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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 firtoz/trellis using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"firtoz/trellis:4876f2a8da1c544772dffa32e8889da4a1bab3a1f5c1937bfcfccb99ae347251",
{
input: {
seed: 0,
images: ["https://replicate.delivery/pbxt/ML1p0eA4AEhEvXPlIzds5RWD4axHK8Qj5276Q4Gi9aAuqg1G/20250117_144447.jpg","https://replicate.delivery/pbxt/ML1p0XhuTj7PjRPOIfN3q0ZNurZgN3EgWjuYI5ISHMl7DlmJ/20250117_144443.jpg","https://replicate.delivery/pbxt/ML1ozyZUROpp5iLoLEI2SWn4YBe5jmJ5DPxrjg9FivKLvKEl/20250117_144437.jpg","https://replicate.delivery/pbxt/ML1p0TLpeGDAMlEranut1WEJNljGKP94IV0PdtRtnrbpHCeX/20250117_144431.jpg","https://replicate.delivery/pbxt/ML1p0rXh6U26VEzshLLFZq30UzVk6zsc11AOIfhYoDIbepn1/20250117_144423.jpg"],
texture_size: 2048,
mesh_simplify: 0.9,
generate_color: true,
generate_model: true,
randomize_seed: true,
generate_normal: false,
save_gaussian_ply: true,
ss_sampling_steps: 38,
slat_sampling_steps: 12,
return_no_background: false,
ss_guidance_strength: 7.5,
slat_guidance_strength: 3
}
}
);
console.log(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 firtoz/trellis using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"firtoz/trellis:4876f2a8da1c544772dffa32e8889da4a1bab3a1f5c1937bfcfccb99ae347251",
input={
"seed": 0,
"images": ["https://replicate.delivery/pbxt/ML1p0eA4AEhEvXPlIzds5RWD4axHK8Qj5276Q4Gi9aAuqg1G/20250117_144447.jpg","https://replicate.delivery/pbxt/ML1p0XhuTj7PjRPOIfN3q0ZNurZgN3EgWjuYI5ISHMl7DlmJ/20250117_144443.jpg","https://replicate.delivery/pbxt/ML1ozyZUROpp5iLoLEI2SWn4YBe5jmJ5DPxrjg9FivKLvKEl/20250117_144437.jpg","https://replicate.delivery/pbxt/ML1p0TLpeGDAMlEranut1WEJNljGKP94IV0PdtRtnrbpHCeX/20250117_144431.jpg","https://replicate.delivery/pbxt/ML1p0rXh6U26VEzshLLFZq30UzVk6zsc11AOIfhYoDIbepn1/20250117_144423.jpg"],
"texture_size": 2048,
"mesh_simplify": 0.9,
"generate_color": True,
"generate_model": True,
"randomize_seed": True,
"generate_normal": False,
"save_gaussian_ply": True,
"ss_sampling_steps": 38,
"slat_sampling_steps": 12,
"return_no_background": False,
"ss_guidance_strength": 7.5,
"slat_guidance_strength": 3
}
)
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 firtoz/trellis 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": "firtoz/trellis:4876f2a8da1c544772dffa32e8889da4a1bab3a1f5c1937bfcfccb99ae347251",
"input": {
"seed": 0,
"images": ["https://replicate.delivery/pbxt/ML1p0eA4AEhEvXPlIzds5RWD4axHK8Qj5276Q4Gi9aAuqg1G/20250117_144447.jpg","https://replicate.delivery/pbxt/ML1p0XhuTj7PjRPOIfN3q0ZNurZgN3EgWjuYI5ISHMl7DlmJ/20250117_144443.jpg","https://replicate.delivery/pbxt/ML1ozyZUROpp5iLoLEI2SWn4YBe5jmJ5DPxrjg9FivKLvKEl/20250117_144437.jpg","https://replicate.delivery/pbxt/ML1p0TLpeGDAMlEranut1WEJNljGKP94IV0PdtRtnrbpHCeX/20250117_144431.jpg","https://replicate.delivery/pbxt/ML1p0rXh6U26VEzshLLFZq30UzVk6zsc11AOIfhYoDIbepn1/20250117_144423.jpg"],
"texture_size": 2048,
"mesh_simplify": 0.9,
"generate_color": true,
"generate_model": true,
"randomize_seed": true,
"generate_normal": false,
"save_gaussian_ply": true,
"ss_sampling_steps": 38,
"slat_sampling_steps": 12,
"return_no_background": false,
"ss_guidance_strength": 7.5,
"slat_guidance_strength": 3
}
}' \
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.
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2025-01-17T16:16:06.377741Z",
"created_at": "2025-01-17T16:12:18.813000Z",
"data_removed": false,
"error": null,
"id": "xg5e45k9znrj40cmem4v7y2t9w",
"input": {
"seed": 0,
"images": [
"https://replicate.delivery/pbxt/ML1p0eA4AEhEvXPlIzds5RWD4axHK8Qj5276Q4Gi9aAuqg1G/20250117_144447.jpg",
"https://replicate.delivery/pbxt/ML1p0XhuTj7PjRPOIfN3q0ZNurZgN3EgWjuYI5ISHMl7DlmJ/20250117_144443.jpg",
"https://replicate.delivery/pbxt/ML1ozyZUROpp5iLoLEI2SWn4YBe5jmJ5DPxrjg9FivKLvKEl/20250117_144437.jpg",
"https://replicate.delivery/pbxt/ML1p0TLpeGDAMlEranut1WEJNljGKP94IV0PdtRtnrbpHCeX/20250117_144431.jpg",
"https://replicate.delivery/pbxt/ML1p0rXh6U26VEzshLLFZq30UzVk6zsc11AOIfhYoDIbepn1/20250117_144423.jpg"
],
"texture_size": 2048,
"mesh_simplify": 0.9,
"generate_color": true,
"generate_model": true,
"randomize_seed": true,
"generate_normal": false,
"save_gaussian_ply": true,
"ss_sampling_steps": 38,
"slat_sampling_steps": 12,
"return_no_background": false,
"ss_guidance_strength": 7.5,
"slat_guidance_strength": 3
},
"logs": "INFO:predict:Loading and preprocessing input images...\nINFO:predict:Using randomized seed: 891671724\nINFO:predict:Running TRELLIS pipeline...\nSampling: 0%| | 0/38 [00:00<?, ?it/s]\nSampling: 3%|▎ | 1/38 [00:00<00:04, 9.20it/s]\nSampling: 8%|▊ | 3/38 [00:00<00:03, 10.66it/s]\nSampling: 13%|█▎ | 5/38 [00:00<00:03, 10.99it/s]\nSampling: 18%|█▊ | 7/38 [00:00<00:02, 11.12it/s]\nSampling: 24%|██▎ | 9/38 [00:00<00:02, 11.18it/s]\nSampling: 29%|██▉ | 11/38 [00:00<00:02, 11.20it/s]\nSampling: 34%|███▍ | 13/38 [00:01<00:02, 11.24it/s]\nSampling: 39%|███▉ | 15/38 [00:01<00:02, 11.26it/s]\nSampling: 45%|████▍ | 17/38 [00:01<00:01, 11.28it/s]\nSampling: 50%|█████ | 19/38 [00:01<00:01, 11.27it/s]\nSampling: 55%|█████▌ | 21/38 [00:01<00:01, 11.24it/s]\nSampling: 61%|██████ | 23/38 [00:02<00:01, 11.27it/s]\nSampling: 66%|██████▌ | 25/38 [00:02<00:01, 11.28it/s]\nSampling: 71%|███████ | 27/38 [00:02<00:00, 11.28it/s]\nSampling: 76%|███████▋ | 29/38 [00:02<00:00, 11.28it/s]\nSampling: 84%|████████▍ | 32/38 [00:02<00:00, 14.05it/s]\nSampling: 92%|█████████▏| 35/38 [00:02<00:00, 16.21it/s]\nSampling: 100%|██████████| 38/38 [00:02<00:00, 17.89it/s]\nSampling: 100%|██████████| 38/38 [00:02<00:00, 12.71it/s]\nSampling: 0%| | 0/12 [00:00<?, ?it/s]\nSampling: 8%|▊ | 1/12 [00:00<00:02, 4.00it/s]\nSampling: 17%|█▋ | 2/12 [00:00<00:02, 4.68it/s]\nSampling: 25%|██▌ | 3/12 [00:00<00:01, 4.95it/s]\nSampling: 33%|███▎ | 4/12 [00:00<00:01, 5.08it/s]\nSampling: 42%|████▏ | 5/12 [00:01<00:01, 5.15it/s]\nSampling: 50%|█████ | 6/12 [00:01<00:01, 5.16it/s]\nSampling: 58%|█████▊ | 7/12 [00:01<00:00, 5.22it/s]\nSampling: 67%|██████▋ | 8/12 [00:01<00:00, 5.26it/s]\nSampling: 75%|███████▌ | 9/12 [00:01<00:00, 5.27it/s]\nSampling: 83%|████████▎ | 10/12 [00:01<00:00, 5.26it/s]\nSampling: 100%|██████████| 12/12 [00:02<00:00, 6.88it/s]\nSampling: 100%|██████████| 12/12 [00:02<00:00, 5.60it/s]\nINFO:predict:TRELLIS pipeline complete!\nINFO:predict:Available output formats: dict_keys(['mesh', 'gaussian'])\nINFO:predict:Starting video rendering...\nINFO:predict:Generating color video from gaussian output...\nRendering: 0it [00:00, ?it/s]\nRendering: 19it [00:00, 187.20it/s]\nRendering: 45it [00:00, 226.43it/s]\nRendering: 68it [00:00, 227.46it/s]\nRendering: 93it [00:00, 235.15it/s]\nRendering: 117it [00:00, 233.63it/s]\nRendering: 120it [00:00, 229.23it/s]\nINFO:predict:Available gaussian render types: ['color', 'depth']\nINFO:predict:Generated color video successfully\nINFO:predict:Video rendering complete!\nINFO:predict:Generating GLB model...\nINFO- Loaded 11214 vertices and 22292 faces.\n0% done\n14% done\n28% done\n42% done\n57% done\n71% done\n85% done\n100% done\nWARNING- Some cuts were necessary to cope with non manifold configuration.\nRendering: 0it [00:00, ?it/s]\nRendering: 11it [00:00, 103.60it/s]\nRendering: 23it [00:00, 110.80it/s]\nRendering: 35it [00:00, 113.82it/s]\nRendering: 47it [00:00, 114.74it/s]\nRendering: 59it [00:00, 115.59it/s]\nRendering: 71it [00:00, 114.19it/s]\nRendering: 83it [00:00, 113.60it/s]\nRendering: 95it [00:00, 114.66it/s]\nRendering: 100it [00:00, 113.91it/s]\nINFO:predict:GLB model generation complete!\nINFO:predict:Saving Gaussian point cloud as PLY...\nINFO:predict:Gaussian PLY file saved successfully!\nINFO:predict:Prediction complete! Returning results...",
"metrics": {
"predict_time": 70.578317478,
"total_time": 227.564741
},
"output": {
"model_file": "https://replicate.delivery/yhqm/ZeryUVHg64we6EwKh44TxkO6HVZZWaQveBafideoZLeZR0gBF/output.glb",
"color_video": "https://replicate.delivery/yhqm/OMLHE43og7ooOBlpAmkxppfXqgDdgilzbXgnsDPRInwioBDKA/output_color.mp4",
"gaussian_ply": "https://replicate.delivery/yhqm/juaXDr5cNTIBNR1jx6A6J4u8pwFeXllFbvojb1ky6w7ioBDKA/output_gaussian.ply",
"normal_video": null,
"combined_video": null,
"no_background_images": null
},
"started_at": "2025-01-17T16:14:55.799423Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/xg5e45k9znrj40cmem4v7y2t9w",
"cancel": "https://api.replicate.com/v1/predictions/xg5e45k9znrj40cmem4v7y2t9w/cancel"
},
"version": "4876f2a8da1c544772dffa32e8889da4a1bab3a1f5c1937bfcfccb99ae347251"
}
INFO:predict:Loading and preprocessing input images...
INFO:predict:Using randomized seed: 891671724
INFO:predict:Running TRELLIS pipeline...
Sampling: 0%| | 0/38 [00:00<?, ?it/s]
Sampling: 3%|▎ | 1/38 [00:00<00:04, 9.20it/s]
Sampling: 8%|▊ | 3/38 [00:00<00:03, 10.66it/s]
Sampling: 13%|█▎ | 5/38 [00:00<00:03, 10.99it/s]
Sampling: 18%|█▊ | 7/38 [00:00<00:02, 11.12it/s]
Sampling: 24%|██▎ | 9/38 [00:00<00:02, 11.18it/s]
Sampling: 29%|██▉ | 11/38 [00:00<00:02, 11.20it/s]
Sampling: 34%|███▍ | 13/38 [00:01<00:02, 11.24it/s]
Sampling: 39%|███▉ | 15/38 [00:01<00:02, 11.26it/s]
Sampling: 45%|████▍ | 17/38 [00:01<00:01, 11.28it/s]
Sampling: 50%|█████ | 19/38 [00:01<00:01, 11.27it/s]
Sampling: 55%|█████▌ | 21/38 [00:01<00:01, 11.24it/s]
Sampling: 61%|██████ | 23/38 [00:02<00:01, 11.27it/s]
Sampling: 66%|██████▌ | 25/38 [00:02<00:01, 11.28it/s]
Sampling: 71%|███████ | 27/38 [00:02<00:00, 11.28it/s]
Sampling: 76%|███████▋ | 29/38 [00:02<00:00, 11.28it/s]
Sampling: 84%|████████▍ | 32/38 [00:02<00:00, 14.05it/s]
Sampling: 92%|█████████▏| 35/38 [00:02<00:00, 16.21it/s]
Sampling: 100%|██████████| 38/38 [00:02<00:00, 17.89it/s]
Sampling: 100%|██████████| 38/38 [00:02<00:00, 12.71it/s]
Sampling: 0%| | 0/12 [00:00<?, ?it/s]
Sampling: 8%|▊ | 1/12 [00:00<00:02, 4.00it/s]
Sampling: 17%|█▋ | 2/12 [00:00<00:02, 4.68it/s]
Sampling: 25%|██▌ | 3/12 [00:00<00:01, 4.95it/s]
Sampling: 33%|███▎ | 4/12 [00:00<00:01, 5.08it/s]
Sampling: 42%|████▏ | 5/12 [00:01<00:01, 5.15it/s]
Sampling: 50%|█████ | 6/12 [00:01<00:01, 5.16it/s]
Sampling: 58%|█████▊ | 7/12 [00:01<00:00, 5.22it/s]
Sampling: 67%|██████▋ | 8/12 [00:01<00:00, 5.26it/s]
Sampling: 75%|███████▌ | 9/12 [00:01<00:00, 5.27it/s]
Sampling: 83%|████████▎ | 10/12 [00:01<00:00, 5.26it/s]
Sampling: 100%|██████████| 12/12 [00:02<00:00, 6.88it/s]
Sampling: 100%|██████████| 12/12 [00:02<00:00, 5.60it/s]
INFO:predict:TRELLIS pipeline complete!
INFO:predict:Available output formats: dict_keys(['mesh', 'gaussian'])
INFO:predict:Starting video rendering...
INFO:predict:Generating color video from gaussian output...
Rendering: 0it [00:00, ?it/s]
Rendering: 19it [00:00, 187.20it/s]
Rendering: 45it [00:00, 226.43it/s]
Rendering: 68it [00:00, 227.46it/s]
Rendering: 93it [00:00, 235.15it/s]
Rendering: 117it [00:00, 233.63it/s]
Rendering: 120it [00:00, 229.23it/s]
INFO:predict:Available gaussian render types: ['color', 'depth']
INFO:predict:Generated color video successfully
INFO:predict:Video rendering complete!
INFO:predict:Generating GLB model...
INFO- Loaded 11214 vertices and 22292 faces.
0% done
14% done
28% done
42% done
57% done
71% done
85% done
100% done
WARNING- Some cuts were necessary to cope with non manifold configuration.
Rendering: 0it [00:00, ?it/s]
Rendering: 11it [00:00, 103.60it/s]
Rendering: 23it [00:00, 110.80it/s]
Rendering: 35it [00:00, 113.82it/s]
Rendering: 47it [00:00, 114.74it/s]
Rendering: 59it [00:00, 115.59it/s]
Rendering: 71it [00:00, 114.19it/s]
Rendering: 83it [00:00, 113.60it/s]
Rendering: 95it [00:00, 114.66it/s]
Rendering: 100it [00:00, 113.91it/s]
INFO:predict:GLB model generation complete!
INFO:predict:Saving Gaussian point cloud as PLY...
INFO:predict:Gaussian PLY file saved successfully!
INFO:predict:Prediction complete! Returning results...