/50 [00:02<00:02, 10.12it/s]\n 50%|█████     | 25/50 [00:02<00:02, 10.11it/s]\n 54%|█████▍    | 27/50 [00:02<00:02, 10.10it/s]\n 58%|█████▊    | 29/50 [00:02<00:02, 10.09it/s]\n 62%|██████▏   | 31/50 [00:03<00:01, 10.09it/s]\n 66%|██████▌   | 33/50 [00:03<00:01, 10.08it/s]\n 70%|███████   | 35/50 [00:03<00:01, 10.08it/s]\n 74%|███████▍  | 37/50 [00:03<00:01, 10.06it/s]\n 78%|███████▊  | 39/50 [00:03<00:01, 10.06it/s]\n 82%|████████▏ | 41/50 [00:04<00:00, 10.06it/s]\n 86%|████████▌ | 43/50 [00:04<00:00, 10.06it/s]\n 90%|█████████ | 45/50 [00:04<00:00, 10.06it/s]\n 94%|█████████▍| 47/50 [00:04<00:00, 10.06it/s]\n 98%|█████████▊| 49/50 [00:04<00:00, 10.06it/s]\n100%|██████████| 50/50 [00:04<00:00, 10.12it/s]\nstep 1 query num: 16777216\nstep 2 query num: 13218384\nfinal grids shape =  torch.Size([512, 512, 512])",
  "metrics": {
    "predict_time": 19.719734619,
    "total_time": 336.902607
  },
  "output": "https://replicate.delivery/xezq/1ZfJxSKaji1QNygkWPpyAei7Ubpefn1pgE0LeuutD0IFC4ujC/output.obj",
  "started_at": "2025-03-30T21:56:12.891872Z",
  "status": "succeeded",
  "urls": {
    "stream": "https://stream.replicate.com/v1/files/bcwr-xxdm4kfuo5mxczqk5tx6w6btoaihv3f74xdtu4dwlgnsvlqmmpfq",
    "get": "https://api.replicate.com/v1/predictions/et79cm2cvnrma0cnx44v0ky2pc",
    "cancel": "https://api.replicate.com/v1/predictions/et79cm2cvnrma0cnx44v0ky2pc/cancel"
  },
  "version": "14bcf0ef5a1d638ef5cd78c30a72efb32344cdd9280efb5819fd15275cec85e3"
}

Generated in

19.7 seconds

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