Versions
465fb417
Latest
628d6087
You're looking at a specific version of this model. Jump to the model overview.
lucataco /sdxl-controlnet-depth:465fb417
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=lucataco/sdxl-controlnet-depth
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run lucataco/sdxl-controlnet-depth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/sdxl-controlnet-depth:465fb41789dc2203a9d7158be11d1d2570606a039c65e0e236fd329b5eecb10c",
{
input: {
seed: 25087,
image: "https://replicate.delivery/pbxt/JLl0qK0Hjm0GCGhfrmDPQDZkzKHBD98jQ1EjiRiUpC08MzK1/demo.png",
prompt: "spiderman lecture, photorealistic",
condition_scale: 0.5,
num_inference_steps: 30
}
}
);
console.log(output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun lucataco/sdxl-controlnet-depth using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/sdxl-controlnet-depth:465fb41789dc2203a9d7158be11d1d2570606a039c65e0e236fd329b5eecb10c",
input={
"seed": 25087,
"image": "https://replicate.delivery/pbxt/JLl0qK0Hjm0GCGhfrmDPQDZkzKHBD98jQ1EjiRiUpC08MzK1/demo.png",
"prompt": "spiderman lecture, photorealistic",
"condition_scale": 0.5,
"num_inference_steps": 30
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run lucataco/sdxl-controlnet-depth 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": "465fb41789dc2203a9d7158be11d1d2570606a039c65e0e236fd329b5eecb10c",
"input": {
"seed": 25087,
"image": "https://replicate.delivery/pbxt/JLl0qK0Hjm0GCGhfrmDPQDZkzKHBD98jQ1EjiRiUpC08MzK1/demo.png",
"prompt": "spiderman lecture, photorealistic",
"condition_scale": 0.5,
"num_inference_steps": 30
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/lucataco/sdxl-controlnet-depth@sha256:465fb41789dc2203a9d7158be11d1d2570606a039c65e0e236fd329b5eecb10c \
-i 'seed=25087' \
-i 'image="https://replicate.delivery/pbxt/JLl0qK0Hjm0GCGhfrmDPQDZkzKHBD98jQ1EjiRiUpC08MzK1/demo.png"' \
-i 'prompt="spiderman lecture, photorealistic"' \
-i 'condition_scale=0.5' \
-i 'num_inference_steps=30'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/lucataco/sdxl-controlnet-depth@sha256:465fb41789dc2203a9d7158be11d1d2570606a039c65e0e236fd329b5eecb10ccurl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "seed": 25087, "image": "https://replicate.delivery/pbxt/JLl0qK0Hjm0GCGhfrmDPQDZkzKHBD98jQ1EjiRiUpC08MzK1/demo.png", "prompt": "spiderman lecture, photorealistic", "condition_scale": 0.5, "num_inference_steps": 30 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
Each run costs approximately $0.031. Alternatively, try out our featured models for free.
Sign in with GitHub
By signing in, you agree to our
terms of service and privacy policy
Output
{
"completed_at": "2023-09-12T22:47:53.749512Z",
"created_at": "2023-09-12T22:45:45.734709Z",
"data_removed": false,
"error": null,
"id": "cgekvctbear65ui5vgwiahmn34",
"input": {
"seed": 25087,
"image": "https://replicate.delivery/pbxt/JLl0qK0Hjm0GCGhfrmDPQDZkzKHBD98jQ1EjiRiUpC08MzK1/demo.png",
"prompt": "spiderman lecture, photorealistic",
"condition_scale": 0.5,
"num_inference_steps": 30
},
"logs": "Using seed: 25087\nOriginal width:458, height:458\nAspect Ratio: 1.00\nnew_width:1024, new_height:1024\n 0%| | 0/30 [00:00<?, ?it/s]\n 3%|▎ | 1/30 [00:00<00:09, 3.05it/s]\n 7%|▋ | 2/30 [00:00<00:08, 3.26it/s]\n 10%|█ | 3/30 [00:00<00:08, 3.33it/s]\n 13%|█▎ | 4/30 [00:01<00:07, 3.34it/s]\n 17%|█▋ | 5/30 [00:01<00:07, 3.36it/s]\n 20%|██ | 6/30 [00:01<00:07, 3.38it/s]\n 23%|██▎ | 7/30 [00:02<00:06, 3.38it/s]\n 27%|██▋ | 8/30 [00:02<00:06, 3.38it/s]\n 30%|███ | 9/30 [00:02<00:06, 3.39it/s]\n 33%|███▎ | 10/30 [00:02<00:05, 3.39it/s]\n 37%|███▋ | 11/30 [00:03<00:05, 3.38it/s]\n 40%|████ | 12/30 [00:03<00:05, 3.35it/s]\n 43%|████▎ | 13/30 [00:03<00:05, 3.37it/s]\n 47%|████▋ | 14/30 [00:04<00:04, 3.37it/s]\n 50%|█████ | 15/30 [00:04<00:04, 3.37it/s]\n 53%|█████▎ | 16/30 [00:04<00:04, 3.38it/s]\n 57%|█████▋ | 17/30 [00:05<00:03, 3.38it/s]\n 60%|██████ | 18/30 [00:05<00:03, 3.38it/s]\n 63%|██████▎ | 19/30 [00:05<00:03, 3.38it/s]\n 67%|██████▋ | 20/30 [00:05<00:02, 3.38it/s]\n 70%|███████ | 21/30 [00:06<00:02, 3.38it/s]\n 73%|███████▎ | 22/30 [00:06<00:02, 3.38it/s]\n 77%|███████▋ | 23/30 [00:06<00:02, 3.38it/s]\n 80%|████████ | 24/30 [00:07<00:01, 3.38it/s]\n 83%|████████▎ | 25/30 [00:07<00:01, 3.38it/s]\n 87%|████████▋ | 26/30 [00:07<00:01, 3.38it/s]\n 90%|█████████ | 27/30 [00:08<00:00, 3.38it/s]\n 93%|█████████▎| 28/30 [00:08<00:00, 3.38it/s]\n 97%|█████████▋| 29/30 [00:08<00:00, 3.38it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.38it/s]\n100%|██████████| 30/30 [00:08<00:00, 3.37it/s]",
"metrics": {
"predict_time": 12.481869,
"total_time": 128.014803
},
"output": "https://pbxt.replicate.delivery/lvhWUVZ8cqaaDRyNwcoP5SxZnZYO8lG3JXqRmNFAM5Fmc6YE/output.png",
"started_at": "2023-09-12T22:47:41.267643Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/cgekvctbear65ui5vgwiahmn34",
"cancel": "https://api.replicate.com/v1/predictions/cgekvctbear65ui5vgwiahmn34/cancel"
},
"version": "5e0a5cda895aa23a1aaa1a9a265220097102448e1b4c42b22a3c6d87c12d41a9"
}Generated in
Using seed: 25087
Original width:458, height:458
Aspect Ratio: 1.00
new_width:1024, new_height:1024
0%| | 0/30 [00:00<?, ?it/s]
3%|▎ | 1/30 [00:00<00:09, 3.05it/s]
7%|▋ | 2/30 [00:00<00:08, 3.26it/s]
10%|█ | 3/30 [00:00<00:08, 3.33it/s]
13%|█▎ | 4/30 [00:01<00:07, 3.34it/s]
17%|█▋ | 5/30 [00:01<00:07, 3.36it/s]
20%|██ | 6/30 [00:01<00:07, 3.38it/s]
23%|██▎ | 7/30 [00:02<00:06, 3.38it/s]
27%|██▋ | 8/30 [00:02<00:06, 3.38it/s]
30%|███ | 9/30 [00:02<00:06, 3.39it/s]
33%|███▎ | 10/30 [00:02<00:05, 3.39it/s]
37%|███▋ | 11/30 [00:03<00:05, 3.38it/s]
40%|████ | 12/30 [00:03<00:05, 3.35it/s]
43%|████▎ | 13/30 [00:03<00:05, 3.37it/s]
47%|████▋ | 14/30 [00:04<00:04, 3.37it/s]
50%|█████ | 15/30 [00:04<00:04, 3.37it/s]
53%|█████▎ | 16/30 [00:04<00:04, 3.38it/s]
57%|█████▋ | 17/30 [00:05<00:03, 3.38it/s]
60%|██████ | 18/30 [00:05<00:03, 3.38it/s]
63%|██████▎ | 19/30 [00:05<00:03, 3.38it/s]
67%|██████▋ | 20/30 [00:05<00:02, 3.38it/s]
70%|███████ | 21/30 [00:06<00:02, 3.38it/s]
73%|███████▎ | 22/30 [00:06<00:02, 3.38it/s]
77%|███████▋ | 23/30 [00:06<00:02, 3.38it/s]
80%|████████ | 24/30 [00:07<00:01, 3.38it/s]
83%|████████▎ | 25/30 [00:07<00:01, 3.38it/s]
87%|████████▋ | 26/30 [00:07<00:01, 3.38it/s]
90%|█████████ | 27/30 [00:08<00:00, 3.38it/s]
93%|█████████▎| 28/30 [00:08<00:00, 3.38it/s]
97%|█████████▋| 29/30 [00:08<00:00, 3.38it/s]
100%|██████████| 30/30 [00:08<00:00, 3.38it/s]
100%|██████████| 30/30 [00:08<00:00, 3.37it/s]This example was created by a different version, lucataco/sdxl-controlnet-depth:5e0a5cda.