typefile
ID
0p73xazfanrmc0cnndx8xk16nm
Status
Succeeded
Source
Web
Hardware
L40S
Total duration
Created
by lucataco
Webhook
–
Input
- front_image
- back_image
- left_image
- steps
- 30default30typenumeric-rangevalue typeintegerminimum1maximum100
- guidance_scale
- 5default5typenumericvalue typenumber
- seed
- 1234default1234typenumericvalue typeinteger
- octree_resolution
- 256default256typenumeric-rangevalue typeintegerminimum16maximum512
- remove_background
- truedefaulttruetypeboolean
- num_chunks
- 200000default200000typenumeric-rangevalue typeintegerminimum1000maximum5000000
- randomize_seed
- truedefaulttruetypeboolean
- target_face_num
- 10000default10000typenumeric-rangevalue typeintegerminimum100maximum1000000
- file_type
- glbdefaultglbtypeenumvalue typestringoptionsglb, obj, ply, stl
{
"back_image": "https://replicate.delivery/pbxt/MgQTJZJpLfwXQc6N8rcxSAVGGf2GSGWAFYSqyKQyUVadSfiv/dog2-back.png",
"file_type": "glb",
"front_image": "https://replicate.delivery/pbxt/MgQTJRO3p8S9ToUYyoMkWLm5edO6y7DZKqP9OZWhYG3zUFtM/dog2-front.png",
"guidance_scale": 5,
"left_image": "https://replicate.delivery/pbxt/MgQTKA8In6bsulSoqMd1pp6lhRFmacbXOJuK9swVdknRJSbR/dog2-side.png",
"num_chunks": 200000,
"octree_resolution": 256,
"randomize_seed": true,
"remove_background": true,
"seed": 1234,
"steps": 30,
"target_face_num": 10000
}Install Replicate’s Node.js client library:
npm install replicate
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_6ew**********************************
This is your API token. Keep it to yourself.
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 tencent/hunyuan3d-2mv using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"tencent/hunyuan3d-2mv:71798fbc3c9f7b7097e3bb85496e5a797d8b8f616b550692e7c3e176a8e9e5db",
{
input: {
back_image: "https://replicate.delivery/pbxt/MgQTJZJpLfwXQc6N8rcxSAVGGf2GSGWAFYSqyKQyUVadSfiv/dog2-back.png",
file_type: "glb",
front_image: "https://replicate.delivery/pbxt/MgQTJRO3p8S9ToUYyoMkWLm5edO6y7DZKqP9OZWhYG3zUFtM/dog2-front.png",
guidance_scale: 5,
left_image: "https://replicate.delivery/pbxt/MgQTKA8In6bsulSoqMd1pp6lhRFmacbXOJuK9swVdknRJSbR/dog2-side.png",
num_chunks: 200000,
octree_resolution: 256,
randomize_seed: true,
remove_background: true,
seed: 1234,
steps: 30,
target_face_num: 10000
}
}
);
// 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=r8_6ew**********************************
This is your API token. Keep it to yourself.
Import the client:
import replicate
Run tencent/hunyuan3d-2mv using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"tencent/hunyuan3d-2mv:71798fbc3c9f7b7097e3bb85496e5a797d8b8f616b550692e7c3e176a8e9e5db",
input={
"back_image": "https://replicate.delivery/pbxt/MgQTJZJpLfwXQc6N8rcxSAVGGf2GSGWAFYSqyKQyUVadSfiv/dog2-back.png",
"file_type": "glb",
"front_image": "https://replicate.delivery/pbxt/MgQTJRO3p8S9ToUYyoMkWLm5edO6y7DZKqP9OZWhYG3zUFtM/dog2-front.png",
"guidance_scale": 5,
"left_image": "https://replicate.delivery/pbxt/MgQTKA8In6bsulSoqMd1pp6lhRFmacbXOJuK9swVdknRJSbR/dog2-side.png",
"num_chunks": 200000,
"octree_resolution": 256,
"randomize_seed": True,
"remove_background": True,
"seed": 1234,
"steps": 30,
"target_face_num": 10000
}
)
# To access the file URL:
print(output.url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output.read())
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=r8_6ew**********************************
This is your API token. Keep it to yourself.
Run tencent/hunyuan3d-2mv 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": "tencent/hunyuan3d-2mv:71798fbc3c9f7b7097e3bb85496e5a797d8b8f616b550692e7c3e176a8e9e5db",
"input": {
"back_image": "https://replicate.delivery/pbxt/MgQTJZJpLfwXQc6N8rcxSAVGGf2GSGWAFYSqyKQyUVadSfiv/dog2-back.png",
"file_type": "glb",
"front_image": "https://replicate.delivery/pbxt/MgQTJRO3p8S9ToUYyoMkWLm5edO6y7DZKqP9OZWhYG3zUFtM/dog2-front.png",
"guidance_scale": 5,
"left_image": "https://replicate.delivery/pbxt/MgQTKA8In6bsulSoqMd1pp6lhRFmacbXOJuK9swVdknRJSbR/dog2-side.png",
"num_chunks": 200000,
"octree_resolution": 256,
"randomize_seed": true,
"remove_background": true,
"seed": 1234,
"steps": 30,
"target_face_num": 10000
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
Use your mouse to zoom and rotate the model
{
"id": "0p73xazfanrmc0cnndx8xk16nm",
"model": "tencent/hunyuan3d-2mv",
"version": "71798fbc3c9f7b7097e3bb85496e5a797d8b8f616b550692e7c3e176a8e9e5db",
"input": {
"back_image": "https://replicate.delivery/pbxt/MgQTJZJpLfwXQc6N8rcxSAVGGf2GSGWAFYSqyKQyUVadSfiv/dog2-back.png",
"file_type": "glb",
"front_image": "https://replicate.delivery/pbxt/MgQTJRO3p8S9ToUYyoMkWLm5edO6y7DZKqP9OZWhYG3zUFtM/dog2-front.png",
"guidance_scale": 5,
"left_image": "https://replicate.delivery/pbxt/MgQTKA8In6bsulSoqMd1pp6lhRFmacbXOJuK9swVdknRJSbR/dog2-side.png",
"num_chunks": 200000,
"octree_resolution": 256,
"randomize_seed": true,
"remove_background": true,
"seed": 1234,
"steps": 30,
"target_face_num": 10000
},
"logs": "Diffusion Sampling:: 0%| | 0/30 [00:00<?, ?it/s]\nDiffusion Sampling:: 3%|▎ | 1/30 [00:00<00:04, 6.97it/s]\nDiffusion Sampling:: 10%|█ | 3/30 [00:00<00:02, 9.33it/s]\nDiffusion Sampling:: 13%|█▎ | 4/30 [00:00<00:03, 8.36it/s]\nDiffusion Sampling:: 17%|█▋ | 5/30 [00:00<00:03, 7.85it/s]\nDiffusion Sampling:: 20%|██ | 6/30 [00:00<00:03, 7.55it/s]\nDiffusion Sampling:: 23%|██▎ | 7/30 [00:00<00:03, 7.35it/s]\nDiffusion Sampling:: 27%|██▋ | 8/30 [00:01<00:03, 7.23it/s]\nDiffusion Sampling:: 30%|███ | 9/30 [00:01<00:02, 7.15it/s]\nDiffusion Sampling:: 33%|███▎ | 10/30 [00:01<00:02, 7.09it/s]\nDiffusion Sampling:: 37%|███▋ | 11/30 [00:01<00:02, 7.04it/s]\nDiffusion Sampling:: 40%|████ | 12/30 [00:01<00:02, 7.01it/s]\nDiffusion Sampling:: 43%|████▎ | 13/30 [00:01<00:02, 6.99it/s]\nDiffusion Sampling:: 47%|████▋ | 14/30 [00:01<00:02, 6.98it/s]\nDiffusion Sampling:: 50%|█████ | 15/30 [00:02<00:02, 6.97it/s]\nDiffusion Sampling:: 53%|█████▎ | 16/30 [00:02<00:02, 6.96it/s]\nDiffusion Sampling:: 57%|█████▋ | 17/30 [00:02<00:01, 6.95it/s]\nDiffusion Sampling:: 60%|██████ | 18/30 [00:02<00:01, 6.94it/s]\nDiffusion Sampling:: 63%|██████▎ | 19/30 [00:02<00:01, 6.94it/s]\nDiffusion Sampling:: 67%|██████▋ | 20/30 [00:02<00:01, 6.94it/s]\nDiffusion Sampling:: 70%|███████ | 21/30 [00:02<00:01, 6.93it/s]\nDiffusion Sampling:: 73%|███████▎ | 22/30 [00:03<00:01, 6.94it/s]\nDiffusion Sampling:: 77%|███████▋ | 23/30 [00:03<00:01, 6.94it/s]\nDiffusion Sampling:: 80%|████████ | 24/30 [00:03<00:00, 6.94it/s]\nDiffusion Sampling:: 83%|████████▎ | 25/30 [00:03<00:00, 6.93it/s]\nDiffusion Sampling:: 87%|████████▋ | 26/30 [00:03<00:00, 6.93it/s]\nDiffusion Sampling:: 90%|█████████ | 27/30 [00:03<00:00, 6.93it/s]\nDiffusion Sampling:: 93%|█████████▎| 28/30 [00:03<00:00, 6.92it/s]\nDiffusion Sampling:: 97%|█████████▋| 29/30 [00:04<00:00, 6.92it/s]\nDiffusion Sampling:: 100%|██████████| 30/30 [00:04<00:00, 6.92it/s]\nDiffusion Sampling:: 100%|██████████| 30/30 [00:04<00:00, 7.11it/s]\nVolume Decoding: 0%| | 0/85 [00:00<?, ?it/s]\nVolume Decoding: 55%|█████▌ | 47/85 [00:00<00:00, 375.96it/s]\nVolume Decoding: 100%|██████████| 85/85 [00:02<00:00, 33.51it/s]\nVolume Decoding: 100%|██████████| 85/85 [00:02<00:00, 39.47it/s]\nShape generation took 9.23 seconds\nCreated new folder: outputs/58ebb0d3-ed6c-4d07-8a2a-f91b81f2b258",
"output": "https://replicate.delivery/xezq/yUpfv4vLevlUF0wBqVNig7jTeQR9Y4EJSDtw18UPWCrTl1zoA/gray_mesh.glb",
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2025-03-18T22:58:35.477Z",
"started_at": "2025-03-18T22:58:35.492577Z",
"completed_at": "2025-03-18T22:58:49.577033Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/0p73xazfanrmc0cnndx8xk16nm/cancel",
"get": "https://api.replicate.com/v1/predictions/0p73xazfanrmc0cnndx8xk16nm",
"stream": "https://stream.replicate.com/v1/files/bcwr-bexsttkek76wq7t72wdsekhx5mrajhhgo2nigf2xqyk5skulw36q",
"web": "https://replicate.com/p/0p73xazfanrmc0cnndx8xk16nm"
},
"metrics": {
"predict_time": 14.084455464,
"total_time": 14.100033
}
}Generated in
Diffusion Sampling:: 0%| | 0/30 [00:00<?, ?it/s]
Diffusion Sampling:: 3%|▎ | 1/30 [00:00<00:04, 6.97it/s]
Diffusion Sampling:: 10%|█ | 3/30 [00:00<00:02, 9.33it/s]
Diffusion Sampling:: 13%|█▎ | 4/30 [00:00<00:03, 8.36it/s]
Diffusion Sampling:: 17%|█▋ | 5/30 [00:00<00:03, 7.85it/s]
Diffusion Sampling:: 20%|██ | 6/30 [00:00<00:03, 7.55it/s]
Diffusion Sampling:: 23%|██▎ | 7/30 [00:00<00:03, 7.35it/s]
Diffusion Sampling:: 27%|██▋ | 8/30 [00:01<00:03, 7.23it/s]
Diffusion Sampling:: 30%|███ | 9/30 [00:01<00:02, 7.15it/s]
Diffusion Sampling:: 33%|███▎ | 10/30 [00:01<00:02, 7.09it/s]
Diffusion Sampling:: 37%|███▋ | 11/30 [00:01<00:02, 7.04it/s]
Diffusion Sampling:: 40%|████ | 12/30 [00:01<00:02, 7.01it/s]
Diffusion Sampling:: 43%|████▎ | 13/30 [00:01<00:02, 6.99it/s]
Diffusion Sampling:: 47%|████▋ | 14/30 [00:01<00:02, 6.98it/s]
Diffusion Sampling:: 50%|█████ | 15/30 [00:02<00:02, 6.97it/s]
Diffusion Sampling:: 53%|█████▎ | 16/30 [00:02<00:02, 6.96it/s]
Diffusion Sampling:: 57%|█████▋ | 17/30 [00:02<00:01, 6.95it/s]
Diffusion Sampling:: 60%|██████ | 18/30 [00:02<00:01, 6.94it/s]
Diffusion Sampling:: 63%|██████▎ | 19/30 [00:02<00:01, 6.94it/s]
Diffusion Sampling:: 67%|██████▋ | 20/30 [00:02<00:01, 6.94it/s]
Diffusion Sampling:: 70%|███████ | 21/30 [00:02<00:01, 6.93it/s]
Diffusion Sampling:: 73%|███████▎ | 22/30 [00:03<00:01, 6.94it/s]
Diffusion Sampling:: 77%|███████▋ | 23/30 [00:03<00:01, 6.94it/s]
Diffusion Sampling:: 80%|████████ | 24/30 [00:03<00:00, 6.94it/s]
Diffusion Sampling:: 83%|████████▎ | 25/30 [00:03<00:00, 6.93it/s]
Diffusion Sampling:: 87%|████████▋ | 26/30 [00:03<00:00, 6.93it/s]
Diffusion Sampling:: 90%|█████████ | 27/30 [00:03<00:00, 6.93it/s]
Diffusion Sampling:: 93%|█████████▎| 28/30 [00:03<00:00, 6.92it/s]
Diffusion Sampling:: 97%|█████████▋| 29/30 [00:04<00:00, 6.92it/s]
Diffusion Sampling:: 100%|██████████| 30/30 [00:04<00:00, 6.92it/s]
Diffusion Sampling:: 100%|██████████| 30/30 [00:04<00:00, 7.11it/s]
Volume Decoding: 0%| | 0/85 [00:00<?, ?it/s]
Volume Decoding: 55%|█████▌ | 47/85 [00:00<00:00, 375.96it/s]
Volume Decoding: 100%|██████████| 85/85 [00:02<00:00, 33.51it/s]
Volume Decoding: 100%|██████████| 85/85 [00:02<00:00, 39.47it/s]
Shape generation took 9.23 seconds
Created new folder: outputs/58ebb0d3-ed6c-4d07-8a2a-f91b81f2b258