mamorett / samothraki-upscaler
An upscaler based on tile and inpaint controlnets, aimed to preserve the original image while injecting more details. (Updated 3 months, 1 week ago)
Prediction
mamorett/samothraki-upscaler:c3a0140d658919e87f0cd529c978f6246a00c135d6ade54958030c28ca1a2c60IDmecfqc7spsrme0cn4xb8ynr7prStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- hdr
- 0
- image
- denoise
- 1
- upscaler
- 4x_NMKD-Siax_200k
- upscale_by
- 2
- guidance_scale
- 3
- color_correction
- num_inference_steps
- 20
{ "hdr": 0, "image": "https://replicate.delivery/pbxt/MXJmd3p7qNuirILUq3CVYBo1EKAJAUnAlofHYDkX83OF4jpt/_trithemius_a_vapour_Ghost_in_a_forest_in_autumn_Fuji_color_fil_3a4634fe-79f1-4ffc-a168-2ff3b01b11a3.png_flux_dev8_0003.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 }Install Replicate’s Node.js client library:npm install replicateImport 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 mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mamorett/samothraki-upscaler:c3a0140d658919e87f0cd529c978f6246a00c135d6ade54958030c28ca1a2c60", { input: { hdr: 0, image: "https://replicate.delivery/pbxt/MXJmd3p7qNuirILUq3CVYBo1EKAJAUnAlofHYDkX83OF4jpt/_trithemius_a_vapour_Ghost_in_a_forest_in_autumn_Fuji_color_fil_3a4634fe-79f1-4ffc-a168-2ff3b01b11a3.png_flux_dev8_0003.png", denoise: 1, upscaler: "4x_NMKD-Siax_200k", upscale_by: 2, guidance_scale: 3, color_correction: true, num_inference_steps: 20 } } ); // 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 replicateImport the client:import replicateRun mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mamorett/samothraki-upscaler:c3a0140d658919e87f0cd529c978f6246a00c135d6ade54958030c28ca1a2c60", input={ "hdr": 0, "image": "https://replicate.delivery/pbxt/MXJmd3p7qNuirILUq3CVYBo1EKAJAUnAlofHYDkX83OF4jpt/_trithemius_a_vapour_Ghost_in_a_forest_in_autumn_Fuji_color_fil_3a4634fe-79f1-4ffc-a168-2ff3b01b11a3.png_flux_dev8_0003.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": True, "num_inference_steps": 20 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mamorett/samothraki-upscaler 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": "mamorett/samothraki-upscaler:c3a0140d658919e87f0cd529c978f6246a00c135d6ade54958030c28ca1a2c60", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MXJmd3p7qNuirILUq3CVYBo1EKAJAUnAlofHYDkX83OF4jpt/_trithemius_a_vapour_Ghost_in_a_forest_in_autumn_Fuji_color_fil_3a4634fe-79f1-4ffc-a168-2ff3b01b11a3.png_flux_dev8_0003.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-21T07:11:33.793351Z", "created_at": "2025-02-21T07:09:26.326000Z", "data_removed": false, "error": null, "id": "mecfqc7spsrme0cn4xb8ynr7pr", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MXJmd3p7qNuirILUq3CVYBo1EKAJAUnAlofHYDkX83OF4jpt/_trithemius_a_vapour_Ghost_in_a_forest_in_autumn_Fuji_color_fil_3a4634fe-79f1-4ffc-a168-2ff3b01b11a3.png_flux_dev8_0003.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 }, "logs": "0%| | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/utils/torch_utils.py:110: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. (Triggered internally at /pytorch/aten/src/ATen/EmptyTensor.cpp:50.)\nx_freq = fftn(x, dim=(-2, -1))\n 5%|▌ | 1/20 [00:00<00:11, 1.64it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.97it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 7.94it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 10.40it/s]\n 45%|████▌ | 9/20 [00:01<00:00, 12.42it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.83it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.96it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 15.81it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 16.39it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 16.88it/s]\n100%|██████████| 20/20 [00:01<00:00, 11.95it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:08, 2.18it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 6.18it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 9.26it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.62it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 13.43it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 14.61it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 15.60it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 16.36it/s]\n 85%|████████▌ | 17/20 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16.31it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 16.79it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 16.96it/s]\n100%|██████████| 20/20 [00:01<00:00, 13.13it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:09, 2.11it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 6.04it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 9.18it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.58it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 13.30it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 14.55it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 15.51it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 16.24it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 16.56it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 16.93it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.94it/s]", "metrics": { "predict_time": 55.523241014999996, "total_time": 127.467351 }, "output": "https://replicate.delivery/xezq/fVILnN3h1etArEJLfGBjKzcmLMK26d7mlccUSluUEMeWS2FRB/output.png", "started_at": "2025-02-21T07:10:38.270110Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-pcdbkcwfbvbih5w27rmjm3ruo2vdksxms5ntmppwijbldlh5ny7q", "get": "https://api.replicate.com/v1/predictions/mecfqc7spsrme0cn4xb8ynr7pr", "cancel": "https://api.replicate.com/v1/predictions/mecfqc7spsrme0cn4xb8ynr7pr/cancel" }, "version": "c3a0140d658919e87f0cd529c978f6246a00c135d6ade54958030c28ca1a2c60" }Generated in0%| | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/utils/torch_utils.py:110: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. 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| 15/20 [00:01<00:00, 16.24it/s] 85%|████████▌ | 17/20 [00:01<00:00, 16.56it/s] 95%|█████████▌| 19/20 [00:01<00:00, 16.93it/s] 100%|██████████| 20/20 [00:01<00:00, 12.94it/s]Prediction
mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52eIDejbe47bsynrme0cn4ycbavq5ngStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- hdr
- 0
- image
- denoise
- 1
- upscaler
- 4x_NMKD-Siax_200k
- upscale_by
- 2
- guidance_scale
- 3
- color_correction
- num_inference_steps
- 20
{ "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKsQbPIxB6Wa3BhG90yVelZCLIGfByJcPTtZ6SADR2JReYy/FB_IMG_1735132317491.jpg_flux_dev8_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 }Install Replicate’s Node.js client library:npm install replicateImport 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 mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e", { input: { hdr: 0, image: "https://replicate.delivery/pbxt/MXKsQbPIxB6Wa3BhG90yVelZCLIGfByJcPTtZ6SADR2JReYy/FB_IMG_1735132317491.jpg_flux_dev8_0001.png", denoise: 1, upscaler: "4x_NMKD-Siax_200k", upscale_by: 2, guidance_scale: 3, color_correction: true, num_inference_steps: 20 } } ); // 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 replicateImport the client:import replicateRun mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e", input={ "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKsQbPIxB6Wa3BhG90yVelZCLIGfByJcPTtZ6SADR2JReYy/FB_IMG_1735132317491.jpg_flux_dev8_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": True, "num_inference_steps": 20 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mamorett/samothraki-upscaler 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": "mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKsQbPIxB6Wa3BhG90yVelZCLIGfByJcPTtZ6SADR2JReYy/FB_IMG_1735132317491.jpg_flux_dev8_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-21T08:23:41.468089Z", "created_at": "2025-02-21T08:20:58.997000Z", "data_removed": false, "error": null, "id": "ejbe47bsynrme0cn4ycbavq5ng", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKsQbPIxB6Wa3BhG90yVelZCLIGfByJcPTtZ6SADR2JReYy/FB_IMG_1735132317491.jpg_flux_dev8_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 }, "logs": "0%| | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/utils/torch_utils.py:110: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. (Triggered internally at /pytorch/aten/src/ATen/EmptyTensor.cpp:50.)\nx_freq = fftn(x, dim=(-2, -1))\n 5%|▌ | 1/20 [00:00<00:11, 1.68it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 5.04it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 7.88it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 10.23it/s]\n 45%|████▌ | 9/20 [00:01<00:00, 12.04it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.36it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.33it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 15.09it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 15.66it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 16.06it/s]\n100%|██████████| 20/20 [00:01<00:00, 11.64it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:08, 2.13it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 6.01it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 8.95it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.11it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 12.70it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.81it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.66it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 15.15it/s]\n 85%|████████▌ | 17/20 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12.22it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:09, 2.08it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 5.86it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 8.74it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 10.82it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 12.25it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.47it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.26it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 14.94it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 15.40it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 15.77it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.01it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:08, 2.14it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 6.00it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 8.97it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.15it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 12.75it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.94it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.87it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 15.53it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 16.11it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 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15.85it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 15.16it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.17it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:09, 1.95it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 5.68it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 8.69it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.00it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 12.76it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.97it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.98it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 15.64it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 16.14it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 16.56it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.40it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:09, 2.00it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 5.69it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 8.62it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 10.65it/s]\n 45%|████▌ | 9/20 [00:01<00:00, 11.76it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 12.49it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 12.96it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 13.82it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 14.47it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 14.88it/s]\n100%|██████████| 20/20 [00:01<00:00, 11.55it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:09, 2.06it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 5.93it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 8.99it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.12it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 12.92it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 14.08it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.81it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 15.10it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 15.70it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 16.00it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.20it/s]", "metrics": { "predict_time": 57.194666763, "total_time": 162.471089 }, "output": "https://replicate.delivery/xezq/Iloj04wcKMIeOS9pfMwyDNJC6tOxhleLOS8SBkEG5sbaQ9ioA/output.png", "started_at": "2025-02-21T08:22:44.273422Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-257htuxgdt3je4uhwfdfhu3ujzrqn6mwuggk46p45squhk6goujq", "get": "https://api.replicate.com/v1/predictions/ejbe47bsynrme0cn4ycbavq5ng", "cancel": "https://api.replicate.com/v1/predictions/ejbe47bsynrme0cn4ycbavq5ng/cancel" }, "version": "423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e" }Generated in0%| | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/utils/torch_utils.py:110: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. 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mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52eIDwxwkkk96nnrm80cn4yetzg505gStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- hdr
- 0
- image
- denoise
- 1
- upscaler
- 4x_NMKD-Siax_200k
- upscale_by
- 2
- guidance_scale
- 3
- color_correction
- num_inference_steps
- 20
{ "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKxGd3rAIynZHXnoOl2yfdABF9IgOJ6pTQUGbAoff6sjWBv/Trithemiana%201.0_00001___0012.png_realvisxlV50_v50Bakedvae_0001.png_flux_dev8_0002.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 }Install Replicate’s Node.js client library:npm install replicateImport 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 mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e", { input: { hdr: 0, image: "https://replicate.delivery/pbxt/MXKxGd3rAIynZHXnoOl2yfdABF9IgOJ6pTQUGbAoff6sjWBv/Trithemiana%201.0_00001___0012.png_realvisxlV50_v50Bakedvae_0001.png_flux_dev8_0002.png", denoise: 1, upscaler: "4x_NMKD-Siax_200k", upscale_by: 2, guidance_scale: 3, color_correction: true, num_inference_steps: 20 } } ); // 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 replicateImport the client:import replicateRun mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e", input={ "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKxGd3rAIynZHXnoOl2yfdABF9IgOJ6pTQUGbAoff6sjWBv/Trithemiana%201.0_00001___0012.png_realvisxlV50_v50Bakedvae_0001.png_flux_dev8_0002.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": True, "num_inference_steps": 20 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mamorett/samothraki-upscaler 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": "mamorett/samothraki-upscaler:423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKxGd3rAIynZHXnoOl2yfdABF9IgOJ6pTQUGbAoff6sjWBv/Trithemiana%201.0_00001___0012.png_realvisxlV50_v50Bakedvae_0001.png_flux_dev8_0002.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-21T08:28:15.551143Z", "created_at": "2025-02-21T08:26:05.357000Z", "data_removed": false, "error": null, "id": "wxwkkk96nnrm80cn4yetzg505g", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MXKxGd3rAIynZHXnoOl2yfdABF9IgOJ6pTQUGbAoff6sjWBv/Trithemiana%201.0_00001___0012.png_realvisxlV50_v50Bakedvae_0001.png_flux_dev8_0002.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "color_correction": true, "num_inference_steps": 20 }, "logs": "0%| | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/utils/torch_utils.py:110: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. 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15.16it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 15.58it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 15.79it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.38it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:08, 2.12it/s]\n 15%|█▌ | 3/20 [00:00<00:02, 5.99it/s]\n 25%|██▌ | 5/20 [00:00<00:01, 8.90it/s]\n 35%|███▌ | 7/20 [00:00<00:01, 11.04it/s]\n 45%|████▌ | 9/20 [00:00<00:00, 12.59it/s]\n 55%|█████▌ | 11/20 [00:01<00:00, 13.72it/s]\n 65%|██████▌ | 13/20 [00:01<00:00, 14.46it/s]\n 75%|███████▌ | 15/20 [00:01<00:00, 15.07it/s]\n 85%|████████▌ | 17/20 [00:01<00:00, 15.31it/s]\n 95%|█████████▌| 19/20 [00:01<00:00, 15.55it/s]\n100%|██████████| 20/20 [00:01<00:00, 12.24it/s]", "metrics": { "predict_time": 56.636006346, "total_time": 130.194143 }, "output": "https://replicate.delivery/xezq/FMQYsjQE2qZCPJIUfq9VsG8qDhfMjrOrZbFI3hoIdANfY9ioA/output.png", "started_at": "2025-02-21T08:27:18.915137Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-5tf6ijjnqamnga24s7srmf26jshhx3hxgry4kx7wspr7fymw2zoa", "get": "https://api.replicate.com/v1/predictions/wxwkkk96nnrm80cn4yetzg505g", "cancel": "https://api.replicate.com/v1/predictions/wxwkkk96nnrm80cn4yetzg505g/cancel" }, "version": "423119f693198fd011fedb9785c93e74e68ea4bfa973b6c0ed3f1216c436f52e" }Generated in0%| | 0/20 [00:00<?, ?it/s]/root/.pyenv/versions/3.11.10/lib/python3.11/site-packages/diffusers/utils/torch_utils.py:110: UserWarning: ComplexHalf support is experimental and many operators don't support it yet. 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| 15/20 [00:01<00:00, 15.07it/s] 85%|████████▌ | 17/20 [00:01<00:00, 15.31it/s] 95%|█████████▌| 19/20 [00:01<00:00, 15.55it/s] 100%|██████████| 20/20 [00:01<00:00, 12.24it/s]Prediction
mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99dID6n632vqm8drma0cnc4atfp6xnrStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- hdr
- 0
- image
- denoise
- 1
- upscaler
- 4x_NMKD-Siax_200k
- upscale_by
- 2
- guidance_scale
- 3
- calculate_tiles
- color_correction
- num_inference_steps
- 20
{ "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIYSSjsgejBsVc25KaJFiUzAEcx7MNhLZaAoMymmbCD6Xgp/trithemius_front_view_photograph_of_very_skinny_Nicole_Richie__0de58ba4-57a1-49d0-92c5-c2e3a08c209b.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": false, "color_correction": true, "num_inference_steps": 20 }Install Replicate’s Node.js client library:npm install replicateImport 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 mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d", { input: { hdr: 0, image: "https://replicate.delivery/pbxt/MbIYSSjsgejBsVc25KaJFiUzAEcx7MNhLZaAoMymmbCD6Xgp/trithemius_front_view_photograph_of_very_skinny_Nicole_Richie__0de58ba4-57a1-49d0-92c5-c2e3a08c209b.png", denoise: 1, upscaler: "4x_NMKD-Siax_200k", upscale_by: 2, guidance_scale: 3, calculate_tiles: false, color_correction: true, num_inference_steps: 20 } } ); // 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 replicateImport the client:import replicateRun mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d", input={ "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIYSSjsgejBsVc25KaJFiUzAEcx7MNhLZaAoMymmbCD6Xgp/trithemius_front_view_photograph_of_very_skinny_Nicole_Richie__0de58ba4-57a1-49d0-92c5-c2e3a08c209b.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": False, "color_correction": True, "num_inference_steps": 20 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mamorett/samothraki-upscaler 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": "mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIYSSjsgejBsVc25KaJFiUzAEcx7MNhLZaAoMymmbCD6Xgp/trithemius_front_view_photograph_of_very_skinny_Nicole_Richie__0de58ba4-57a1-49d0-92c5-c2e3a08c209b.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": false, "color_correction": true, "num_inference_steps": 20 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-04T12:17:11.820870Z", "created_at": "2025-03-04T12:16:23.619000Z", "data_removed": false, "error": null, "id": "6n632vqm8drma0cnc4atfp6xnr", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIYSSjsgejBsVc25KaJFiUzAEcx7MNhLZaAoMymmbCD6Xgp/trithemius_front_view_photograph_of_very_skinny_Nicole_Richie__0de58ba4-57a1-49d0-92c5-c2e3a08c209b.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": false, "color_correction": true, "num_inference_steps": 20 }, "logs": "Starting image processing...\nImage Width (W): 2048\nImage Height (H): 2048\nTile Width: 1024\nTile Height: 1024\nOverlap: 64\nNumber of Tiles in X direction: 3\nNumber of Tiles in Y direction: 3\nTotal Number of Tiles: 9\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:12, 1.50it/s]\n 10%|█ | 2/20 [00:00<00:06, 2.63it/s]\n 15%|█▌ | 3/20 [00:01<00:04, 3.47it/s]\n 20%|██ | 4/20 [00:01<00:03, 4.09it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 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[00:02<00:01, 5.43it/s]\n 70%|███████ | 14/20 [00:03<00:01, 5.47it/s]\n 75%|███████▌ | 15/20 [00:03<00:00, 5.47it/s]\n 80%|████████ | 16/20 [00:03<00:00, 5.49it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 5.49it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 5.51it/s]\n 95%|█████████▌| 19/20 [00:03<00:00, 5.50it/s]\n100%|██████████| 20/20 [00:04<00:00, 5.49it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.85it/s]", "metrics": { "predict_time": 48.194562598, "total_time": 48.20187 }, "output": "https://replicate.delivery/xezq/0juf143QDejPjUz2pHbVCuY2hyRFba97VGkRUeKWa3hOKUqoA/output.png", "started_at": "2025-03-04T12:16:23.626308Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-n6xixtfncyjmf6pj5isvy3bchs4wkozba4mozjblwz22fbersaja", "get": "https://api.replicate.com/v1/predictions/6n632vqm8drma0cnc4atfp6xnr", "cancel": "https://api.replicate.com/v1/predictions/6n632vqm8drma0cnc4atfp6xnr/cancel" }, "version": "7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d" }Generated inStarting image processing... Image Width (W): 2048 Image Height (H): 2048 Tile Width: 1024 Tile Height: 1024 Overlap: 64 Number of Tiles in X direction: 3 Number of Tiles in Y direction: 3 Total Number of Tiles: 9 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.50it/s] 10%|█ | 2/20 [00:00<00:06, 2.63it/s] 15%|█▌ | 3/20 [00:01<00:04, 3.47it/s] 20%|██ | 4/20 [00:01<00:03, 4.09it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.51it/s] 30%|███ | 6/20 [00:01<00:02, 4.83it/s] 35%|███▌ | 7/20 [00:01<00:02, 5.04it/s] 40%|████ | 8/20 [00:01<00:02, 5.19it/s] 45%|████▌ | 9/20 [00:02<00:02, 5.31it/s] 50%|█████ | 10/20 [00:02<00:01, 5.40it/s] 55%|█████▌ | 11/20 [00:02<00:01, 5.43it/s] 60%|██████ | 12/20 [00:02<00:01, 5.48it/s] 65%|██████▌ | 13/20 [00:02<00:01, 5.50it/s] 70%|███████ | 14/20 [00:03<00:01, 5.51it/s] 75%|███████▌ | 15/20 [00:03<00:00, 5.50it/s] 80%|████████ | 16/20 [00:03<00:00, 5.52it/s] 85%|████████▌ | 17/20 [00:03<00:00, 5.53it/s] 90%|█████████ | 18/20 [00:03<00:00, 5.55it/s] 95%|█████████▌| 19/20 [00:03<00:00, 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mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99dIDcrsg9vjc15rm80cnc49batnrswStatusSucceededSourceWebHardwareL40STotal durationCreatedInput
- hdr
- 0
- image
- denoise
- 1
- upscaler
- 4x_NMKD-Siax_200k
- upscale_by
- 2
- guidance_scale
- 3
- calculate_tiles
- color_correction
- num_inference_steps
- 20
{ "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIUgMsmafzMJIdxIbsXnZ8IhkDyFJdyWfSZpdK1f3ugUXhM/2025-02-19_08-58-32_4620.png_fluxHyper-FLUX.1-dev-8steps-lora_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": false, "color_correction": true, "num_inference_steps": 20 }Install Replicate’s Node.js client library:npm install replicateImport 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 mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d", { input: { hdr: 0, image: "https://replicate.delivery/pbxt/MbIUgMsmafzMJIdxIbsXnZ8IhkDyFJdyWfSZpdK1f3ugUXhM/2025-02-19_08-58-32_4620.png_fluxHyper-FLUX.1-dev-8steps-lora_0001.png", denoise: 1, upscaler: "4x_NMKD-Siax_200k", upscale_by: 2, guidance_scale: 3, calculate_tiles: false, color_correction: true, num_inference_steps: 20 } } ); // 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 replicateImport the client:import replicateRun mamorett/samothraki-upscaler using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d", input={ "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIUgMsmafzMJIdxIbsXnZ8IhkDyFJdyWfSZpdK1f3ugUXhM/2025-02-19_08-58-32_4620.png_fluxHyper-FLUX.1-dev-8steps-lora_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": False, "color_correction": True, "num_inference_steps": 20 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run mamorett/samothraki-upscaler 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": "mamorett/samothraki-upscaler:7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIUgMsmafzMJIdxIbsXnZ8IhkDyFJdyWfSZpdK1f3ugUXhM/2025-02-19_08-58-32_4620.png_fluxHyper-FLUX.1-dev-8steps-lora_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": false, "color_correction": true, "num_inference_steps": 20 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-03-04T12:12:57.172679Z", "created_at": "2025-03-04T12:12:23.945000Z", "data_removed": false, "error": null, "id": "crsg9vjc15rm80cnc49batnrsw", "input": { "hdr": 0, "image": "https://replicate.delivery/pbxt/MbIUgMsmafzMJIdxIbsXnZ8IhkDyFJdyWfSZpdK1f3ugUXhM/2025-02-19_08-58-32_4620.png_fluxHyper-FLUX.1-dev-8steps-lora_0001.png", "denoise": 1, "upscaler": "4x_NMKD-Siax_200k", "upscale_by": 2, "guidance_scale": 3, "calculate_tiles": false, "color_correction": true, "num_inference_steps": 20 }, "logs": "Starting image processing...\nImage Width (W): 1664\nImage Height (H): 2432\nTile Width: 1024\nTile Height: 1024\nOverlap: 64\nNumber of Tiles in X direction: 2\nNumber of Tiles in Y direction: 3\nTotal Number of Tiles: 6\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:12, 1.50it/s]\n 10%|█ | 2/20 [00:00<00:06, 2.61it/s]\n 15%|█▌ | 3/20 [00:01<00:04, 3.43it/s]\n 20%|██ | 4/20 [00:01<00:03, 4.04it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.46it/s]\n 30%|███ | 6/20 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[00:02<00:02, 5.28it/s]\n 50%|█████ | 10/20 [00:02<00:01, 5.32it/s]\n 55%|█████▌ | 11/20 [00:02<00:01, 5.35it/s]\n 60%|██████ | 12/20 [00:02<00:01, 5.40it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 5.41it/s]\n 70%|███████ | 14/20 [00:03<00:01, 5.45it/s]\n 75%|███████▌ | 15/20 [00:03<00:00, 5.45it/s]\n 80%|████████ | 16/20 [00:03<00:00, 5.47it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.58it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 4.27it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.41it/s]\n100%|██████████| 20/20 [00:04<00:00, 3.98it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.46it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:12, 1.50it/s]\n 10%|█ | 2/20 [00:00<00:06, 2.62it/s]\n 15%|█▌ | 3/20 [00:01<00:04, 3.44it/s]\n 20%|██ | 4/20 [00:01<00:03, 4.04it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.44it/s]\n 30%|███ | 6/20 [00:01<00:02, 4.75it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.95it/s]\n 40%|████ | 8/20 [00:01<00:02, 5.12it/s]\n 45%|████▌ | 9/20 [00:02<00:02, 5.22it/s]\n 50%|█████ | 10/20 [00:02<00:01, 5.30it/s]\n 55%|█████▌ | 11/20 [00:02<00:01, 5.35it/s]\n 60%|██████ | 12/20 [00:02<00:01, 5.38it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 5.41it/s]\n 70%|███████ | 14/20 [00:03<00:01, 5.44it/s]\n 75%|███████▌ | 15/20 [00:03<00:00, 5.46it/s]\n 80%|████████ | 16/20 [00:03<00:00, 5.47it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 5.49it/s]\n 90%|█████████ | 18/20 [00:03<00:00, 5.51it/s]\n 95%|█████████▌| 19/20 [00:03<00:00, 5.49it/s]\n100%|██████████| 20/20 [00:04<00:00, 5.47it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.84it/s]\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:12, 1.48it/s]\n 10%|█ | 2/20 [00:00<00:06, 2.60it/s]\n 15%|█▌ | 3/20 [00:01<00:04, 3.41it/s]\n 20%|██ | 4/20 [00:01<00:03, 4.03it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.44it/s]\n 30%|███ | 6/20 [00:01<00:02, 4.77it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.97it/s]\n 40%|████ | 8/20 [00:01<00:02, 5.13it/s]\n 45%|████▌ | 9/20 [00:02<00:02, 5.24it/s]\n 50%|█████ | 10/20 [00:02<00:01, 5.34it/s]\n 55%|█████▌ | 11/20 [00:02<00:01, 5.38it/s]\n 60%|██████ | 12/20 [00:02<00:01, 5.43it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 5.44it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.38it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.67it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.49it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.50it/s]\n 90%|█████████ | 18/20 [00:04<00:00, 4.76it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 3.15it/s]\n100%|██████████| 20/20 [00:04<00:00, 3.60it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.20it/s]", "metrics": { "predict_time": 33.220818998, "total_time": 33.227679 }, "output": "https://replicate.delivery/xezq/4ackiAOvPhqHMRmsqmHqvnXFXfahXgv15peoo7Y5ivQJBKVUA/output.png", "started_at": "2025-03-04T12:12:23.951860Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/bcwr-woct74tqbdrzdu3gstc35ylzn4pu2o4kl5sx3iaotqcqhfscsnfq", "get": "https://api.replicate.com/v1/predictions/crsg9vjc15rm80cnc49batnrsw", "cancel": "https://api.replicate.com/v1/predictions/crsg9vjc15rm80cnc49batnrsw/cancel" }, "version": "7cf467dbd284920e360fa341dbf2d44cb4144de9b54131781082d6ea67ece99d" }Generated inStarting image processing... Image Width (W): 1664 Image Height (H): 2432 Tile Width: 1024 Tile Height: 1024 Overlap: 64 Number of Tiles in X direction: 2 Number of Tiles in Y direction: 3 Total Number of Tiles: 6 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.50it/s] 10%|█ | 2/20 [00:00<00:06, 2.61it/s] 15%|█▌ | 3/20 [00:01<00:04, 3.43it/s] 20%|██ | 4/20 [00:01<00:03, 4.04it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.46it/s] 30%|███ | 6/20 [00:01<00:02, 4.78it/s] 35%|███▌ | 7/20 [00:01<00:02, 5.01it/s] 40%|████ | 8/20 [00:01<00:02, 5.16it/s] 45%|████▌ | 9/20 [00:02<00:02, 5.27it/s] 50%|█████ | 10/20 [00:02<00:01, 5.34it/s] 55%|█████▌ | 11/20 [00:02<00:01, 5.38it/s] 60%|██████ | 12/20 [00:02<00:01, 5.42it/s] 65%|██████▌ | 13/20 [00:02<00:01, 5.45it/s] 70%|███████ | 14/20 [00:03<00:01, 5.47it/s] 75%|███████▌ | 15/20 [00:03<00:00, 5.47it/s] 80%|████████ | 16/20 [00:03<00:00, 5.49it/s] 85%|████████▌ | 17/20 [00:03<00:00, 5.50it/s] 90%|█████████ | 18/20 [00:03<00:00, 5.50it/s] 95%|█████████▌| 19/20 [00:03<00:00, 5.51it/s] 100%|██████████| 20/20 [00:04<00:00, 5.51it/s] 100%|██████████| 20/20 [00:04<00:00, 4.86it/s] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.46it/s] 10%|█ | 2/20 [00:00<00:06, 2.57it/s] 15%|█▌ | 3/20 [00:01<00:04, 3.40it/s] 20%|██ | 4/20 [00:01<00:03, 4.02it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.45it/s] 30%|███ | 6/20 [00:01<00:02, 4.76it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.98it/s] 40%|████ | 8/20 [00:01<00:02, 5.15it/s] 45%|████▌ | 9/20 [00:02<00:02, 5.27it/s] 50%|█████ | 10/20 [00:02<00:01, 5.35it/s] 55%|█████▌ | 11/20 [00:02<00:01, 5.40it/s] 60%|██████ | 12/20 [00:02<00:01, 5.46it/s] 65%|██████▌ | 13/20 [00:02<00:01, 5.47it/s] 70%|███████ | 14/20 [00:03<00:01, 5.51it/s] 75%|███████▌ | 15/20 [00:03<00:00, 5.52it/s] 80%|████████ | 16/20 [00:03<00:00, 5.53it/s] 85%|████████▌ | 17/20 [00:03<00:00, 5.52it/s] 90%|█████████ | 18/20 [00:03<00:00, 5.54it/s] 95%|█████████▌| 19/20 [00:03<00:00, 5.54it/s] 100%|██████████| 20/20 [00:04<00:00, 5.54it/s] 100%|██████████| 20/20 [00:04<00:00, 4.86it/s] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.49it/s] 10%|█ | 2/20 [00:00<00:06, 2.62it/s] 15%|█▌ | 3/20 [00:01<00:04, 3.44it/s] 20%|██ | 4/20 [00:01<00:03, 4.05it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.48it/s] 30%|███ | 6/20 [00:01<00:02, 4.80it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.99it/s] 40%|████ | 8/20 [00:01<00:02, 5.15it/s] 45%|████▌ | 9/20 [00:02<00:02, 5.24it/s] 50%|█████ | 10/20 [00:02<00:01, 5.33it/s] 55%|█████▌ | 11/20 [00:02<00:01, 5.38it/s] 60%|██████ | 12/20 [00:02<00:01, 5.42it/s] 65%|██████▌ | 13/20 [00:02<00:01, 5.45it/s] 70%|███████ | 14/20 [00:03<00:01, 5.48it/s] 75%|███████▌ | 15/20 [00:03<00:00, 5.50it/s] 80%|████████ | 16/20 [00:03<00:00, 5.53it/s] 85%|████████▌ | 17/20 [00:03<00:00, 5.53it/s] 90%|█████████ | 18/20 [00:03<00:00, 5.53it/s] 95%|█████████▌| 19/20 [00:03<00:00, 5.54it/s] 100%|██████████| 20/20 [00:04<00:00, 5.55it/s] 100%|██████████| 20/20 [00:04<00:00, 4.87it/s] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.50it/s] 10%|█ | 2/20 [00:00<00:06, 2.62it/s] 15%|█▌ | 3/20 [00:01<00:04, 3.44it/s] 20%|██ | 4/20 [00:01<00:03, 4.04it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.47it/s] 30%|███ | 6/20 [00:01<00:02, 4.79it/s] 35%|███▌ | 7/20 [00:01<00:02, 5.00it/s] 40%|████ | 8/20 [00:01<00:02, 5.18it/s] 45%|████▌ | 9/20 [00:02<00:02, 5.28it/s] 50%|█████ | 10/20 [00:02<00:01, 5.32it/s] 55%|█████▌ | 11/20 [00:02<00:01, 5.35it/s] 60%|██████ | 12/20 [00:02<00:01, 5.40it/s] 65%|██████▌ | 13/20 [00:02<00:01, 5.41it/s] 70%|███████ | 14/20 [00:03<00:01, 5.45it/s] 75%|███████▌ | 15/20 [00:03<00:00, 5.45it/s] 80%|████████ | 16/20 [00:03<00:00, 5.47it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.58it/s] 90%|█████████ | 18/20 [00:03<00:00, 4.27it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.41it/s] 100%|██████████| 20/20 [00:04<00:00, 3.98it/s] 100%|██████████| 20/20 [00:04<00:00, 4.46it/s] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.50it/s] 10%|█ | 2/20 [00:00<00:06, 2.62it/s] 15%|█▌ | 3/20 [00:01<00:04, 3.44it/s] 20%|██ | 4/20 [00:01<00:03, 4.04it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.44it/s] 30%|███ | 6/20 [00:01<00:02, 4.75it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.95it/s] 40%|████ | 8/20 [00:01<00:02, 5.12it/s] 45%|████▌ | 9/20 [00:02<00:02, 5.22it/s] 50%|█████ | 10/20 [00:02<00:01, 5.30it/s] 55%|█████▌ | 11/20 [00:02<00:01, 5.35it/s] 60%|██████ | 12/20 [00:02<00:01, 5.38it/s] 65%|██████▌ | 13/20 [00:02<00:01, 5.41it/s] 70%|███████ | 14/20 [00:03<00:01, 5.44it/s] 75%|███████▌ | 15/20 [00:03<00:00, 5.46it/s] 80%|████████ | 16/20 [00:03<00:00, 5.47it/s] 85%|████████▌ | 17/20 [00:03<00:00, 5.49it/s] 90%|█████████ | 18/20 [00:03<00:00, 5.51it/s] 95%|█████████▌| 19/20 [00:03<00:00, 5.49it/s] 100%|██████████| 20/20 [00:04<00:00, 5.47it/s] 100%|██████████| 20/20 [00:04<00:00, 4.84it/s] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:12, 1.48it/s] 10%|█ | 2/20 [00:00<00:06, 2.60it/s] 15%|█▌ | 3/20 [00:01<00:04, 3.41it/s] 20%|██ | 4/20 [00:01<00:03, 4.03it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.44it/s] 30%|███ | 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