Qwen-Image-Layered

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'alibaba:qwen-image@layered',
  positivePrompt: 'Decompose the supplied museum preparation-lab photograph into coherent, independently editable RGBA layers while preserving the original composition, framing, scale, lighting, color, texture, and photographic appearance. Create a clean foreground layer for the complete Triceratops skull replica and its dark steel rolling mount, retaining every horn edge, opening, frill contour, support bar, wheel, and natural contact detail with accurate transparency and no halos. Separate the cast shadow beneath the mount where practical. Group the stainless-steel workbench, archival specimen crates, folded moving blanket, and rolling tool cart into logical midground layers. Preserve the pale-gray wall and sealed concrete floor as a continuous, complete background layer suitable for removal or replacement. Reconstruct any background areas hidden behind extracted objects so the background remains visually continuous when foreground and midground layers are disabled. Maintain exact alignment between all layers and avoid changing, redesigning, adding, or removing visible content.',
  inputs: {
    referenceImages: [
      'https://assets.runware.ai/assets/inputs/1eeaaf35-4b58-437b-9d2e-7620875d0c7f.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": "alibaba:qwen-image@layered",
            "positivePrompt": "Decompose the supplied museum preparation-lab photograph into coherent, independently editable RGBA layers while preserving the original composition, framing, scale, lighting, color, texture, and photographic appearance. Create a clean foreground layer for the complete Triceratops skull replica and its dark steel rolling mount, retaining every horn edge, opening, frill contour, support bar, wheel, and natural contact detail with accurate transparency and no halos. Separate the cast shadow beneath the mount where practical. Group the stainless-steel workbench, archival specimen crates, folded moving blanket, and rolling tool cart into logical midground layers. Preserve the pale-gray wall and sealed concrete floor as a continuous, complete background layer suitable for removal or replacement. Reconstruct any background areas hidden behind extracted objects so the background remains visually continuous when foreground and midground layers are disabled. Maintain exact alignment between all layers and avoid changing, redesigning, adding, or removing visible content.",
            "inputs": {
                "referenceImages": [
                    "https://assets.runware.ai/assets/inputs/1eeaaf35-4b58-437b-9d2e-7620875d0c7f.jpg"
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "imageInference",
      "taskUUID": "0d3a0b8c-1a6e-4faa-ab65-625b3346d896",
      "model": "alibaba:qwen-image@layered",
      "positivePrompt": "Decompose the supplied museum preparation-lab photograph into coherent, independently editable RGBA layers while preserving the original composition, framing, scale, lighting, color, texture, and photographic appearance. Create a clean foreground layer for the complete Triceratops skull replica and its dark steel rolling mount, retaining every horn edge, opening, frill contour, support bar, wheel, and natural contact detail with accurate transparency and no halos. Separate the cast shadow beneath the mount where practical. Group the stainless-steel workbench, archival specimen crates, folded moving blanket, and rolling tool cart into logical midground layers. Preserve the pale-gray wall and sealed concrete floor as a continuous, complete background layer suitable for removal or replacement. Reconstruct any background areas hidden behind extracted objects so the background remains visually continuous when foreground and midground layers are disabled. Maintain exact alignment between all layers and avoid changing, redesigning, adding, or removing visible content.",
      "inputs": {
        "referenceImages": [
          "https://assets.runware.ai/assets/inputs/1eeaaf35-4b58-437b-9d2e-7620875d0c7f.jpg"
        ]
      }
    }
  ]'

runware run alibaba:qwen-image@layered \
  positivePrompt="Decompose the supplied museum preparation-lab photograph into coherent, independently editable RGBA layers while preserving the original composition, framing, scale, lighting, color, texture, and photographic appearance. Create a clean foreground layer for the complete Triceratops skull replica and its dark steel rolling mount, retaining every horn edge, opening, frill contour, support bar, wheel, and natural contact detail with accurate transparency and no halos. Separate the cast shadow beneath the mount where practical. Group the stainless-steel workbench, archival specimen crates, folded moving blanket, and rolling tool cart into logical midground layers. Preserve the pale-gray wall and sealed concrete floor as a continuous, complete background layer suitable for removal or replacement. Reconstruct any background areas hidden behind extracted objects so the background remains visually continuous when foreground and midground layers are disabled. Maintain exact alignment between all layers and avoid changing, redesigning, adding, or removing visible content." \
  inputs.referenceImages.0=https://assets.runware.ai/assets/inputs/1eeaaf35-4b58-437b-9d2e-7620875d0c7f.jpg

{
  "taskType": "imageInference",
  "taskUUID": "0d3a0b8c-1a6e-4faa-ab65-625b3346d896",
  "model": "alibaba:qwen-image@layered",
  "positivePrompt": "Decompose the supplied museum preparation-lab photograph into coherent, independently editable RGBA layers while preserving the original composition, framing, scale, lighting, color, texture, and photographic appearance. Create a clean foreground layer for the complete Triceratops skull replica and its dark steel rolling mount, retaining every horn edge, opening, frill contour, support bar, wheel, and natural contact detail with accurate transparency and no halos. Separate the cast shadow beneath the mount where practical. Group the stainless-steel workbench, archival specimen crates, folded moving blanket, and rolling tool cart into logical midground layers. Preserve the pale-gray wall and sealed concrete floor as a continuous, complete background layer suitable for removal or replacement. Reconstruct any background areas hidden behind extracted objects so the background remains visually continuous when foreground and midground layers are disabled. Maintain exact alignment between all layers and avoid changing, redesigning, adding, or removing visible content.",
  "inputs": {
    "referenceImages": [
      "https://assets.runware.ai/assets/inputs/1eeaaf35-4b58-437b-9d2e-7620875d0c7f.jpg"
    ]
  }
}

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'alibaba:qwen-image@layered',
  positivePrompt: 'Transform the supplied rooftop beekeeping photograph into a polished mid-century civic screenprint illustration for the cover of an urban agriculture annual report. Preserve the original vertical composition, camera angle, subject identity, pose, honey-frame details, hive placement, planters, skyline silhouette, lighting direction, and spatial depth. Use bold hand-cut shapes, subtle imperfect ink registration, restrained paper grain, simplified dimensional shading, and a sophisticated limited palette of honey gold, deep petrol blue, warm cream, brick red, and charcoal. Keep the mood practical, optimistic, and documentary rather than whimsical. No lettering, logos, border, or added objects. Decompose the finished image into coherent, independently editable RGBA layers while maintaining a seamless match when composited: isolate the foreground beekeeper and honey frame with clean transparent edges; separate the midground hive boxes; separate the rooftop planters and vegetation; retain the city skyline and sky as a continuous full-frame background; preserve natural occlusion, edge detail, shadows, and visual continuity between every layer.',
  inputs: {
    referenceImages: [
      'https://assets.runware.ai/assets/inputs/02f7285a-412b-4c35-961f-ed1ae626afaf.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": "alibaba:qwen-image@layered",
            "positivePrompt": "Transform the supplied rooftop beekeeping photograph into a polished mid-century civic screenprint illustration for the cover of an urban agriculture annual report. Preserve the original vertical composition, camera angle, subject identity, pose, honey-frame details, hive placement, planters, skyline silhouette, lighting direction, and spatial depth. Use bold hand-cut shapes, subtle imperfect ink registration, restrained paper grain, simplified dimensional shading, and a sophisticated limited palette of honey gold, deep petrol blue, warm cream, brick red, and charcoal. Keep the mood practical, optimistic, and documentary rather than whimsical. No lettering, logos, border, or added objects. Decompose the finished image into coherent, independently editable RGBA layers while maintaining a seamless match when composited: isolate the foreground beekeeper and honey frame with clean transparent edges; separate the midground hive boxes; separate the rooftop planters and vegetation; retain the city skyline and sky as a continuous full-frame background; preserve natural occlusion, edge detail, shadows, and visual continuity between every layer.",
            "inputs": {
                "referenceImages": [
                    "https://assets.runware.ai/assets/inputs/02f7285a-412b-4c35-961f-ed1ae626afaf.jpg"
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "imageInference",
      "taskUUID": "ccccd4e9-467c-4143-8b6a-9f5993dddff1",
      "model": "alibaba:qwen-image@layered",
      "positivePrompt": "Transform the supplied rooftop beekeeping photograph into a polished mid-century civic screenprint illustration for the cover of an urban agriculture annual report. Preserve the original vertical composition, camera angle, subject identity, pose, honey-frame details, hive placement, planters, skyline silhouette, lighting direction, and spatial depth. Use bold hand-cut shapes, subtle imperfect ink registration, restrained paper grain, simplified dimensional shading, and a sophisticated limited palette of honey gold, deep petrol blue, warm cream, brick red, and charcoal. Keep the mood practical, optimistic, and documentary rather than whimsical. No lettering, logos, border, or added objects. Decompose the finished image into coherent, independently editable RGBA layers while maintaining a seamless match when composited: isolate the foreground beekeeper and honey frame with clean transparent edges; separate the midground hive boxes; separate the rooftop planters and vegetation; retain the city skyline and sky as a continuous full-frame background; preserve natural occlusion, edge detail, shadows, and visual continuity between every layer.",
      "inputs": {
        "referenceImages": [
          "https://assets.runware.ai/assets/inputs/02f7285a-412b-4c35-961f-ed1ae626afaf.jpg"
        ]
      }
    }
  ]'

runware run alibaba:qwen-image@layered \
  positivePrompt="Transform the supplied rooftop beekeeping photograph into a polished mid-century civic screenprint illustration for the cover of an urban agriculture annual report. Preserve the original vertical composition, camera angle, subject identity, pose, honey-frame details, hive placement, planters, skyline silhouette, lighting direction, and spatial depth. Use bold hand-cut shapes, subtle imperfect ink registration, restrained paper grain, simplified dimensional shading, and a sophisticated limited palette of honey gold, deep petrol blue, warm cream, brick red, and charcoal. Keep the mood practical, optimistic, and documentary rather than whimsical. No lettering, logos, border, or added objects. Decompose the finished image into coherent, independently editable RGBA layers while maintaining a seamless match when composited: isolate the foreground beekeeper and honey frame with clean transparent edges; separate the midground hive boxes; separate the rooftop planters and vegetation; retain the city skyline and sky as a continuous full-frame background; preserve natural occlusion, edge detail, shadows, and visual continuity between every layer." \
  inputs.referenceImages.0=https://assets.runware.ai/assets/inputs/02f7285a-412b-4c35-961f-ed1ae626afaf.jpg

{
  "taskType": "imageInference",
  "taskUUID": "ccccd4e9-467c-4143-8b6a-9f5993dddff1",
  "model": "alibaba:qwen-image@layered",
  "positivePrompt": "Transform the supplied rooftop beekeeping photograph into a polished mid-century civic screenprint illustration for the cover of an urban agriculture annual report. Preserve the original vertical composition, camera angle, subject identity, pose, honey-frame details, hive placement, planters, skyline silhouette, lighting direction, and spatial depth. Use bold hand-cut shapes, subtle imperfect ink registration, restrained paper grain, simplified dimensional shading, and a sophisticated limited palette of honey gold, deep petrol blue, warm cream, brick red, and charcoal. Keep the mood practical, optimistic, and documentary rather than whimsical. No lettering, logos, border, or added objects. Decompose the finished image into coherent, independently editable RGBA layers while maintaining a seamless match when composited: isolate the foreground beekeeper and honey frame with clean transparent edges; separate the midground hive boxes; separate the rooftop planters and vegetation; retain the city skyline and sky as a continuous full-frame background; preserve natural occlusion, edge detail, shadows, and visual continuity between every layer.",
  "inputs": {
    "referenceImages": [
      "https://assets.runware.ai/assets/inputs/02f7285a-412b-4c35-961f-ed1ae626afaf.jpg"
    ]
  }
}

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'alibaba:qwen-image@layered',
  positivePrompt: 'Decompose the supplied observatory photograph into coherent, independently editable RGBA layers while preserving the original composition, camera perspective, lighting, color, texture, shadows, reflections, and photorealistic appearance when all layers are visible. Place the orange rolling maintenance ladder and its attached black power cable on a dedicated foreground removal layer with precise edges, wheel details, openings between the ladder rails, natural contact shadows, and clean transparency. Reconstruct a continuous clean-plate base beneath and behind that equipment, generatively filling the obscured pale speckled terrazzo floor, grout lines, subtle reflections, and adjacent architectural surfaces so the ladder and cable can be hidden without a visible patch. Separate the historic brass-and-cream refracting telescope and pedestal as the principal midground layer. Keep the circular railing and dark green equipment cabinets on distinct midground layers where practical. Preserve the curved ribbed plaster dome, open viewing slit, dusk sky, and uninterrupted architectural illumination as the continuous background layer. Retain all fine mechanical detail and ensure clean alpha boundaries without halos, duplicated edges, missing geometry, or unintended changes to the scene.',
  inputs: {
    referenceImages: [
      'https://assets.runware.ai/assets/inputs/d616c40d-1313-4d3e-a387-6f48cde878c0.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": "alibaba:qwen-image@layered",
            "positivePrompt": "Decompose the supplied observatory photograph into coherent, independently editable RGBA layers while preserving the original composition, camera perspective, lighting, color, texture, shadows, reflections, and photorealistic appearance when all layers are visible. Place the orange rolling maintenance ladder and its attached black power cable on a dedicated foreground removal layer with precise edges, wheel details, openings between the ladder rails, natural contact shadows, and clean transparency. Reconstruct a continuous clean-plate base beneath and behind that equipment, generatively filling the obscured pale speckled terrazzo floor, grout lines, subtle reflections, and adjacent architectural surfaces so the ladder and cable can be hidden without a visible patch. Separate the historic brass-and-cream refracting telescope and pedestal as the principal midground layer. Keep the circular railing and dark green equipment cabinets on distinct midground layers where practical. Preserve the curved ribbed plaster dome, open viewing slit, dusk sky, and uninterrupted architectural illumination as the continuous background layer. Retain all fine mechanical detail and ensure clean alpha boundaries without halos, duplicated edges, missing geometry, or unintended changes to the scene.",
            "inputs": {
                "referenceImages": [
                    "https://assets.runware.ai/assets/inputs/d616c40d-1313-4d3e-a387-6f48cde878c0.jpg"
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "imageInference",
      "taskUUID": "2ccb991c-ddb8-426e-aad0-cb3a81f67b68",
      "model": "alibaba:qwen-image@layered",
      "positivePrompt": "Decompose the supplied observatory photograph into coherent, independently editable RGBA layers while preserving the original composition, camera perspective, lighting, color, texture, shadows, reflections, and photorealistic appearance when all layers are visible. Place the orange rolling maintenance ladder and its attached black power cable on a dedicated foreground removal layer with precise edges, wheel details, openings between the ladder rails, natural contact shadows, and clean transparency. Reconstruct a continuous clean-plate base beneath and behind that equipment, generatively filling the obscured pale speckled terrazzo floor, grout lines, subtle reflections, and adjacent architectural surfaces so the ladder and cable can be hidden without a visible patch. Separate the historic brass-and-cream refracting telescope and pedestal as the principal midground layer. Keep the circular railing and dark green equipment cabinets on distinct midground layers where practical. Preserve the curved ribbed plaster dome, open viewing slit, dusk sky, and uninterrupted architectural illumination as the continuous background layer. Retain all fine mechanical detail and ensure clean alpha boundaries without halos, duplicated edges, missing geometry, or unintended changes to the scene.",
      "inputs": {
        "referenceImages": [
          "https://assets.runware.ai/assets/inputs/d616c40d-1313-4d3e-a387-6f48cde878c0.jpg"
        ]
      }
    }
  ]'

runware run alibaba:qwen-image@layered \
  positivePrompt="Decompose the supplied observatory photograph into coherent, independently editable RGBA layers while preserving the original composition, camera perspective, lighting, color, texture, shadows, reflections, and photorealistic appearance when all layers are visible. Place the orange rolling maintenance ladder and its attached black power cable on a dedicated foreground removal layer with precise edges, wheel details, openings between the ladder rails, natural contact shadows, and clean transparency. Reconstruct a continuous clean-plate base beneath and behind that equipment, generatively filling the obscured pale speckled terrazzo floor, grout lines, subtle reflections, and adjacent architectural surfaces so the ladder and cable can be hidden without a visible patch. Separate the historic brass-and-cream refracting telescope and pedestal as the principal midground layer. Keep the circular railing and dark green equipment cabinets on distinct midground layers where practical. Preserve the curved ribbed plaster dome, open viewing slit, dusk sky, and uninterrupted architectural illumination as the continuous background layer. Retain all fine mechanical detail and ensure clean alpha boundaries without halos, duplicated edges, missing geometry, or unintended changes to the scene." \
  inputs.referenceImages.0=https://assets.runware.ai/assets/inputs/d616c40d-1313-4d3e-a387-6f48cde878c0.jpg

{
  "taskType": "imageInference",
  "taskUUID": "2ccb991c-ddb8-426e-aad0-cb3a81f67b68",
  "model": "alibaba:qwen-image@layered",
  "positivePrompt": "Decompose the supplied observatory photograph into coherent, independently editable RGBA layers while preserving the original composition, camera perspective, lighting, color, texture, shadows, reflections, and photorealistic appearance when all layers are visible. Place the orange rolling maintenance ladder and its attached black power cable on a dedicated foreground removal layer with precise edges, wheel details, openings between the ladder rails, natural contact shadows, and clean transparency. Reconstruct a continuous clean-plate base beneath and behind that equipment, generatively filling the obscured pale speckled terrazzo floor, grout lines, subtle reflections, and adjacent architectural surfaces so the ladder and cable can be hidden without a visible patch. Separate the historic brass-and-cream refracting telescope and pedestal as the principal midground layer. Keep the circular railing and dark green equipment cabinets on distinct midground layers where practical. Preserve the curved ribbed plaster dome, open viewing slit, dusk sky, and uninterrupted architectural illumination as the continuous background layer. Retain all fine mechanical detail and ensure clean alpha boundaries without halos, duplicated edges, missing geometry, or unintended changes to the scene.",
  "inputs": {
    "referenceImages": [
      "https://assets.runware.ai/assets/inputs/d616c40d-1313-4d3e-a387-6f48cde878c0.jpg"
    ]
  }
}

import { createClient } from '@runware/sdk'

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

const [result] = await client.run({
  model: 'alibaba:qwen-image@layered',
  positivePrompt: 'Decompose the supplied heritage railway crew portrait into coherent, independently editable RGBA layers while preserving the source image\'s exact composition, people, facial appearance, clothing, lighting, color palette, perspective, texture, and photographic realism. Isolate the seated retired chief engineer in the foreground as a clean standalone subject layer with precise boundaries around his hair, burgundy neckerchief, navy coveralls, hands, boots, toolbox, and natural contact shadows so he can be removed or repositioned without affecting anyone else. Separate the standing restoration crew in the midground into logically editable person layers wherever their silhouettes permit, preserving all overlaps and depth order. Place the steam locomotive and workshop props on distinct midground layers. Create a continuous engine-shed background layer containing the brick wall, floor, structural details, pendant lights, and plausible clean reconstruction behind foreground and midground subjects, enabling the seated engineer to be removed cleanly. Retain natural edge softness, fine fabric detail, reflections, ambient shadows, and transparent antialiased boundaries. The layered result must visually match the supplied photograph when all layers are composited.',
  inputs: {
    referenceImages: [
      'https://assets.runware.ai/assets/inputs/02c3191c-9d79-4d2d-a3d7-40e33bf77f2a.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": "alibaba:qwen-image@layered",
            "positivePrompt": "Decompose the supplied heritage railway crew portrait into coherent, independently editable RGBA layers while preserving the source image's exact composition, people, facial appearance, clothing, lighting, color palette, perspective, texture, and photographic realism. Isolate the seated retired chief engineer in the foreground as a clean standalone subject layer with precise boundaries around his hair, burgundy neckerchief, navy coveralls, hands, boots, toolbox, and natural contact shadows so he can be removed or repositioned without affecting anyone else. Separate the standing restoration crew in the midground into logically editable person layers wherever their silhouettes permit, preserving all overlaps and depth order. Place the steam locomotive and workshop props on distinct midground layers. Create a continuous engine-shed background layer containing the brick wall, floor, structural details, pendant lights, and plausible clean reconstruction behind foreground and midground subjects, enabling the seated engineer to be removed cleanly. Retain natural edge softness, fine fabric detail, reflections, ambient shadows, and transparent antialiased boundaries. The layered result must visually match the supplied photograph when all layers are composited.",
            "inputs": {
                "referenceImages": [
                    "https://assets.runware.ai/assets/inputs/02c3191c-9d79-4d2d-a3d7-40e33bf77f2a.jpg"
                ]
            }
        })


asyncio.run(main())

curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "imageInference",
      "taskUUID": "08708418-6947-499e-8c2e-9b82b0d71a25",
      "model": "alibaba:qwen-image@layered",
      "positivePrompt": "Decompose the supplied heritage railway crew portrait into coherent, independently editable RGBA layers while preserving the source image's exact composition, people, facial appearance, clothing, lighting, color palette, perspective, texture, and photographic realism. Isolate the seated retired chief engineer in the foreground as a clean standalone subject layer with precise boundaries around his hair, burgundy neckerchief, navy coveralls, hands, boots, toolbox, and natural contact shadows so he can be removed or repositioned without affecting anyone else. Separate the standing restoration crew in the midground into logically editable person layers wherever their silhouettes permit, preserving all overlaps and depth order. Place the steam locomotive and workshop props on distinct midground layers. Create a continuous engine-shed background layer containing the brick wall, floor, structural details, pendant lights, and plausible clean reconstruction behind foreground and midground subjects, enabling the seated engineer to be removed cleanly. Retain natural edge softness, fine fabric detail, reflections, ambient shadows, and transparent antialiased boundaries. The layered result must visually match the supplied photograph when all layers are composited.",
      "inputs": {
        "referenceImages": [
          "https://assets.runware.ai/assets/inputs/02c3191c-9d79-4d2d-a3d7-40e33bf77f2a.jpg"
        ]
      }
    }
  ]'

runware run alibaba:qwen-image@layered \
  positivePrompt="Decompose the supplied heritage railway crew portrait into coherent, independently editable RGBA layers while preserving the source image's exact composition, people, facial appearance, clothing, lighting, color palette, perspective, texture, and photographic realism. Isolate the seated retired chief engineer in the foreground as a clean standalone subject layer with precise boundaries around his hair, burgundy neckerchief, navy coveralls, hands, boots, toolbox, and natural contact shadows so he can be removed or repositioned without affecting anyone else. Separate the standing restoration crew in the midground into logically editable person layers wherever their silhouettes permit, preserving all overlaps and depth order. Place the steam locomotive and workshop props on distinct midground layers. Create a continuous engine-shed background layer containing the brick wall, floor, structural details, pendant lights, and plausible clean reconstruction behind foreground and midground subjects, enabling the seated engineer to be removed cleanly. Retain natural edge softness, fine fabric detail, reflections, ambient shadows, and transparent antialiased boundaries. The layered result must visually match the supplied photograph when all layers are composited." \
  inputs.referenceImages.0=https://assets.runware.ai/assets/inputs/02c3191c-9d79-4d2d-a3d7-40e33bf77f2a.jpg

{
  "taskType": "imageInference",
  "taskUUID": "08708418-6947-499e-8c2e-9b82b0d71a25",
  "model": "alibaba:qwen-image@layered",
  "positivePrompt": "Decompose the supplied heritage railway crew portrait into coherent, independently editable RGBA layers while preserving the source image's exact composition, people, facial appearance, clothing, lighting, color palette, perspective, texture, and photographic realism. Isolate the seated retired chief engineer in the foreground as a clean standalone subject layer with precise boundaries around his hair, burgundy neckerchief, navy coveralls, hands, boots, toolbox, and natural contact shadows so he can be removed or repositioned without affecting anyone else. Separate the standing restoration crew in the midground into logically editable person layers wherever their silhouettes permit, preserving all overlaps and depth order. Place the steam locomotive and workshop props on distinct midground layers. Create a continuous engine-shed background layer containing the brick wall, floor, structural details, pendant lights, and plausible clean reconstruction behind foreground and midground subjects, enabling the seated engineer to be removed cleanly. Retain natural edge softness, fine fabric detail, reflections, ambient shadows, and transparent antialiased boundaries. The layered result must visually match the supplied photograph when all layers are composited.",
  "inputs": {
    "referenceImages": [
      "https://assets.runware.ai/assets/inputs/02c3191c-9d79-4d2d-a3d7-40e33bf77f2a.jpg"
    ]
  }
}