MODEL IDrunware:controlnet-preprocess@softedge
live

ControlNet Preprocess SoftEdge

ControlNet Preprocess SoftEdge extracts smoother, more organic edge structure from an input image for ControlNet conditioning. It is useful when the goal is to preserve contours and layout without the harsh binary boundaries of Canny, especially for painterly, naturalistic, or softer illustration workflows.

ControlNet Preprocess SoftEdge
soft-edge-detection

Vintage Synthesizer Catalog Cleanup Guide

Vintage Synthesizer Catalog Cleanup Guide
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/ace1715c-d664-4c90-a40d-5f85043ae1d9.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/ace1715c-d664-4c90-a40d-5f85043ae1d9.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "ec1b33f6-a82c-4baa-aab8-bc6fe413477b",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/ace1715c-d664-4c90-a40d-5f85043ae1d9.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/ace1715c-d664-4c90-a40d-5f85043ae1d9.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "ec1b33f6-a82c-4baa-aab8-bc6fe413477b",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/ace1715c-d664-4c90-a40d-5f85043ae1d9.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "ec1b33f6-a82c-4baa-aab8-bc6fe413477b",
  "guideImageURL": "https://im.runware.ai/image/os/a02d21/ws/3/ii/ea785fb2-5f96-4568-ad64-9ce4ccbe282e.jpg",
  "cost": 0.0006,
  "guideImageUUID": "ea785fb2-5f96-4568-ad64-9ce4ccbe282e",
  "inputImageUUID": "5c29412d-16a6-4271-a066-a58c3e701eb3"
}
Edge Detection

Velvet Moth Specimen Arrangement

Velvet Moth Specimen Arrangement
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/e8a55df8-04d7-440c-90a2-f99b06625483.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/e8a55df8-04d7-440c-90a2-f99b06625483.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "cca67287-0cb0-49b9-806e-e758f6645c66",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/e8a55df8-04d7-440c-90a2-f99b06625483.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/e8a55df8-04d7-440c-90a2-f99b06625483.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "cca67287-0cb0-49b9-806e-e758f6645c66",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/e8a55df8-04d7-440c-90a2-f99b06625483.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "cca67287-0cb0-49b9-806e-e758f6645c66",
  "guideImageURL": "https://im.runware.ai/image/os/a07dlim3/ws/3/ii/8c797a2e-375c-43f3-8cdb-089ae8a10e6d.jpg",
  "cost": 0.0006,
  "guideImageUUID": "8c797a2e-375c-43f3-8cdb-089ae8a10e6d",
  "inputImageUUID": "3d45ba91-1772-405d-9f56-5a0af6bdfbee"
}
Preprocess

Moss Courtyard Cellist Silhouette

Moss Courtyard Cellist Silhouette
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/eed8f734-892d-47c4-82b9-e9b3b676ff38.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/eed8f734-892d-47c4-82b9-e9b3b676ff38.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "ad4b7a3f-04f5-4392-b64d-5c4ad16e3fd0",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/eed8f734-892d-47c4-82b9-e9b3b676ff38.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/eed8f734-892d-47c4-82b9-e9b3b676ff38.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "ad4b7a3f-04f5-4392-b64d-5c4ad16e3fd0",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/eed8f734-892d-47c4-82b9-e9b3b676ff38.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "ad4b7a3f-04f5-4392-b64d-5c4ad16e3fd0",
  "guideImageURL": "https://im.runware.ai/image/os/a09dlim3/ws/3/ii/953dc3c1-2b85-4306-805e-ef6b95477ba7.jpg",
  "cost": 0.0006,
  "guideImageUUID": "953dc3c1-2b85-4306-805e-ef6b95477ba7",
  "inputImageUUID": "d2039547-39f7-45b8-971e-8314a08dc974"
}
soft-edge-detection

Harbor Pilot Headshot Edge Guide

Harbor Pilot Headshot Edge Guide
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/8cb8d284-70d1-46a5-a682-d3a77e5dab97.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/8cb8d284-70d1-46a5-a682-d3a77e5dab97.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "4fb56e07-2c40-45a6-915e-eab905685abe",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/8cb8d284-70d1-46a5-a682-d3a77e5dab97.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/8cb8d284-70d1-46a5-a682-d3a77e5dab97.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "4fb56e07-2c40-45a6-915e-eab905685abe",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/8cb8d284-70d1-46a5-a682-d3a77e5dab97.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "4fb56e07-2c40-45a6-915e-eab905685abe",
  "guideImageURL": "https://im.runware.ai/image/os/a03d21/ws/3/ii/1dfe2475-5b56-43de-a76e-28937b0207ca.jpg",
  "cost": 0.0006,
  "guideImageUUID": "1dfe2475-5b56-43de-a76e-28937b0207ca",
  "inputImageUUID": "f6f5aece-4768-4fcc-93b3-745acb4663c3"
}
soft-edge-detection

Espresso Machine Colorway Edge Guide

Espresso Machine Colorway Edge Guide
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/a3cf5f9b-2d12-4da2-bb3e-7485a1d8b7f6.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/a3cf5f9b-2d12-4da2-bb3e-7485a1d8b7f6.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "9e73b552-47f4-4414-81d1-ab09b95d2ed1",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/a3cf5f9b-2d12-4da2-bb3e-7485a1d8b7f6.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/a3cf5f9b-2d12-4da2-bb3e-7485a1d8b7f6.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "9e73b552-47f4-4414-81d1-ab09b95d2ed1",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/a3cf5f9b-2d12-4da2-bb3e-7485a1d8b7f6.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "9e73b552-47f4-4414-81d1-ab09b95d2ed1",
  "guideImageURL": "https://im.runware.ai/image/os/a05d22/ws/3/ii/f7ff03b5-5c91-45ff-925a-068ea31714b7.jpg",
  "cost": 0.0006,
  "guideImageUUID": "f7ff03b5-5c91-45ff-925a-068ea31714b7",
  "inputImageUUID": "e1439521-25ae-4bdd-b077-884d8a8f099c"
}
Edge Detection

Origami Heron Paper Diorama

Origami Heron Paper Diorama
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/3031f736-ac70-4253-9846-6734cd480939.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/3031f736-ac70-4253-9846-6734cd480939.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "a3efddd2-d856-4fa6-b55d-1dd1fb326a9b",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/3031f736-ac70-4253-9846-6734cd480939.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/3031f736-ac70-4253-9846-6734cd480939.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "a3efddd2-d856-4fa6-b55d-1dd1fb326a9b",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/3031f736-ac70-4253-9846-6734cd480939.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "a3efddd2-d856-4fa6-b55d-1dd1fb326a9b",
  "guideImageURL": "https://im.runware.ai/image/os/a09dlim3/ws/3/ii/a0b55567-4442-4208-aef5-1bcd0e413983.jpg",
  "cost": 0.0006,
  "guideImageUUID": "a0b55567-4442-4208-aef5-1bcd0e413983",
  "inputImageUUID": "6701ab86-9aab-44ad-b540-34a1c463beb8"
}
soft-edge-detection

Alpine Tram Heritage Lithograph

Alpine Tram Heritage Lithograph
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/dac8c60e-bd4f-4c72-ae7a-84babd93fec9.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/dac8c60e-bd4f-4c72-ae7a-84babd93fec9.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "b21163c1-1628-431a-8a43-9a36797190bb",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/dac8c60e-bd4f-4c72-ae7a-84babd93fec9.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/dac8c60e-bd4f-4c72-ae7a-84babd93fec9.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "b21163c1-1628-431a-8a43-9a36797190bb",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/dac8c60e-bd4f-4c72-ae7a-84babd93fec9.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "b21163c1-1628-431a-8a43-9a36797190bb",
  "guideImageURL": "https://im.runware.ai/image/os/a01d21/ws/3/ii/dc15cc8d-f3c7-49d7-80f8-9761ccbfe949.jpg",
  "cost": 0.0006,
  "guideImageUUID": "dc15cc8d-f3c7-49d7-80f8-9761ccbfe949",
  "inputImageUUID": "0893e3c0-6da5-4b9f-9c8c-160c348b281c"
}
Edge Detection

Tidepool Shell Arrangement Study

Tidepool Shell Arrangement Study
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'runware:controlnet-preprocess@softedge',
  inputs: {
    image: 'https://assets.runware.ai/assets/inputs/d3f277b7-78af-469d-a609-8bfb927bc7d8.jpg'
  }
})
import asyncio
import os

from runware import Runware


async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "runware:controlnet-preprocess@softedge",
            "inputs": {
                "image": "https://assets.runware.ai/assets/inputs/d3f277b7-78af-469d-a609-8bfb927bc7d8.jpg"
            }
        })


asyncio.run(main())
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "controlNetPreprocess",
      "taskUUID": "7520ee24-f756-4686-a705-b9217ebadbf4",
      "model": "runware:controlnet-preprocess@softedge",
      "inputs": {
        "image": "https://assets.runware.ai/assets/inputs/d3f277b7-78af-469d-a609-8bfb927bc7d8.jpg"
      }
    }
  ]'
runware run runware:controlnet-preprocess@softedge \
  inputs.image=https://assets.runware.ai/assets/inputs/d3f277b7-78af-469d-a609-8bfb927bc7d8.jpg
{
  "taskType": "controlNetPreprocess",
  "taskUUID": "7520ee24-f756-4686-a705-b9217ebadbf4",
  "model": "runware:controlnet-preprocess@softedge",
  "inputs": {
    "image": "https://assets.runware.ai/assets/inputs/d3f277b7-78af-469d-a609-8bfb927bc7d8.jpg"
  }
}
Response
{
  "taskType": "imageControlNetPreProcess",
  "taskUUID": "7520ee24-f756-4686-a705-b9217ebadbf4",
  "guideImageURL": "https://im.runware.ai/image/os/a05d22/ws/3/ii/0999dbd7-ea93-4337-9f9c-f568abc97f08.jpg",
  "cost": 0.0006,
  "guideImageUUID": "0999dbd7-ea93-4337-9f9c-f568abc97f08",
  "inputImageUUID": "68b0f2c6-b0ee-42db-87bb-6602f9d686a1"
}