yuni-eng
/
controlnet-sdxl
Create variations of an uploaded image. Please see README for more details
Prediction
yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5efIDkbxt6n3bk44poimxvvdoaoem7eStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 0
- image
- width
- 768
- height
- 768
- prompt
- an oil painting of golden gate
- num_outputs
- 1
- guidance_scale
- 2
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy
- num_inference_steps
- 100
{ "seed": 0, "image": "https://replicate.delivery/pbxt/JsFYXkgtgbgCtuVOk8NBAMjo25QG205oM2OSuToyrLAqzqLp/goldengate.png", "width": 768, "height": 768, "prompt": "an oil painting of golden gate", "num_outputs": 1, "guidance_scale": 2, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", { input: { seed: 0, image: "https://replicate.delivery/pbxt/JsFYXkgtgbgCtuVOk8NBAMjo25QG205oM2OSuToyrLAqzqLp/goldengate.png", width: 768, height: 768, prompt: "an oil painting of golden gate", num_outputs: 1, guidance_scale: 2, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", num_inference_steps: 100 } } ); // 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 replicateImport the client:import replicateRun yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", input={ "seed": 0, "image": "https://replicate.delivery/pbxt/JsFYXkgtgbgCtuVOk8NBAMjo25QG205oM2OSuToyrLAqzqLp/goldengate.png", "width": 768, "height": 768, "prompt": "an oil painting of golden gate", "num_outputs": 1, "guidance_scale": 2, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/controlnet-sdxl 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": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", "input": { "seed": 0, "image": "https://replicate.delivery/pbxt/JsFYXkgtgbgCtuVOk8NBAMjo25QG205oM2OSuToyrLAqzqLp/goldengate.png", "width": 768, "height": 768, "prompt": "an oil painting of golden gate", "num_outputs": 1, "guidance_scale": 2, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-14T06:15:13.704541Z", "created_at": "2023-11-14T06:14:41.611308Z", "data_removed": false, "error": null, "id": "kbxt6n3bk44poimxvvdoaoem7e", "input": { "seed": 0, "image": "https://replicate.delivery/pbxt/JsFYXkgtgbgCtuVOk8NBAMjo25QG205oM2OSuToyrLAqzqLp/goldengate.png", "width": 768, "height": 768, "prompt": "an oil painting of golden gate", "num_outputs": 1, "guidance_scale": 2, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }, "logs": "Using seed: 57720\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:31, 3.13it/s]\n 2%|▏ | 2/100 [00:00<00:30, 3.26it/s]\n 3%|▎ | 3/100 [00:00<00:29, 3.30it/s]\n 4%|▍ | 4/100 [00:01<00:28, 3.32it/s]\n 5%|▌ | 5/100 [00:01<00:28, 3.33it/s]\n 6%|▌ | 6/100 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[00:28<00:01, 3.33it/s]\n 95%|█████████▌| 95/100 [00:28<00:01, 3.32it/s]\n 96%|█████████▌| 96/100 [00:28<00:01, 3.32it/s]\n 97%|█████████▋| 97/100 [00:29<00:00, 3.32it/s]\n 98%|█████████▊| 98/100 [00:29<00:00, 3.32it/s]\n 99%|█████████▉| 99/100 [00:29<00:00, 3.32it/s]\n100%|██████████| 100/100 [00:29<00:00, 3.32it/s]\n100%|██████████| 100/100 [00:29<00:00, 3.34it/s]\nPrediction complete", "metrics": { "predict_time": 32.14772, "total_time": 32.093233 }, "output": [ "https://replicate.delivery/pbxt/mkBhYkREKP7bHhY6VYxd410slzCkzR9jfoWPFCvrsZD4EG8IA/out-0.png" ], "started_at": "2023-11-14T06:14:41.556821Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/kbxt6n3bk44poimxvvdoaoem7e", "cancel": "https://api.replicate.com/v1/predictions/kbxt6n3bk44poimxvvdoaoem7e/cancel" }, "version": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef" }Generated inUsing seed: 57720 0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:31, 3.13it/s] 2%|▏ | 2/100 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95%|█████████▌| 95/100 [00:28<00:01, 3.32it/s] 96%|█████████▌| 96/100 [00:28<00:01, 3.32it/s] 97%|█████████▋| 97/100 [00:29<00:00, 3.32it/s] 98%|█████████▊| 98/100 [00:29<00:00, 3.32it/s] 99%|█████████▉| 99/100 [00:29<00:00, 3.32it/s] 100%|██████████| 100/100 [00:29<00:00, 3.32it/s] 100%|██████████| 100/100 [00:29<00:00, 3.34it/s] Prediction completePrediction
yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5efIDnswepbtbudf2znjbi6gthixv7uStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedby @yuni-engInput
- seed
- 9465
- image
- width
- 768
- height
- 768
- prompt
- a realistic photo
- num_outputs
- 1
- guidance_scale
- 7.5
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy
- num_inference_steps
- 100
{ "seed": 9465, "image": "https://replicate.delivery/pbxt/JsFpilrSx3ulOeVYX91Nw3rfofoRnNL7QRF9t2v3US9SOBMw/kungfupanda.png", "width": 768, "height": 768, "prompt": "a realistic photo ", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", { input: { seed: 9465, image: "https://replicate.delivery/pbxt/JsFpilrSx3ulOeVYX91Nw3rfofoRnNL7QRF9t2v3US9SOBMw/kungfupanda.png", width: 768, height: 768, prompt: "a realistic photo ", num_outputs: 1, guidance_scale: 7.5, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", num_inference_steps: 100 } } ); // 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 replicateImport the client:import replicateRun yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", input={ "seed": 9465, "image": "https://replicate.delivery/pbxt/JsFpilrSx3ulOeVYX91Nw3rfofoRnNL7QRF9t2v3US9SOBMw/kungfupanda.png", "width": 768, "height": 768, "prompt": "a realistic photo ", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/controlnet-sdxl 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": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", "input": { "seed": 9465, "image": "https://replicate.delivery/pbxt/JsFpilrSx3ulOeVYX91Nw3rfofoRnNL7QRF9t2v3US9SOBMw/kungfupanda.png", "width": 768, "height": 768, "prompt": "a realistic photo ", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-14T06:33:22.214749Z", "created_at": "2023-11-14T06:32:49.835943Z", "data_removed": false, "error": null, "id": "nswepbtbudf2znjbi6gthixv7u", "input": { "seed": 9465, "image": "https://replicate.delivery/pbxt/JsFpilrSx3ulOeVYX91Nw3rfofoRnNL7QRF9t2v3US9SOBMw/kungfupanda.png", "width": 768, "height": 768, "prompt": "a realistic photo ", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }, "logs": "Using seed: 9465\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:29, 3.36it/s]\n 2%|▏ | 2/100 [00:00<00:29, 3.36it/s]\n 3%|▎ | 3/100 [00:00<00:28, 3.36it/s]\n 4%|▍ | 4/100 [00:01<00:28, 3.36it/s]\n 5%|▌ | 5/100 [00:01<00:28, 3.36it/s]\n 6%|▌ | 6/100 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[00:28<00:01, 3.32it/s]\n 95%|█████████▌| 95/100 [00:28<00:01, 3.32it/s]\n 96%|█████████▌| 96/100 [00:28<00:01, 3.32it/s]\n 97%|█████████▋| 97/100 [00:29<00:00, 3.32it/s]\n 98%|█████████▊| 98/100 [00:29<00:00, 3.32it/s]\n 99%|█████████▉| 99/100 [00:29<00:00, 3.32it/s]\n100%|██████████| 100/100 [00:29<00:00, 3.32it/s]\n100%|██████████| 100/100 [00:29<00:00, 3.33it/s]\nPrediction complete", "metrics": { "predict_time": 32.393994, "total_time": 32.378806 }, "output": [ "https://replicate.delivery/pbxt/I2qbBAinaQ6OKRJ8M3Mdd73S4UxEPKWHFJocunwLTHTsGDeIA/out-0.png" ], "started_at": "2023-11-14T06:32:49.820755Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/nswepbtbudf2znjbi6gthixv7u", "cancel": "https://api.replicate.com/v1/predictions/nswepbtbudf2znjbi6gthixv7u/cancel" }, "version": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef" }Generated inUsing seed: 9465 0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:29, 3.36it/s] 2%|▏ | 2/100 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95%|█████████▌| 95/100 [00:28<00:01, 3.32it/s] 96%|█████████▌| 96/100 [00:28<00:01, 3.32it/s] 97%|█████████▋| 97/100 [00:29<00:00, 3.32it/s] 98%|█████████▊| 98/100 [00:29<00:00, 3.32it/s] 99%|█████████▉| 99/100 [00:29<00:00, 3.32it/s] 100%|██████████| 100/100 [00:29<00:00, 3.32it/s] 100%|██████████| 100/100 [00:29<00:00, 3.33it/s] Prediction completePrediction
yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5efIDl3jmdy3bdo45aoi36py7y5jz5eStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 0
- image
- width
- 768
- height
- 768
- prompt
- a photo of american flag
- num_outputs
- 1
- guidance_scale
- 7.5
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy
- num_inference_steps
- 100
{ "seed": 0, "image": "https://replicate.delivery/pbxt/JsG8PJbFVkhhzuuPqp3evSku9o8SfCQ1RQ8uOQmCoQEDjLFM/Screenshot%202023-11-13%20at%2010.48.32%20PM.png", "width": 768, "height": 768, "prompt": "a photo of american flag", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", { input: { seed: 0, image: "https://replicate.delivery/pbxt/JsG8PJbFVkhhzuuPqp3evSku9o8SfCQ1RQ8uOQmCoQEDjLFM/Screenshot%202023-11-13%20at%2010.48.32%20PM.png", width: 768, height: 768, prompt: "a photo of american flag", num_outputs: 1, guidance_scale: 7.5, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", num_inference_steps: 100 } } ); // 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 replicateImport the client:import replicateRun yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", input={ "seed": 0, "image": "https://replicate.delivery/pbxt/JsG8PJbFVkhhzuuPqp3evSku9o8SfCQ1RQ8uOQmCoQEDjLFM/Screenshot%202023-11-13%20at%2010.48.32%20PM.png", "width": 768, "height": 768, "prompt": "a photo of american flag", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/controlnet-sdxl 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": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", "input": { "seed": 0, "image": "https://replicate.delivery/pbxt/JsG8PJbFVkhhzuuPqp3evSku9o8SfCQ1RQ8uOQmCoQEDjLFM/Screenshot%202023-11-13%20at%2010.48.32%20PM.png", "width": 768, "height": 768, "prompt": "a photo of american flag", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-14T06:53:45.111708Z", "created_at": "2023-11-14T06:53:35.051822Z", "data_removed": false, "error": null, "id": "l3jmdy3bdo45aoi36py7y5jz5e", "input": { "seed": 0, "image": "https://replicate.delivery/pbxt/JsG8PJbFVkhhzuuPqp3evSku9o8SfCQ1RQ8uOQmCoQEDjLFM/Screenshot%202023-11-13%20at%2010.48.32%20PM.png", "width": 768, "height": 768, "prompt": "a photo of american flag", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }, "logs": "Using seed: 46492\n 0%| | 0/100 [00:00<?, ?it/s]\n 2%|▏ | 2/100 [00:00<00:07, 12.28it/s]\n 4%|▍ | 4/100 [00:00<00:07, 12.33it/s]\n 6%|▌ | 6/100 [00:00<00:07, 12.32it/s]\n 8%|▊ | 8/100 [00:00<00:07, 12.21it/s]\n 10%|█ | 10/100 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11.95it/s]\n 56%|█████▌ | 56/100 [00:04<00:03, 11.94it/s]\n 58%|█████▊ | 58/100 [00:04<00:03, 11.91it/s]\n 60%|██████ | 60/100 [00:05<00:03, 11.86it/s]\n 62%|██████▏ | 62/100 [00:05<00:03, 11.81it/s]\n 64%|██████▍ | 64/100 [00:05<00:03, 11.91it/s]\n 66%|██████▌ | 66/100 [00:05<00:02, 11.90it/s]\n 68%|██████▊ | 68/100 [00:05<00:02, 11.90it/s]\n 70%|███████ | 70/100 [00:05<00:02, 11.86it/s]\n 72%|███████▏ | 72/100 [00:06<00:02, 11.85it/s]\n 74%|███████▍ | 74/100 [00:06<00:02, 11.81it/s]\n 76%|███████▌ | 76/100 [00:06<00:02, 11.97it/s]\n 78%|███████▊ | 78/100 [00:06<00:01, 11.89it/s]\n 80%|████████ | 80/100 [00:06<00:01, 11.85it/s]\n 82%|████████▏ | 82/100 [00:06<00:01, 11.83it/s]\n 84%|████████▍ | 84/100 [00:07<00:01, 11.79it/s]\n 86%|████████▌ | 86/100 [00:07<00:01, 11.80it/s]\n 88%|████████▊ | 88/100 [00:07<00:01, 11.90it/s]\n 90%|█████████ | 90/100 [00:07<00:00, 11.89it/s]\n 92%|█████████▏| 92/100 [00:07<00:00, 11.87it/s]\n 94%|█████████▍| 94/100 [00:07<00:00, 11.85it/s]\n 96%|█████████▌| 96/100 [00:08<00:00, 11.80it/s]\n 98%|█████████▊| 98/100 [00:08<00:00, 11.83it/s]\n100%|██████████| 100/100 [00:08<00:00, 11.79it/s]\n100%|██████████| 100/100 [00:08<00:00, 11.92it/s]\nPrediction complete", "metrics": { "predict_time": 10.070491, "total_time": 10.059886 }, "output": [ "https://replicate.delivery/pbxt/GzRCbJ7qbyICDNiDFKviUr49vzIknLCBqWVjIDF2nGFeWG8IA/out-0.png" ], "started_at": "2023-11-14T06:53:35.041217Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/l3jmdy3bdo45aoi36py7y5jz5e", "cancel": "https://api.replicate.com/v1/predictions/l3jmdy3bdo45aoi36py7y5jz5e/cancel" }, "version": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef" }Generated inUsing seed: 46492 0%| | 0/100 [00:00<?, ?it/s] 2%|▏ | 2/100 [00:00<00:07, 12.28it/s] 4%|▍ | 4/100 [00:00<00:07, 12.33it/s] 6%|▌ | 6/100 [00:00<00:07, 12.32it/s] 8%|▊ | 8/100 [00:00<00:07, 12.21it/s] 10%|█ | 10/100 [00:00<00:07, 12.12it/s] 12%|█▏ | 12/100 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[00:08<00:00, 11.79it/s] 100%|██████████| 100/100 [00:08<00:00, 11.92it/s] Prediction completePrediction
yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5efIDd5fqg33bozbzp4cq7co3hlac7eStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- seed
- 9465
- image
- width
- 768
- height
- 768
- prompt
- an illustration of a beautiful mountain, sun rising with lush coconut trees
- num_outputs
- 1
- guidance_scale
- 7.5
- negative_prompt
- poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy
- num_inference_steps
- 100
{ "seed": 9465, "image": "https://replicate.delivery/pbxt/Jsc4fn6UGQOoJNO0A4c6DBJzyP1bKMwRSaBDzDhi7Un4p1cC/Screenshot%202023-11-14%20at%2010.46.05%20PM.png", "width": 768, "height": 768, "prompt": "an illustration of a beautiful mountain, sun rising with lush coconut trees", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", { input: { seed: 9465, image: "https://replicate.delivery/pbxt/Jsc4fn6UGQOoJNO0A4c6DBJzyP1bKMwRSaBDzDhi7Un4p1cC/Screenshot%202023-11-14%20at%2010.46.05%20PM.png", width: 768, height: 768, prompt: "an illustration of a beautiful mountain, sun rising with lush coconut trees", num_outputs: 1, guidance_scale: 7.5, negative_prompt: "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", num_inference_steps: 100 } } ); // 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 replicateImport the client:import replicateRun yuni-eng/controlnet-sdxl using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "yuni-eng/controlnet-sdxl:0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", input={ "seed": 9465, "image": "https://replicate.delivery/pbxt/Jsc4fn6UGQOoJNO0A4c6DBJzyP1bKMwRSaBDzDhi7Un4p1cC/Screenshot%202023-11-14%20at%2010.46.05%20PM.png", "width": 768, "height": 768, "prompt": "an illustration of a beautiful mountain, sun rising with lush coconut trees", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run yuni-eng/controlnet-sdxl 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": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef", "input": { "seed": 9465, "image": "https://replicate.delivery/pbxt/Jsc4fn6UGQOoJNO0A4c6DBJzyP1bKMwRSaBDzDhi7Un4p1cC/Screenshot%202023-11-14%20at%2010.46.05%20PM.png", "width": 768, "height": 768, "prompt": "an illustration of a beautiful mountain, sun rising with lush coconut trees", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-11-15T06:48:56.514245Z", "created_at": "2023-11-15T06:48:07.595434Z", "data_removed": false, "error": null, "id": "d5fqg33bozbzp4cq7co3hlac7e", "input": { "seed": 9465, "image": "https://replicate.delivery/pbxt/Jsc4fn6UGQOoJNO0A4c6DBJzyP1bKMwRSaBDzDhi7Un4p1cC/Screenshot%202023-11-14%20at%2010.46.05%20PM.png", "width": 768, "height": 768, "prompt": "an illustration of a beautiful mountain, sun rising with lush coconut trees", "num_outputs": 1, "guidance_scale": 7.5, "negative_prompt": "poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, disfigured, deformed, body out of frame, bad anatomy, signature, cut off, low contrast, underexposed, overexposed, bad art, beginner, amateur, distorted face, blurry, draft, grainy", "num_inference_steps": 100 }, "logs": "Using seed: 9465\n 0%| | 0/100 [00:00<?, ?it/s]\n 1%| | 1/100 [00:00<00:45, 2.19it/s]\n 2%|▏ | 2/100 [00:00<00:45, 2.18it/s]\n 3%|▎ | 3/100 [00:01<00:44, 2.17it/s]\n 4%|▍ | 4/100 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51%|█████ | 51/100 [00:23<00:22, 2.15it/s]\n 52%|█████▏ | 52/100 [00:24<00:22, 2.15it/s]\n 53%|█████▎ | 53/100 [00:24<00:21, 2.15it/s]\n 54%|█████▍ | 54/100 [00:25<00:21, 2.15it/s]\n 55%|█████▌ | 55/100 [00:25<00:20, 2.15it/s]\n 56%|█████▌ | 56/100 [00:25<00:20, 2.15it/s]\n 57%|█████▋ | 57/100 [00:26<00:20, 2.15it/s]\n 58%|█████▊ | 58/100 [00:26<00:19, 2.15it/s]\n 59%|█████▉ | 59/100 [00:27<00:19, 2.15it/s]\n 60%|██████ | 60/100 [00:27<00:18, 2.15it/s]\n 61%|██████ | 61/100 [00:28<00:18, 2.15it/s]\n 62%|██████▏ | 62/100 [00:28<00:17, 2.15it/s]\n 63%|██████▎ | 63/100 [00:29<00:17, 2.15it/s]\n 64%|██████▍ | 64/100 [00:29<00:16, 2.15it/s]\n 65%|██████▌ | 65/100 [00:30<00:16, 2.15it/s]\n 66%|██████▌ | 66/100 [00:30<00:15, 2.15it/s]\n 67%|██████▋ | 67/100 [00:31<00:15, 2.15it/s]\n 68%|██████▊ | 68/100 [00:31<00:14, 2.15it/s]\n 69%|██████▉ | 69/100 [00:32<00:14, 2.15it/s]\n 70%|███████ | 70/100 [00:32<00:13, 2.15it/s]\n 71%|███████ | 71/100 [00:32<00:13, 2.15it/s]\n 72%|███████▏ | 72/100 [00:33<00:13, 2.15it/s]\n 73%|███████▎ | 73/100 [00:33<00:12, 2.15it/s]\n 74%|███████▍ | 74/100 [00:34<00:12, 2.15it/s]\n 75%|███████▌ | 75/100 [00:34<00:11, 2.15it/s]\n 76%|███████▌ | 76/100 [00:35<00:11, 2.15it/s]\n 77%|███████▋ | 77/100 [00:35<00:10, 2.15it/s]\n 78%|███████▊ | 78/100 [00:36<00:10, 2.15it/s]\n 79%|███████▉ | 79/100 [00:36<00:09, 2.15it/s]\n 80%|████████ | 80/100 [00:37<00:09, 2.15it/s]\n 81%|████████ | 81/100 [00:37<00:08, 2.14it/s]\n 82%|████████▏ | 82/100 [00:38<00:08, 2.13it/s]\n 83%|████████▎ | 83/100 [00:38<00:07, 2.13it/s]\n 84%|████████▍ | 84/100 [00:39<00:07, 2.14it/s]\n 85%|████████▌ | 85/100 [00:39<00:07, 2.14it/s]\n 86%|████████▌ | 86/100 [00:39<00:06, 2.14it/s]\n 87%|████████▋ | 87/100 [00:40<00:06, 2.15it/s]\n 88%|████████▊ | 88/100 [00:40<00:05, 2.15it/s]\n 89%|████████▉ | 89/100 [00:41<00:05, 2.15it/s]\n 90%|█████████ | 90/100 [00:41<00:04, 2.15it/s]\n 91%|█████████ | 91/100 [00:42<00:04, 2.15it/s]\n 92%|█████████▏| 92/100 [00:42<00:03, 2.15it/s]\n 93%|█████████▎| 93/100 [00:43<00:03, 2.15it/s]\n 94%|█████████▍| 94/100 [00:43<00:02, 2.15it/s]\n 95%|█████████▌| 95/100 [00:44<00:02, 2.15it/s]\n 96%|█████████▌| 96/100 [00:44<00:01, 2.15it/s]\n 97%|█████████▋| 97/100 [00:45<00:01, 2.15it/s]\n 98%|█████████▊| 98/100 [00:45<00:00, 2.15it/s]\n 99%|█████████▉| 99/100 [00:45<00:00, 2.15it/s]\n100%|██████████| 100/100 [00:46<00:00, 2.15it/s]\n100%|██████████| 100/100 [00:46<00:00, 2.15it/s]\nPrediction complete", "metrics": { "predict_time": 48.882095, "total_time": 48.918811 }, "output": [ "https://replicate.delivery/pbxt/MAkulHCKBYawNNi5LTV6oinzopSjvbYdbY60SJ6BRW21bIeIA/out-0.png" ], "started_at": "2023-11-15T06:48:07.632150Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/d5fqg33bozbzp4cq7co3hlac7e", "cancel": "https://api.replicate.com/v1/predictions/d5fqg33bozbzp4cq7co3hlac7e/cancel" }, "version": "0bdd2d10541b2210ebd284aaec263a20c855e59c7e1a2d905063ed717501b5ef" }Generated inUsing seed: 9465 0%| | 0/100 [00:00<?, ?it/s] 1%| | 1/100 [00:00<00:45, 2.19it/s] 2%|▏ | 2/100 [00:00<00:45, 2.18it/s] 3%|▎ | 3/100 [00:01<00:44, 2.17it/s] 4%|▍ | 4/100 [00:01<00:44, 2.17it/s] 5%|▌ | 5/100 [00:02<00:43, 2.17it/s] 6%|▌ | 6/100 [00:02<00:43, 2.17it/s] 7%|▋ | 7/100 [00:03<00:42, 2.17it/s] 8%|▊ | 8/100 [00:03<00:42, 2.17it/s] 9%|▉ | 9/100 [00:04<00:41, 2.17it/s] 10%|█ | 10/100 [00:04<00:41, 2.17it/s] 11%|█ | 11/100 [00:05<00:41, 2.17it/s] 12%|█▏ | 12/100 [00:05<00:40, 2.17it/s] 13%|█▎ | 13/100 [00:05<00:40, 2.17it/s] 14%|█▍ | 14/100 [00:06<00:39, 2.17it/s] 15%|█▌ | 15/100 [00:06<00:39, 2.17it/s] 16%|█▌ | 16/100 [00:07<00:38, 2.17it/s] 17%|█▋ | 17/100 [00:07<00:38, 2.17it/s] 18%|█▊ | 18/100 [00:08<00:37, 2.17it/s] 19%|█▉ | 19/100 [00:08<00:37, 2.16it/s] 20%|██ | 20/100 [00:09<00:36, 2.16it/s] 21%|██ | 21/100 [00:09<00:36, 2.16it/s] 22%|██▏ | 22/100 [00:10<00:36, 2.16it/s] 23%|██▎ | 23/100 [00:10<00:35, 2.16it/s] 24%|██▍ | 24/100 [00:11<00:35, 2.16it/s] 25%|██▌ | 25/100 [00:11<00:34, 2.16it/s] 26%|██▌ | 26/100 [00:12<00:34, 2.16it/s] 27%|██▋ | 27/100 [00:12<00:33, 2.16it/s] 28%|██▊ | 28/100 [00:12<00:33, 2.16it/s] 29%|██▉ | 29/100 [00:13<00:32, 2.16it/s] 30%|███ | 30/100 [00:13<00:32, 2.16it/s] 31%|███ | 31/100 [00:14<00:32, 2.16it/s] 32%|███▏ | 32/100 [00:14<00:31, 2.16it/s] 33%|███▎ | 33/100 [00:15<00:31, 2.16it/s] 34%|███▍ | 34/100 [00:15<00:30, 2.15it/s] 35%|███▌ | 35/100 [00:16<00:30, 2.15it/s] 36%|███▌ | 36/100 [00:16<00:29, 2.15it/s] 37%|███▋ | 37/100 [00:17<00:29, 2.15it/s] 38%|███▊ | 38/100 [00:17<00:28, 2.15it/s] 39%|███▉ | 39/100 [00:18<00:28, 2.15it/s] 40%|████ | 40/100 [00:18<00:27, 2.15it/s] 41%|████ | 41/100 [00:18<00:27, 2.15it/s] 42%|████▏ | 42/100 [00:19<00:26, 2.15it/s] 43%|████▎ | 43/100 [00:19<00:26, 2.15it/s] 44%|████▍ | 44/100 [00:20<00:26, 2.15it/s] 45%|████▌ | 45/100 [00:20<00:25, 2.15it/s] 46%|████▌ | 46/100 [00:21<00:25, 2.15it/s] 47%|████▋ | 47/100 [00:21<00:24, 2.15it/s] 48%|████▊ | 48/100 [00:22<00:24, 2.15it/s] 49%|████▉ | 49/100 [00:22<00:23, 2.15it/s] 50%|█████ | 50/100 [00:23<00:23, 2.15it/s] 51%|█████ | 51/100 [00:23<00:22, 2.15it/s] 52%|█████▏ | 52/100 [00:24<00:22, 2.15it/s] 53%|█████▎ | 53/100 [00:24<00:21, 2.15it/s] 54%|█████▍ | 54/100 [00:25<00:21, 2.15it/s] 55%|█████▌ | 55/100 [00:25<00:20, 2.15it/s] 56%|█████▌ | 56/100 [00:25<00:20, 2.15it/s] 57%|█████▋ | 57/100 [00:26<00:20, 2.15it/s] 58%|█████▊ | 58/100 [00:26<00:19, 2.15it/s] 59%|█████▉ | 59/100 [00:27<00:19, 2.15it/s] 60%|██████ | 60/100 [00:27<00:18, 2.15it/s] 61%|██████ | 61/100 [00:28<00:18, 2.15it/s] 62%|██████▏ | 62/100 [00:28<00:17, 2.15it/s] 63%|██████▎ | 63/100 [00:29<00:17, 2.15it/s] 64%|██████▍ | 64/100 [00:29<00:16, 2.15it/s] 65%|██████▌ | 65/100 [00:30<00:16, 2.15it/s] 66%|██████▌ | 66/100 [00:30<00:15, 2.15it/s] 67%|██████▋ | 67/100 [00:31<00:15, 2.15it/s] 68%|██████▊ | 68/100 [00:31<00:14, 2.15it/s] 69%|██████▉ | 69/100 [00:32<00:14, 2.15it/s] 70%|███████ | 70/100 [00:32<00:13, 2.15it/s] 71%|███████ | 71/100 [00:32<00:13, 2.15it/s] 72%|███████▏ | 72/100 [00:33<00:13, 2.15it/s] 73%|███████▎ | 73/100 [00:33<00:12, 2.15it/s] 74%|███████▍ | 74/100 [00:34<00:12, 2.15it/s] 75%|███████▌ | 75/100 [00:34<00:11, 2.15it/s] 76%|███████▌ | 76/100 [00:35<00:11, 2.15it/s] 77%|███████▋ | 77/100 [00:35<00:10, 2.15it/s] 78%|███████▊ | 78/100 [00:36<00:10, 2.15it/s] 79%|███████▉ | 79/100 [00:36<00:09, 2.15it/s] 80%|████████ | 80/100 [00:37<00:09, 2.15it/s] 81%|████████ | 81/100 [00:37<00:08, 2.14it/s] 82%|████████▏ | 82/100 [00:38<00:08, 2.13it/s] 83%|████████▎ | 83/100 [00:38<00:07, 2.13it/s] 84%|████████▍ | 84/100 [00:39<00:07, 2.14it/s] 85%|████████▌ | 85/100 [00:39<00:07, 2.14it/s] 86%|████████▌ | 86/100 [00:39<00:06, 2.14it/s] 87%|████████▋ | 87/100 [00:40<00:06, 2.15it/s] 88%|████████▊ | 88/100 [00:40<00:05, 2.15it/s] 89%|████████▉ | 89/100 [00:41<00:05, 2.15it/s] 90%|█████████ | 90/100 [00:41<00:04, 2.15it/s] 91%|█████████ | 91/100 [00:42<00:04, 2.15it/s] 92%|█████████▏| 92/100 [00:42<00:03, 2.15it/s] 93%|█████████▎| 93/100 [00:43<00:03, 2.15it/s] 94%|█████████▍| 94/100 [00:43<00:02, 2.15it/s] 95%|█████████▌| 95/100 [00:44<00:02, 2.15it/s] 96%|█████████▌| 96/100 [00:44<00:01, 2.15it/s] 97%|█████████▋| 97/100 [00:45<00:01, 2.15it/s] 98%|█████████▊| 98/100 [00:45<00:00, 2.15it/s] 99%|█████████▉| 99/100 [00:45<00:00, 2.15it/s] 100%|██████████| 100/100 [00:46<00:00, 2.15it/s] 100%|██████████| 100/100 [00:46<00:00, 2.15it/s] Prediction complete
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