jhorovitz / omini-dev
Cogified implementation of OminiControl
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0IDv28xn7ve3xrj60cn2hvrvfgyc8StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- fill
- prompt
- A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.
- num_outputs
- 1
- control_image
- book_masked.jpg?raw=true
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "fill", prompt: "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", num_outputs: 1, control_image: "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "fill", "prompt": "A yellow book with the word \'OMINI\' in large font on the cover. The text \'for FLUX\' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T15:16:07.709118Z", "created_at": "2025-02-17T15:12:06.175000Z", "data_removed": false, "error": null, "id": "v28xn7ve3xrj60cn2hvrvfgyc8", "input": { "seed": 42, "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 2.60it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.04it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.07it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.09it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.10it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.10it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.11it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.11it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.07it/s]", "metrics": { "predict_time": 4.110029013, "total_time": 241.534118 }, "output": [ "https://replicate.delivery/yhqm/Yxwf6wef4efcMiaY1feiG2vBv9SdrSXZ6rOibeF8GlX13SQQUA/out-0.webp" ], "started_at": "2025-02-17T15:16:03.599089Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-cgeffzbmfbs35k5s5cwnvtlohwvqgi7hzuhf2qeikjyqmzxlmh5q", "get": "https://api.replicate.com/v1/predictions/v28xn7ve3xrj60cn2hvrvfgyc8", "cancel": "https://api.replicate.com/v1/predictions/v28xn7ve3xrj60cn2hvrvfgyc8/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 2.60it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.04it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.07it/s] 50%|█████ | 4/8 [00:01<00:01, 3.09it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.10it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.10it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.11it/s] 100%|██████████| 8/8 [00:02<00:00, 3.11it/s] 100%|██████████| 8/8 [00:02<00:00, 3.07it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0IDv28xn7ve3xrj60cn2hvrvfgyc8StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- fill
- prompt
- A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.
- num_outputs
- 1
- control_image
- book_masked.jpg?raw=true
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "fill", prompt: "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", num_outputs: 1, control_image: "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "fill", "prompt": "A yellow book with the word \'OMINI\' in large font on the cover. The text \'for FLUX\' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T15:16:07.709118Z", "created_at": "2025-02-17T15:12:06.175000Z", "data_removed": false, "error": null, "id": "v28xn7ve3xrj60cn2hvrvfgyc8", "input": { "seed": 42, "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 2.60it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.04it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.07it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.09it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.10it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.10it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.11it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.11it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.07it/s]", "metrics": { "predict_time": 4.110029013, "total_time": 241.534118 }, "output": [ "https://replicate.delivery/yhqm/Yxwf6wef4efcMiaY1feiG2vBv9SdrSXZ6rOibeF8GlX13SQQUA/out-0.webp" ], "started_at": "2025-02-17T15:16:03.599089Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-cgeffzbmfbs35k5s5cwnvtlohwvqgi7hzuhf2qeikjyqmzxlmh5q", "get": "https://api.replicate.com/v1/predictions/v28xn7ve3xrj60cn2hvrvfgyc8", "cancel": "https://api.replicate.com/v1/predictions/v28xn7ve3xrj60cn2hvrvfgyc8/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 2.60it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.04it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.07it/s] 50%|█████ | 4/8 [00:01<00:01, 3.09it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.10it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.10it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.11it/s] 100%|██████████| 8/8 [00:02<00:00, 3.11it/s] 100%|██████████| 8/8 [00:02<00:00, 3.07it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0IDg9azsgrz1xrj20cn2n4shsxyn0StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- coloring
- prompt
- A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.
- num_outputs
- 1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "coloring", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "coloring", prompt: "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", num_outputs: 1, control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "coloring", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "coloring", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T19:01:11.386956Z", "created_at": "2025-02-17T19:01:08.495000Z", "data_removed": false, "error": null, "id": "g9azsgrz1xrj20cn2n4shsxyn0", "input": { "seed": 42, "task": "coloring", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.19it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.13it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.16it/s]", "metrics": { "predict_time": 2.8815087740000003, "total_time": 2.891956 }, "output": [ "https://replicate.delivery/yhqm/fqlAZM2BVyySKqUg4XzYe0O44TwOdXEfwVbL0WZ3eWqdXOBRB/out-0.webp" ], "started_at": "2025-02-17T19:01:08.505447Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-dmfkgw2oiy4cc6wnu36qbcysie62w6gyz4vateo6x5spbfguyufa", "get": "https://api.replicate.com/v1/predictions/g9azsgrz1xrj20cn2n4shsxyn0", "cancel": "https://api.replicate.com/v1/predictions/g9azsgrz1xrj20cn2n4shsxyn0/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s] 50%|█████ | 4/8 [00:01<00:01, 3.19it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.13it/s] 100%|██████████| 8/8 [00:02<00:00, 3.16it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0ID9c61tnj8msrj60cn2n4r935em0StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- canny
- prompt
- A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.
- num_outputs
- 1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "canny", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "canny", prompt: "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", num_outputs: 1, control_image: "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "canny", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "canny", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T19:01:23.168113Z", "created_at": "2025-02-17T19:01:19.142000Z", "data_removed": false, "error": null, "id": "9c61tnj8msrj60cn2n4r935em0", "input": { "seed": 42, "task": "canny", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4dM8Ovbefmz957U7hWA1KfTq78jgt4WTBFpBqnCVDnwf1T/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.34it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.24it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.19it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.17it/s]", "metrics": { "predict_time": 3.037037788, "total_time": 4.026113 }, "output": [ "https://replicate.delivery/yhqm/CdLRrAw9I6ZxHBHrsUbbAOIV654tZnH2NTRL2eYqIGsBzJIKA/out-0.webp" ], "started_at": "2025-02-17T19:01:20.131075Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-3qouic6msofnwyqaxzyvkapmfkixsc7sej6vh7tnvcophdmqszva", "get": "https://api.replicate.com/v1/predictions/9c61tnj8msrj60cn2n4r935em0", "cancel": "https://api.replicate.com/v1/predictions/9c61tnj8msrj60cn2n4r935em0/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.34it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.24it/s] 50%|█████ | 4/8 [00:01<00:01, 3.19it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.17it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0ID4vf3k09rr5rj40cn2n4rka179cStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- depth
- prompt
- A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.
- num_outputs
- 1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "depth", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "depth", prompt: "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", num_outputs: 1, control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "depth", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "depth", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T19:01:20.023275Z", "created_at": "2025-02-17T19:01:15.073000Z", "data_removed": false, "error": null, "id": "4vf3k09rr5rj40cn2n4rka179c", "input": { "seed": 42, "task": "depth", "prompt": "A red coffee cup sits on a table next to a blue candle and a container of coffee beans. more beans are strewn around.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.34it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.24it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.19it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.17it/s]", "metrics": { "predict_time": 4.941589066, "total_time": 4.950275 }, "output": [ "https://replicate.delivery/yhqm/0IH3B1hffNsI4Up5i0ElH2JGYpDQtLfJfAx8BFymj1SCYOBRB/out-0.webp" ], "started_at": "2025-02-17T19:01:15.081686Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-zqzds5uqhugyj2bijikybgk5yd3yfx7uoqiixgwtdi77ol3r32ua", "get": "https://api.replicate.com/v1/predictions/4vf3k09rr5rj40cn2n4rka179c", "cancel": "https://api.replicate.com/v1/predictions/4vf3k09rr5rj40cn2n4rka179c/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.34it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.24it/s] 50%|█████ | 4/8 [00:01<00:01, 3.19it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.17it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0IDr8hrbdx5pnrj60cn2n5ay0pje0StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- canny
- prompt
- In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
- num_outputs
- 1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "canny", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "canny", prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", num_outputs: 1, control_image: "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "canny", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "canny", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T19:02:53.073206Z", "created_at": "2025-02-17T19:02:48.501000Z", "data_removed": false, "error": null, "id": "r8hrbdx5pnrj60cn2n5ay0pje0", "input": { "seed": 42, "task": "canny", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4em4udrQkhH3DvCZfuYeCx3foagX6Kfp5BKPtFH9n5gLbZ/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.19it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.16it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.16it/s]", "metrics": { "predict_time": 3.115265258, "total_time": 4.572206 }, "output": [ "https://replicate.delivery/yhqm/HF2FKpNdu76dJhAngWKKSPueWZn6mrCFVz7nPBtJjrzuzJIKA/out-0.webp" ], "started_at": "2025-02-17T19:02:49.957941Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-5kz37itx4owq2h2ejbpkzcsrm2m2jybl3pis5mh4menvemersuta", "get": "https://api.replicate.com/v1/predictions/r8hrbdx5pnrj60cn2n5ay0pje0", "cancel": "https://api.replicate.com/v1/predictions/r8hrbdx5pnrj60cn2n5ay0pje0/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s] 50%|█████ | 4/8 [00:01<00:01, 3.19it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.16it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.16it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0ID1x4np2wnsdrj00cn2n5aqzvnw4StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- depth
- prompt
- In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
- num_outputs
- 1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "depth", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "depth", prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", num_outputs: 1, control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "depth", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "depth", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T19:02:49.861370Z", "created_at": "2025-02-17T19:02:44.427000Z", "data_removed": false, "error": null, "id": "1x4np2wnsdrj00cn2n5aqzvnw4", "input": { "seed": 42, "task": "depth", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.19it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.16it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.16it/s]", "metrics": { "predict_time": 4.901596754, "total_time": 5.43437 }, "output": [ "https://replicate.delivery/yhqm/ppSu5OQMfTQjQacXg0DiY3jReoffhJbDpSd2Lb0YmizkdOBRB/out-0.webp" ], "started_at": "2025-02-17T19:02:44.959773Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-glqszayyqsb2dg5eyin63qpiu6tlwnvz3gwgtjvqxohkbgpjc4za", "get": "https://api.replicate.com/v1/predictions/1x4np2wnsdrj00cn2n5aqzvnw4", "cancel": "https://api.replicate.com/v1/predictions/1x4np2wnsdrj00cn2n5aqzvnw4/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s] 50%|█████ | 4/8 [00:01<00:01, 3.19it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.16it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.16it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0IDwe46ex4ahxrj00cn2n5bxnsn40StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- coloring
- prompt
- In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
- num_outputs
- 1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "coloring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "coloring", prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", num_outputs: 1, control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "coloring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "coloring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T19:02:44.863551Z", "created_at": "2025-02-17T19:02:41.551000Z", "data_removed": false, "error": null, "id": "we46ex4ahxrj00cn2n5bxnsn40", "input": { "seed": 42, "task": "coloring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.19it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.16it/s]", "metrics": { "predict_time": 2.891901895, "total_time": 3.312551 }, "output": [ "https://replicate.delivery/yhqm/sfd161ArsO0nJKfTqxISNS62OjNV9VyVa6fXbsBpdJeQdOBRB/out-0.webp" ], "started_at": "2025-02-17T19:02:41.971649Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-dvk6f3ixr5sbq6hmbwg4tn6gat3zwxy6rquln5gymktsusnq7j4a", "get": "https://api.replicate.com/v1/predictions/we46ex4ahxrj00cn2n5bxnsn40", "cancel": "https://api.replicate.com/v1/predictions/we46ex4ahxrj00cn2n5bxnsn40/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.33it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.23it/s] 50%|█████ | 4/8 [00:01<00:01, 3.19it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.16it/s]
Prediction
jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0IDx52rx4m0b9rj00cn2n5acw77e0StatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- seed
- 42
- task
- deblurring
- prompt
- In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.
- num_outputs
- 1
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 8
{ "seed": 42, "task": "deblurring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", { input: { seed: 42, task: "deblurring", prompt: "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", num_outputs: 1, control_image: "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 8 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", input={ "seed": 42, "task": "deblurring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0", "input": { "seed": 42, "task": "deblurring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-17T19:02:41.828177Z", "created_at": "2025-02-17T19:02:38.938000Z", "data_removed": false, "error": null, "id": "x52rx4m0b9rj00cn2n5acw77e0", "input": { "seed": 42, "task": "deblurring", "prompt": "In a bright room. A cup of a coffee with some beans on the side. They are placed on a dark wooden table.", "num_outputs": 1, "control_image": "https://replicate.delivery/pbxt/MW4aBFDCHSUGpGUt7jOHtlJUbHuD01AONTRoR7odtLEaCItL/coffee.png", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 8 }, "logs": "Using seed: 42\n 0%| | 0/8 [00:00<?, ?it/s]\n 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s]\n 25%|██▌ | 2/8 [00:00<00:01, 3.34it/s]\n 38%|███▊ | 3/8 [00:00<00:01, 3.24it/s]\n 50%|█████ | 4/8 [00:01<00:01, 3.19it/s]\n 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s]\n 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s]\n 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.14it/s]\n100%|██████████| 8/8 [00:02<00:00, 3.17it/s]", "metrics": { "predict_time": 2.878912236, "total_time": 2.890177 }, "output": [ "https://replicate.delivery/yhqm/HQUnacnfHmTDWC5xIxgxQn5PPDAfkmrb8KGKqsGHhf4iOngoA/out-0.webp" ], "started_at": "2025-02-17T19:02:38.949264Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-vrcyfbk43hvte3cuwueuly42obtq3dhn26zecuvcynvyxbwcc5gq", "get": "https://api.replicate.com/v1/predictions/x52rx4m0b9rj00cn2n5acw77e0", "cancel": "https://api.replicate.com/v1/predictions/x52rx4m0b9rj00cn2n5acw77e0/cancel" }, "version": "807c3a225037898bf5cb98c6c267c627d5ec164acd79c490972e38ba74153ec0" }
Generated inUsing seed: 42 0%| | 0/8 [00:00<?, ?it/s] 12%|█▎ | 1/8 [00:00<00:02, 3.12it/s] 25%|██▌ | 2/8 [00:00<00:01, 3.34it/s] 38%|███▊ | 3/8 [00:00<00:01, 3.24it/s] 50%|█████ | 4/8 [00:01<00:01, 3.19it/s] 62%|██████▎ | 5/8 [00:01<00:00, 3.17it/s] 75%|███████▌ | 6/8 [00:01<00:00, 3.15it/s] 88%|████████▊ | 7/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.14it/s] 100%|██████████| 8/8 [00:02<00:00, 3.17it/s]
Prediction
jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1IDtrmh2dbb65rj40cn30cvcfnwtmStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- task
- fill
- prompt
- A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.
- num_outputs
- 1
- control_image
- book_masked.jpg?raw=true
- output_format
- webp
- guidance_scale
- 3.5
- output_quality
- 80
- num_inference_steps
- 28
{ "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }
Install Replicate’s Node.js client library:npm install replicate
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 jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1", { input: { task: "fill", prompt: "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", num_outputs: 1, control_image: "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", output_format: "webp", guidance_scale: 3.5, output_quality: 80, num_inference_steps: 28 } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);
To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicate
Import the client:import replicate
Run jhorovitz/omini-dev using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1", input={ "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } ) print(output)
To learn more, take a look at the guide on getting started with Python.
Run jhorovitz/omini-dev 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": "jhorovitz/omini-dev:85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1", "input": { "task": "fill", "prompt": "A yellow book with the word \'OMINI\' in large font on the cover. The text \'for FLUX\' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 } }' \ https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2025-02-18T08:09:04.853106Z", "created_at": "2025-02-18T08:07:53.905000Z", "data_removed": false, "error": null, "id": "trmh2dbb65rj40cn30cvcfnwtm", "input": { "task": "fill", "prompt": "A yellow book with the word 'OMINI' in large font on the cover. The text 'for FLUX' appears at the bottom.", "num_outputs": 1, "control_image": "https://github.com/jHorovitz/OminiControl/blob/main/assets/book_masked.jpg?raw=true", "output_format": "webp", "guidance_scale": 3.5, "output_quality": 80, "num_inference_steps": 28 }, "logs": "Using seed: 10479\n 0%| | 0/28 [00:00<?, ?it/s]\n 4%|▎ | 1/28 [00:00<00:10, 2.59it/s]\n 7%|▋ | 2/28 [00:00<00:08, 3.05it/s]\n 11%|█ | 3/28 [00:00<00:08, 3.09it/s]\n 14%|█▍ | 4/28 [00:01<00:07, 3.10it/s]\n 18%|█▊ | 5/28 [00:01<00:07, 3.11it/s]\n 21%|██▏ | 6/28 [00:01<00:07, 3.12it/s]\n 25%|██▌ | 7/28 [00:02<00:06, 3.12it/s]\n 29%|██▊ | 8/28 [00:02<00:06, 3.13it/s]\n 32%|███▏ | 9/28 [00:02<00:06, 3.13it/s]\n 36%|███▌ | 10/28 [00:03<00:05, 3.13it/s]\n 39%|███▉ | 11/28 [00:03<00:05, 3.13it/s]\n 43%|████▎ | 12/28 [00:03<00:05, 3.13it/s]\n 46%|████▋ | 13/28 [00:04<00:04, 3.13it/s]\n 50%|█████ | 14/28 [00:04<00:04, 3.13it/s]\n 54%|█████▎ | 15/28 [00:04<00:04, 3.13it/s]\n 57%|█████▋ | 16/28 [00:05<00:03, 3.13it/s]\n 61%|██████ | 17/28 [00:05<00:03, 3.13it/s]\n 64%|██████▍ | 18/28 [00:05<00:03, 3.13it/s]\n 68%|██████▊ | 19/28 [00:06<00:02, 3.13it/s]\n 71%|███████▏ | 20/28 [00:06<00:02, 3.13it/s]\n 75%|███████▌ | 21/28 [00:06<00:02, 3.13it/s]\n 79%|███████▊ | 22/28 [00:07<00:01, 3.13it/s]\n 82%|████████▏ | 23/28 [00:07<00:01, 3.13it/s]\n 86%|████████▌ | 24/28 [00:07<00:01, 3.13it/s]\n 89%|████████▉ | 25/28 [00:08<00:00, 3.13it/s]\n 93%|█████████▎| 26/28 [00:08<00:00, 3.13it/s]\n 96%|█████████▋| 27/28 [00:08<00:00, 3.13it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.13it/s]\n100%|██████████| 28/28 [00:08<00:00, 3.12it/s]", "metrics": { "predict_time": 10.53011346, "total_time": 70.948106 }, "output": [ "https://replicate.delivery/yhqm/smr6RYHT2kpQCxmh094zuMeAVr0Acnqrpdif1JA6mLvgIfgoA/out-0.webp" ], "started_at": "2025-02-18T08:08:54.322992Z", "status": "succeeded", "urls": { "stream": "https://stream.replicate.com/v1/files/yswh-ff4ijjglrur2k542vwoyirv7gb3tosqvaop4tr4zhsotwimgrnea", "get": "https://api.replicate.com/v1/predictions/trmh2dbb65rj40cn30cvcfnwtm", "cancel": "https://api.replicate.com/v1/predictions/trmh2dbb65rj40cn30cvcfnwtm/cancel" }, "version": "85dcc269f1e1c5f1258e955b3ec44a0ee663004d19a2122c963ad7bc238514d1" }
Generated inUsing seed: 10479 0%| | 0/28 [00:00<?, ?it/s] 4%|▎ | 1/28 [00:00<00:10, 2.59it/s] 7%|▋ | 2/28 [00:00<00:08, 3.05it/s] 11%|█ | 3/28 [00:00<00:08, 3.09it/s] 14%|█▍ | 4/28 [00:01<00:07, 3.10it/s] 18%|█▊ | 5/28 [00:01<00:07, 3.11it/s] 21%|██▏ | 6/28 [00:01<00:07, 3.12it/s] 25%|██▌ | 7/28 [00:02<00:06, 3.12it/s] 29%|██▊ | 8/28 [00:02<00:06, 3.13it/s] 32%|███▏ | 9/28 [00:02<00:06, 3.13it/s] 36%|███▌ | 10/28 [00:03<00:05, 3.13it/s] 39%|███▉ | 11/28 [00:03<00:05, 3.13it/s] 43%|████▎ | 12/28 [00:03<00:05, 3.13it/s] 46%|████▋ | 13/28 [00:04<00:04, 3.13it/s] 50%|█████ | 14/28 [00:04<00:04, 3.13it/s] 54%|█████▎ | 15/28 [00:04<00:04, 3.13it/s] 57%|█████▋ | 16/28 [00:05<00:03, 3.13it/s] 61%|██████ | 17/28 [00:05<00:03, 3.13it/s] 64%|██████▍ | 18/28 [00:05<00:03, 3.13it/s] 68%|██████▊ | 19/28 [00:06<00:02, 3.13it/s] 71%|███████▏ | 20/28 [00:06<00:02, 3.13it/s] 75%|███████▌ | 21/28 [00:06<00:02, 3.13it/s] 79%|███████▊ | 22/28 [00:07<00:01, 3.13it/s] 82%|████████▏ | 23/28 [00:07<00:01, 3.13it/s] 86%|████████▌ | 24/28 [00:07<00:01, 3.13it/s] 89%|████████▉ | 25/28 [00:08<00:00, 3.13it/s] 93%|█████████▎| 26/28 [00:08<00:00, 3.13it/s] 96%|█████████▋| 27/28 [00:08<00:00, 3.13it/s] 100%|██████████| 28/28 [00:08<00:00, 3.13it/s] 100%|██████████| 28/28 [00:08<00:00, 3.12it/s]
Want to make some of these yourself?
Run this model