zylim0702
/
controlnet-v1-1-multi
clip interrogator with controlnet sdxl for canny and controlnet v1.1 for the others
- Public
- 2K runs
-
L40S
Prediction
zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88aIDtntmvudbhpfncycnoocai6z7xaStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- image
- scale
- 9
- prompt
- a dog in a bright sunshine jungle, hard lighting
- a_prompt
- Best quality, extremely detailed
- n_prompt
- Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
- strength
- 1
- structure
- canny
- ddim_steps
- 20
- num_samples
- 1
- low_threshold
- 100
- high_threshold
- 200
- image_upscaler
- autogenerated_prompt
- preprocessor_resolution
- 512
{ "image": "https://replicate.delivery/pbxt/JREI44b9KCW78ynS9sH9je7wCckmEHcSF3EXwJBlhDhbh0jH/dog.png", "scale": 9, "prompt": "a dog in a bright sunshine jungle, hard lighting", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": false, "autogenerated_prompt": true, "preprocessor_resolution": 512 }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 zylim0702/controlnet-v1-1-multi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a", { input: { image: "https://replicate.delivery/pbxt/JREI44b9KCW78ynS9sH9je7wCckmEHcSF3EXwJBlhDhbh0jH/dog.png", scale: 9, prompt: "a dog in a bright sunshine jungle, hard lighting", a_prompt: "Best quality, extremely detailed", n_prompt: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", strength: 1, structure: "canny", ddim_steps: 20, num_samples: 1, low_threshold: 100, high_threshold: 200, image_upscaler: false, autogenerated_prompt: true, preprocessor_resolution: 512 } } ); // 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 zylim0702/controlnet-v1-1-multi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a", input={ "image": "https://replicate.delivery/pbxt/JREI44b9KCW78ynS9sH9je7wCckmEHcSF3EXwJBlhDhbh0jH/dog.png", "scale": 9, "prompt": "a dog in a bright sunshine jungle, hard lighting", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": False, "autogenerated_prompt": True, "preprocessor_resolution": 512 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run zylim0702/controlnet-v1-1-multi 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": "zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a", "input": { "image": "https://replicate.delivery/pbxt/JREI44b9KCW78ynS9sH9je7wCckmEHcSF3EXwJBlhDhbh0jH/dog.png", "scale": 9, "prompt": "a dog in a bright sunshine jungle, hard lighting", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": false, "autogenerated_prompt": true, "preprocessor_resolution": 512 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-31T01:13:17.775722Z", "created_at": "2023-08-31T01:13:09.043216Z", "data_removed": false, "error": null, "id": "tntmvudbhpfncycnoocai6z7xa", "input": { "image": "https://replicate.delivery/pbxt/JREI44b9KCW78ynS9sH9je7wCckmEHcSF3EXwJBlhDhbh0jH/dog.png", "scale": 9, "prompt": "a dog in a bright sunshine jungle, hard lighting", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": false, "autogenerated_prompt": true, "preprocessor_resolution": 512 }, "logs": "0%| | 0/55 [00:00<?, ?it/s]\n 56%|█████▋ | 31/55 [00:00<00:00, 304.70it/s]\n100%|██████████| 55/55 [00:00<00:00, 309.42it/s]\na dog in a bright sunshine jungle, hard lighting, there is a dog sitting on a bench in a field, sitting on a bench, sitting on bench, sit on a bench, sitting on a park bench, happy dog, portrait, benches, portrait shot, award - winning pet photography, portrait image, sittin, a wooden, four legged, medium portrait, on a sunny day, at a park, peaceful mood\nUsing seed: 25123\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['sunny day, at a park, peaceful mood']\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['sunny day, at a park, peaceful mood']\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:05, 3.44it/s]\n 10%|█ | 2/20 [00:00<00:05, 3.43it/s]\n 15%|█▌ | 3/20 [00:00<00:04, 3.42it/s]\n 20%|██ | 4/20 [00:01<00:04, 3.41it/s]\n 25%|██▌ | 5/20 [00:01<00:04, 3.41it/s]\n 30%|███ | 6/20 [00:01<00:04, 3.41it/s]\n 35%|███▌ | 7/20 [00:02<00:03, 3.41it/s]\n 40%|████ | 8/20 [00:02<00:03, 3.41it/s]\n 45%|████▌ | 9/20 [00:02<00:03, 3.41it/s]\n 50%|█████ | 10/20 [00:02<00:02, 3.41it/s]\n 55%|█████▌ | 11/20 [00:03<00:02, 3.40it/s]\n 60%|██████ | 12/20 [00:03<00:02, 3.40it/s]\n 65%|██████▌ | 13/20 [00:03<00:02, 3.40it/s]\n 70%|███████ | 14/20 [00:04<00:01, 3.40it/s]\n 75%|███████▌ | 15/20 [00:04<00:01, 3.40it/s]\n 80%|████████ | 16/20 [00:04<00:01, 3.40it/s]\n 85%|████████▌ | 17/20 [00:04<00:00, 3.41it/s]\n 90%|█████████ | 18/20 [00:05<00:00, 3.42it/s]\n 95%|█████████▌| 19/20 [00:05<00:00, 3.42it/s]\n100%|██████████| 20/20 [00:05<00:00, 3.42it/s]\n100%|██████████| 20/20 [00:05<00:00, 3.41it/s]", "metrics": { "predict_time": 8.817962, "total_time": 8.732506 }, "output": [ "https://replicate.delivery/pbxt/kARY8cHjYeSXdyeeXaOsKlECvnhwD0ijD7MHYvP7X3NZZzeFB/out-0.png" ], "started_at": "2023-08-31T01:13:08.957760Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/tntmvudbhpfncycnoocai6z7xa", "cancel": "https://api.replicate.com/v1/predictions/tntmvudbhpfncycnoocai6z7xa/cancel" }, "version": "211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a" }Generated in0%| | 0/55 [00:00<?, ?it/s] 56%|█████▋ | 31/55 [00:00<00:00, 304.70it/s] 100%|██████████| 55/55 [00:00<00:00, 309.42it/s] a dog in a bright sunshine jungle, hard lighting, there is a dog sitting on a bench in a field, sitting on a bench, sitting on bench, sit on a bench, sitting on a park bench, happy dog, portrait, benches, portrait shot, award - winning pet photography, portrait image, sittin, a wooden, four legged, medium portrait, on a sunny day, at a park, peaceful mood Using seed: 25123 The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['sunny day, at a park, peaceful mood'] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['sunny day, at a park, peaceful mood'] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:05, 3.44it/s] 10%|█ | 2/20 [00:00<00:05, 3.43it/s] 15%|█▌ | 3/20 [00:00<00:04, 3.42it/s] 20%|██ | 4/20 [00:01<00:04, 3.41it/s] 25%|██▌ | 5/20 [00:01<00:04, 3.41it/s] 30%|███ | 6/20 [00:01<00:04, 3.41it/s] 35%|███▌ | 7/20 [00:02<00:03, 3.41it/s] 40%|████ | 8/20 [00:02<00:03, 3.41it/s] 45%|████▌ | 9/20 [00:02<00:03, 3.41it/s] 50%|█████ | 10/20 [00:02<00:02, 3.41it/s] 55%|█████▌ | 11/20 [00:03<00:02, 3.40it/s] 60%|██████ | 12/20 [00:03<00:02, 3.40it/s] 65%|██████▌ | 13/20 [00:03<00:02, 3.40it/s] 70%|███████ | 14/20 [00:04<00:01, 3.40it/s] 75%|███████▌ | 15/20 [00:04<00:01, 3.40it/s] 80%|████████ | 16/20 [00:04<00:01, 3.40it/s] 85%|████████▌ | 17/20 [00:04<00:00, 3.41it/s] 90%|█████████ | 18/20 [00:05<00:00, 3.42it/s] 95%|█████████▌| 19/20 [00:05<00:00, 3.42it/s] 100%|██████████| 20/20 [00:05<00:00, 3.42it/s] 100%|██████████| 20/20 [00:05<00:00, 3.41it/s]Prediction
zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88aIDxis6bdtbdvakgcanvtmwj5no3iStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- eta
- 0
- image
- scale
- 9
- prompt
- Bright jungle with ice and snow
- a_prompt
- Best quality, extremely detailed
- n_prompt
- Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
- strength
- 1
- structure
- canny
- ddim_steps
- 20
- num_samples
- 1
- low_threshold
- 100
- high_threshold
- 200
- image_upscaler
- autogenerated_prompt
- preprocessor_resolution
- 512
{ "eta": 0, "image": "https://replicate.delivery/pbxt/JRYTwtDsoFUwmRypxY3NwBm38RPT3vR59tsdIlOJNFkSGFgT/DJI_0459_1.jpg", "scale": 9, "prompt": "Bright jungle with ice and snow", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": false, "autogenerated_prompt": true, "preprocessor_resolution": 512 }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 zylim0702/controlnet-v1-1-multi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a", { input: { eta: 0, image: "https://replicate.delivery/pbxt/JRYTwtDsoFUwmRypxY3NwBm38RPT3vR59tsdIlOJNFkSGFgT/DJI_0459_1.jpg", scale: 9, prompt: "Bright jungle with ice and snow", a_prompt: "Best quality, extremely detailed", n_prompt: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", strength: 1, structure: "canny", ddim_steps: 20, num_samples: 1, low_threshold: 100, high_threshold: 200, image_upscaler: false, autogenerated_prompt: true, preprocessor_resolution: 512 } } ); // 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 zylim0702/controlnet-v1-1-multi using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a", input={ "eta": 0, "image": "https://replicate.delivery/pbxt/JRYTwtDsoFUwmRypxY3NwBm38RPT3vR59tsdIlOJNFkSGFgT/DJI_0459_1.jpg", "scale": 9, "prompt": "Bright jungle with ice and snow", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": False, "autogenerated_prompt": True, "preprocessor_resolution": 512 } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run zylim0702/controlnet-v1-1-multi 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": "zylim0702/controlnet-v1-1-multi:211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a", "input": { "eta": 0, "image": "https://replicate.delivery/pbxt/JRYTwtDsoFUwmRypxY3NwBm38RPT3vR59tsdIlOJNFkSGFgT/DJI_0459_1.jpg", "scale": 9, "prompt": "Bright jungle with ice and snow", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": false, "autogenerated_prompt": true, "preprocessor_resolution": 512 } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2023-08-31T01:18:39.394563Z", "created_at": "2023-08-31T01:18:31.637386Z", "data_removed": false, "error": null, "id": "xis6bdtbdvakgcanvtmwj5no3i", "input": { "eta": 0, "image": "https://replicate.delivery/pbxt/JRYTwtDsoFUwmRypxY3NwBm38RPT3vR59tsdIlOJNFkSGFgT/DJI_0459_1.jpg", "scale": 9, "prompt": "Bright jungle with ice and snow", "a_prompt": "Best quality, extremely detailed", "n_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality", "strength": 1, "structure": "canny", "ddim_steps": 20, "num_samples": 1, "low_threshold": 100, "high_threshold": 200, "image_upscaler": false, "autogenerated_prompt": true, "preprocessor_resolution": 512 }, "logs": "0%| | 0/55 [00:00<?, ?it/s]\n 65%|██████▌ | 36/55 [00:00<00:00, 358.79it/s]\n100%|██████████| 55/55 [00:00<00:00, 361.77it/s]\nBright jungle with ice and snow, arafed view of a river with a lot of houses and boats, flooded fishing village, aerial perspective, aerial view from above, perspective shot from the sky, photo taken from above, aerial shot, aerial shot from the drone, fishing town, drone view, aerial, above view, photograph from above, shutterstock, aerial photography, realistic photo of a town\nUsing seed: 8591\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['realistic photo of a town']\nThe following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['realistic photo of a town']\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:05, 3.77it/s]\n 10%|█ | 2/20 [00:00<00:04, 4.15it/s]\n 15%|█▌ | 3/20 [00:00<00:03, 4.28it/s]\n 20%|██ | 4/20 [00:00<00:03, 4.34it/s]\n 25%|██▌ | 5/20 [00:01<00:03, 4.38it/s]\n 30%|███ | 6/20 [00:01<00:03, 4.39it/s]\n 35%|███▌ | 7/20 [00:01<00:02, 4.41it/s]\n 40%|████ | 8/20 [00:01<00:02, 4.42it/s]\n 45%|████▌ | 9/20 [00:02<00:02, 4.42it/s]\n 50%|█████ | 10/20 [00:02<00:02, 4.42it/s]\n 55%|█████▌ | 11/20 [00:02<00:02, 4.42it/s]\n 60%|██████ | 12/20 [00:02<00:01, 4.42it/s]\n 65%|██████▌ | 13/20 [00:02<00:01, 4.42it/s]\n 70%|███████ | 14/20 [00:03<00:01, 4.42it/s]\n 75%|███████▌ | 15/20 [00:03<00:01, 4.42it/s]\n 80%|████████ | 16/20 [00:03<00:00, 4.42it/s]\n 85%|████████▌ | 17/20 [00:03<00:00, 4.42it/s]\n 90%|█████████ | 18/20 [00:04<00:00, 4.42it/s]\n 95%|█████████▌| 19/20 [00:04<00:00, 4.42it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.42it/s]\n100%|██████████| 20/20 [00:04<00:00, 4.39it/s]", "metrics": { "predict_time": 7.753982, "total_time": 7.757177 }, "output": [ "https://replicate.delivery/pbxt/UcJLTseon42mXanoQ9R6CLelTEkObe7VSfV6fPbMeSznbc2XE/out-0.png" ], "started_at": "2023-08-31T01:18:31.640581Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/xis6bdtbdvakgcanvtmwj5no3i", "cancel": "https://api.replicate.com/v1/predictions/xis6bdtbdvakgcanvtmwj5no3i/cancel" }, "version": "211486c3a33e26c7513c3ae4db00621f155bff401d3a241e260995e04bbbd88a" }Generated in0%| | 0/55 [00:00<?, ?it/s] 65%|██████▌ | 36/55 [00:00<00:00, 358.79it/s] 100%|██████████| 55/55 [00:00<00:00, 361.77it/s] Bright jungle with ice and snow, arafed view of a river with a lot of houses and boats, flooded fishing village, aerial perspective, aerial view from above, perspective shot from the sky, photo taken from above, aerial shot, aerial shot from the drone, fishing town, drone view, aerial, above view, photograph from above, shutterstock, aerial photography, realistic photo of a town Using seed: 8591 The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['realistic photo of a town'] The following part of your input was truncated because CLIP can only handle sequences up to 77 tokens: ['realistic photo of a town'] 0%| | 0/20 [00:00<?, ?it/s] 5%|▌ | 1/20 [00:00<00:05, 3.77it/s] 10%|█ | 2/20 [00:00<00:04, 4.15it/s] 15%|█▌ | 3/20 [00:00<00:03, 4.28it/s] 20%|██ | 4/20 [00:00<00:03, 4.34it/s] 25%|██▌ | 5/20 [00:01<00:03, 4.38it/s] 30%|███ | 6/20 [00:01<00:03, 4.39it/s] 35%|███▌ | 7/20 [00:01<00:02, 4.41it/s] 40%|████ | 8/20 [00:01<00:02, 4.42it/s] 45%|████▌ | 9/20 [00:02<00:02, 4.42it/s] 50%|█████ | 10/20 [00:02<00:02, 4.42it/s] 55%|█████▌ | 11/20 [00:02<00:02, 4.42it/s] 60%|██████ | 12/20 [00:02<00:01, 4.42it/s] 65%|██████▌ | 13/20 [00:02<00:01, 4.42it/s] 70%|███████ | 14/20 [00:03<00:01, 4.42it/s] 75%|███████▌ | 15/20 [00:03<00:01, 4.42it/s] 80%|████████ | 16/20 [00:03<00:00, 4.42it/s] 85%|████████▌ | 17/20 [00:03<00:00, 4.42it/s] 90%|█████████ | 18/20 [00:04<00:00, 4.42it/s] 95%|█████████▌| 19/20 [00:04<00:00, 4.42it/s] 100%|██████████| 20/20 [00:04<00:00, 4.42it/s] 100%|██████████| 20/20 [00:04<00:00, 4.39it/s]
Want to make some of these yourself?
Run this model