Prediction
usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5:59c1f5ce85cf1ea03e07508964ff41968cfad2a61820e3455930120ae2d594f5Input
- eta
- 0
- prompt
- underwater++ world
- max_width
- 512
- scheduler
- DDIM
- guess_mode
- max_height
- 512
- num_outputs
- 1
- lineart_image
- 955ad4a4680988283115264b5b45c211.jpg
- guidance_scale
- 7
- negative_prompt
- Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
- consistency_decoder
- num_inference_steps
- 20
- disable_safety_check
- tile_conditioning_scale
- 1
- depth_conditioning_scale
- 1
- lineart_conditioning_scale
- 1
- scribble_conditioning_scale
- 1
- brightness_conditioning_scale
- 1
- inpainting_conditioning_scale
- 1
{
"eta": 0,
"prompt": "underwater++ world",
"max_width": 512,
"scheduler": "DDIM",
"guess_mode": false,
"max_height": 512,
"num_outputs": 1,
"lineart_image": "https://replicate.delivery/pbxt/Jqzz9g4kPNdw0IyCqEGIXBHCr33Ai9agnbnZGdNVUUKoJqt3/955ad4a4680988283115264b5b45c211.jpg",
"guidance_scale": 7,
"negative_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
"consistency_decoder": true,
"num_inference_steps": 20,
"disable_safety_check": true,
"tile_conditioning_scale": 1,
"depth_conditioning_scale": 1,
"lineart_conditioning_scale": 1,
"scribble_conditioning_scale": 1,
"brightness_conditioning_scale": 1,
"inpainting_conditioning_scale": 1
}
npm install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5:59c1f5ce85cf1ea03e07508964ff41968cfad2a61820e3455930120ae2d594f5",
{
input: {
eta: 0,
prompt: "underwater++ world",
max_width: 512,
scheduler: "DDIM",
guess_mode: false,
max_height: 512,
num_outputs: 1,
lineart_image: "https://replicate.delivery/pbxt/Jqzz9g4kPNdw0IyCqEGIXBHCr33Ai9agnbnZGdNVUUKoJqt3/955ad4a4680988283115264b5b45c211.jpg",
guidance_scale: 7,
negative_prompt: "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
consistency_decoder: true,
num_inference_steps: 20,
disable_safety_check: true,
tile_conditioning_scale: 1,
depth_conditioning_scale: 1,
lineart_conditioning_scale: 1,
scribble_conditioning_scale: 1,
brightness_conditioning_scale: 1,
inpainting_conditioning_scale: 1
}
}
);
// 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.
pip install replicate
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5:59c1f5ce85cf1ea03e07508964ff41968cfad2a61820e3455930120ae2d594f5",
input={
"eta": 0,
"prompt": "underwater++ world",
"max_width": 512,
"scheduler": "DDIM",
"guess_mode": False,
"max_height": 512,
"num_outputs": 1,
"lineart_image": "https://replicate.delivery/pbxt/Jqzz9g4kPNdw0IyCqEGIXBHCr33Ai9agnbnZGdNVUUKoJqt3/955ad4a4680988283115264b5b45c211.jpg",
"guidance_scale": 7,
"negative_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
"consistency_decoder": True,
"num_inference_steps": 20,
"disable_safety_check": True,
"tile_conditioning_scale": 1,
"depth_conditioning_scale": 1,
"lineart_conditioning_scale": 1,
"scribble_conditioning_scale": 1,
"brightness_conditioning_scale": 1,
"inpainting_conditioning_scale": 1
}
)
# To access the file URL:
print(output[0].url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output[0].read())
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5 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": "usamaehsan/multi-controlnet-x-consistency-decoder-x-realestic-vision-v5:59c1f5ce85cf1ea03e07508964ff41968cfad2a61820e3455930120ae2d594f5",
"input": {
"eta": 0,
"prompt": "underwater++ world",
"max_width": 512,
"scheduler": "DDIM",
"guess_mode": false,
"max_height": 512,
"num_outputs": 1,
"lineart_image": "https://replicate.delivery/pbxt/Jqzz9g4kPNdw0IyCqEGIXBHCr33Ai9agnbnZGdNVUUKoJqt3/955ad4a4680988283115264b5b45c211.jpg",
"guidance_scale": 7,
"negative_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
"consistency_decoder": true,
"num_inference_steps": 20,
"disable_safety_check": true,
"tile_conditioning_scale": 1,
"depth_conditioning_scale": 1,
"lineart_conditioning_scale": 1,
"scribble_conditioning_scale": 1,
"brightness_conditioning_scale": 1,
"inpainting_conditioning_scale": 1
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{
"completed_at": "2023-11-10T17:42:18.197496Z",
"created_at": "2023-11-10T17:39:02.361897Z",
"data_removed": false,
"error": null,
"id": "nixvsb3byk2c73cm6hq32v4boq",
"input": {
"eta": 0,
"prompt": "underwater++ world",
"max_width": 512,
"scheduler": "DDIM",
"guess_mode": false,
"max_height": 512,
"num_outputs": 1,
"lineart_image": "https://replicate.delivery/pbxt/Jqzz9g4kPNdw0IyCqEGIXBHCr33Ai9agnbnZGdNVUUKoJqt3/955ad4a4680988283115264b5b45c211.jpg",
"guidance_scale": 7,
"negative_prompt": "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
"consistency_decoder": true,
"num_inference_steps": 20,
"disable_safety_check": true,
"tile_conditioning_scale": 1,
"depth_conditioning_scale": 1,
"lineart_conditioning_scale": 1,
"scribble_conditioning_scale": 1,
"brightness_conditioning_scale": 1,
"inpainting_conditioning_scale": 1
},
"logs": "You have disabled the safety checker for <class 'diffusers.pipelines.controlnet.pipeline_controlnet.StableDiffusionControlNetPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .\nUsing seed: 44665\n 0%| | 0/20 [00:00<?, ?it/s]\n 5%|▌ | 1/20 [00:00<00:03, 4.83it/s]\n 20%|██ | 4/20 [00:00<00:01, 12.98it/s]\n 35%|███▌ | 7/20 [00:00<00:00, 16.54it/s]\n 50%|█████ | 10/20 [00:00<00:00, 18.42it/s]\n 60%|██████ | 12/20 [00:00<00:00, 18.76it/s]\n 70%|███████ | 14/20 [00:00<00:00, 18.86it/s]\n 85%|████████▌ | 17/20 [00:00<00:00, 19.89it/s]\n100%|██████████| 20/20 [00:01<00:00, 20.41it/s]\n100%|██████████| 20/20 [00:01<00:00, 18.04it/s]\nRunning consistency decoder...\nConsistency decoder took 11.307215690612793 seconds",
"metrics": {
"predict_time": 15.267783,
"total_time": 195.835599
},
"output": [
"https://replicate.delivery/pbxt/FMG5rpMM3GrCAVcfnqBFgNDb8mkSfA5mPg5mNJjwgaX51B3RA/seed-44665.png"
],
"started_at": "2023-11-10T17:42:02.929713Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/nixvsb3byk2c73cm6hq32v4boq",
"cancel": "https://api.replicate.com/v1/predictions/nixvsb3byk2c73cm6hq32v4boq/cancel"
},
"version": "59c1f5ce85cf1ea03e07508964ff41968cfad2a61820e3455930120ae2d594f5"
}
You have disabled the safety checker for <class 'diffusers.pipelines.controlnet.pipeline_controlnet.StableDiffusionControlNetPipeline'> by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .
Using seed: 44665
0%| | 0/20 [00:00<?, ?it/s]
5%|▌ | 1/20 [00:00<00:03, 4.83it/s]
20%|██ | 4/20 [00:00<00:01, 12.98it/s]
35%|███▌ | 7/20 [00:00<00:00, 16.54it/s]
50%|█████ | 10/20 [00:00<00:00, 18.42it/s]
60%|██████ | 12/20 [00:00<00:00, 18.76it/s]
70%|███████ | 14/20 [00:00<00:00, 18.86it/s]
85%|████████▌ | 17/20 [00:00<00:00, 19.89it/s]
100%|██████████| 20/20 [00:01<00:00, 20.41it/s]
100%|██████████| 20/20 [00:01<00:00, 18.04it/s]
Running consistency decoder...
Consistency decoder took 11.307215690612793 seconds