jagilley / controlnet-hough

Modify images using M-LSD line detection

Warm

Public
9.5M runs
A100 (80GB)
GitHub
License

Run with an API

Playground API Examples README Versions

Prediction

jagilley/controlnet-hough:854e8727

Model

jagilley/controlnet-hough:854e8727

zgeqaoeoyzee5k72xrn7zp225q

Status

Succeeded

Source

Web

Hardware

–

Total duration

3m 55s

Created

about 2 years ago by @jagilley

Input

image
scale: 9
prompt: a cheerful modernist bedroom
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
ddim_steps: 20
num_samples: 1
value_threshold: 0.1
image_resolution: 512
detect_resolution: 512
distance_threshold: 0.1

{
  "image": "https://replicate.delivery/pbxt/IJZOELWrncBcjdE1s5Ko8ou35ZOxjNxDqMf0BhoRUAtv76u4/room.png",
  "scale": 9,
  "prompt": "a cheerful modernist bedroom",
  "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",
  "ddim_steps": 20,
  "num_samples": "1",
  "value_threshold": 0.1,
  "image_resolution": "512",
  "detect_resolution": 512,
  "distance_threshold": 0.1
}

Install Replicate’s Node.js client library:

npm install replicate

Set 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 jagilley/controlnet-hough using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jagilley/controlnet-hough:854e8727697a057c525cdb45ab037f64ecca770a1769cc52287c2e56472a247b",
  {
    input: {
      image: "https://replicate.delivery/pbxt/IJZOELWrncBcjdE1s5Ko8ou35ZOxjNxDqMf0BhoRUAtv76u4/room.png",
      scale: 9,
      prompt: "a cheerful modernist bedroom",
      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",
      ddim_steps: 20,
      num_samples: "1",
      value_threshold: 0.1,
      image_resolution: "512",
      detect_resolution: 512,
      distance_threshold: 0.1
    }
  }
);
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 replicate

Set 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 replicate

Run jagilley/controlnet-hough using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jagilley/controlnet-hough:854e8727697a057c525cdb45ab037f64ecca770a1769cc52287c2e56472a247b",
    input={
        "image": "https://replicate.delivery/pbxt/IJZOELWrncBcjdE1s5Ko8ou35ZOxjNxDqMf0BhoRUAtv76u4/room.png",
        "scale": 9,
        "prompt": "a cheerful modernist bedroom",
        "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",
        "ddim_steps": 20,
        "num_samples": "1",
        "value_threshold": 0.1,
        "image_resolution": "512",
        "detect_resolution": 512,
        "distance_threshold": 0.1
    }
)
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 jagilley/controlnet-hough 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": "854e8727697a057c525cdb45ab037f64ecca770a1769cc52287c2e56472a247b",
    "input": {
      "image": "https://replicate.delivery/pbxt/IJZOELWrncBcjdE1s5Ko8ou35ZOxjNxDqMf0BhoRUAtv76u4/room.png",
      "scale": 9,
      "prompt": "a cheerful modernist bedroom",
      "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",
      "ddim_steps": 20,
      "num_samples": "1",
      "value_threshold": 0.1,
      "image_resolution": "512",
      "detect_resolution": 512,
      "distance_threshold": 0.1
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2023-02-14T21:23:10.058604Z",
  "created_at": "2023-02-14T21:19:15.426349Z",
  "data_removed": false,
  "error": null,
  "id": "zgeqaoeoyzee5k72xrn7zp225q",
  "input": {
    "image": "https://replicate.delivery/pbxt/IJZOELWrncBcjdE1s5Ko8ou35ZOxjNxDqMf0BhoRUAtv76u4/room.png",
    "scale": 9,
    "prompt": "a cheerful modernist bedroom",
    "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",
    "ddim_steps": 20,
    "num_samples": "1",
    "value_threshold": 0.1,
    "image_resolution": "512",
    "detect_resolution": 512,
    "distance_threshold": 0.1
  },
  "logs": "Global seed set to 954546\nData shape for DDIM sampling is (1, 4, 88, 64), eta 0.0\nRunning DDIM Sampling with 20 timesteps\nDDIM Sampler:   0%|          | 0/20 [00:00<?, ?it/s]\nDDIM Sampler:   5%|▌         | 1/20 [00:01<00:27,  1.46s/it]\nDDIM Sampler:  10%|█         | 2/20 [00:02<00:23,  1.30s/it]\nDDIM Sampler:  15%|█▌        | 3/20 [00:03<00:21,  1.25s/it]\nDDIM Sampler:  20%|██        | 4/20 [00:05<00:19,  1.23s/it]\nDDIM Sampler:  25%|██▌       | 5/20 [00:06<00:18,  1.21s/it]\nDDIM Sampler:  30%|███       | 6/20 [00:07<00:16,  1.21s/it]\nDDIM Sampler:  35%|███▌      | 7/20 [00:08<00:15,  1.21s/it]\nDDIM Sampler:  40%|████      | 8/20 [00:09<00:14,  1.20s/it]\nDDIM Sampler:  45%|████▌     | 9/20 [00:11<00:13,  1.20s/it]\nDDIM Sampler:  50%|█████     | 10/20 [00:12<00:12,  1.20s/it]\nDDIM Sampler:  55%|█████▌    | 11/20 [00:13<00:10,  1.20s/it]\nDDIM Sampler:  60%|██████    | 12/20 [00:14<00:09,  1.20s/it]\nDDIM Sampler:  65%|██████▌   | 13/20 [00:15<00:08,  1.20s/it]\nDDIM Sampler:  70%|███████   | 14/20 [00:17<00:07,  1.21s/it]\nDDIM Sampler:  75%|███████▌  | 15/20 [00:18<00:06,  1.21s/it]\nDDIM Sampler:  80%|████████  | 16/20 [00:19<00:04,  1.21s/it]\nDDIM Sampler:  85%|████████▌ | 17/20 [00:20<00:03,  1.21s/it]\nDDIM Sampler:  90%|█████████ | 18/20 [00:21<00:02,  1.21s/it]\nDDIM Sampler:  95%|█████████▌| 19/20 [00:23<00:01,  1.21s/it]\nDDIM Sampler: 100%|██████████| 20/20 [00:24<00:00,  1.21s/it]\nDDIM Sampler: 100%|██████████| 20/20 [00:24<00:00,  1.22s/it]",
  "metrics": {
    "predict_time": 30.557674,
    "total_time": 234.632255
  },
  "output": [
    "https://replicate.delivery/pbxt/g8O5GtWujE4xId9adfJCpqebz4NvPGHh6Ke1Ica7iIU6t18gA/output_0.png",
    "https://replicate.delivery/pbxt/kfbWmK9LnJRiOqqfOmnYrrbQ4X37kysVlAMllEKManE92aegA/output_1.png"
  ],
  "started_at": "2023-02-14T21:22:39.500930Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/zgeqaoeoyzee5k72xrn7zp225q",
    "cancel": "https://api.replicate.com/v1/predictions/zgeqaoeoyzee5k72xrn7zp225q/cancel"
  },
  "version": "854e8727697a057c525cdb45ab037f64ecca770a1769cc52287c2e56472a247b"
}

Generated in

30.6 seconds

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