MediaPipe Eyes Mesh
MediaPipe Eyes Mesh is an image masking model specialized for generating black-and-white masks over the eye regions using MediaPipe facial landmarks. It is suited to selective edits, makeup-style retouching, and targeted eye-area enhancement workflows.
Train Platform Commuter Glance
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:35@15',
settings: {
confidence: 0.65,
maxDetections: 1,
maskPadding: 14,
maskBlur: 6
},
inputs: {
image: 'https://assets.runware.ai/assets/inputs/9fbd1d08-50d0-422c-baab-58e56b5a09d9.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:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 14,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/9fbd1d08-50d0-422c-baab-58e56b5a09d9.jpg"
}
})
asyncio.run(main())curl https://api.runware.ai/v1 \
-H "Authorization: Bearer $RUNWARE_API_KEY" \
-H "Content-Type: application/json" \
-d '[
{
"taskType": "imageMasking",
"taskUUID": "f3b8d562-d663-4fe9-b538-8f7f59df7712",
"model": "runware:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 14,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/9fbd1d08-50d0-422c-baab-58e56b5a09d9.jpg"
}
}
]'runware run runware:35@15 \
settings.confidence=0.65 \
settings.maxDetections=1 \
settings.maskPadding=14 \
settings.maskBlur=6 \
inputs.image=https://assets.runware.ai/assets/inputs/9fbd1d08-50d0-422c-baab-58e56b5a09d9.jpg{
"taskType": "imageMasking",
"taskUUID": "f3b8d562-d663-4fe9-b538-8f7f59df7712",
"model": "runware:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 14,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/9fbd1d08-50d0-422c-baab-58e56b5a09d9.jpg"
}
}{
"taskType": "imageMasking",
"taskUUID": "f3b8d562-d663-4fe9-b538-8f7f59df7712",
"maskImageURL": "https://im.runware.ai/image/os/a08dlim3/ws/4/ii/ecaa7f97-cbc4-4346-88ea-3b74fd3585c5.jpg",
"detections": [
{
"index": 154,
"coordinates": [
494,
379
]
},
{
"index": 155,
"coordinates": [
496,
379
]
},
{
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"coordinates": [
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]
},
{
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]
},
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]
},
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]
},
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]
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]
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]
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]
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]
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]
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{
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]
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{
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]
},
{
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"coordinates": [
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]
},
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]
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]
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]
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{
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"coordinates": [
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]
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{
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]
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]
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]
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]
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"coordinates": [
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]
},
{
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"coordinates": [
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]
},
{
"index": 159,
"coordinates": [
490,
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]
},
{
"index": 466,
"coordinates": [
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]
},
{
"index": 388,
"coordinates": [
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]
},
{
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"coordinates": [
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]
},
{
"index": 295,
"coordinates": [
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]
},
{
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"coordinates": [
520,
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]
},
{
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"coordinates": [
517,
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]
}
],
"cost": 0.0006,
"maskImageUUID": "ecaa7f97-cbc4-4346-88ea-3b74fd3585c5"
}Bakery Counter Morning Shift
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:35@15',
settings: {
confidence: 0.65,
maxDetections: 1,
maskPadding: 18,
maskBlur: 8
},
inputs: {
image: 'https://assets.runware.ai/assets/inputs/f68f9cbe-6511-4295-8d90-e1135625f509.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:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 18,
"maskBlur": 8
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/f68f9cbe-6511-4295-8d90-e1135625f509.jpg"
}
})
asyncio.run(main())curl https://api.runware.ai/v1 \
-H "Authorization: Bearer $RUNWARE_API_KEY" \
-H "Content-Type: application/json" \
-d '[
{
"taskType": "imageMasking",
"taskUUID": "123e1bd7-0d90-429b-9e15-a76f06dcfb17",
"model": "runware:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 18,
"maskBlur": 8
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/f68f9cbe-6511-4295-8d90-e1135625f509.jpg"
}
}
]'runware run runware:35@15 \
settings.confidence=0.65 \
settings.maxDetections=1 \
settings.maskPadding=18 \
settings.maskBlur=8 \
inputs.image=https://assets.runware.ai/assets/inputs/f68f9cbe-6511-4295-8d90-e1135625f509.jpg{
"taskType": "imageMasking",
"taskUUID": "123e1bd7-0d90-429b-9e15-a76f06dcfb17",
"model": "runware:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 18,
"maskBlur": 8
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/f68f9cbe-6511-4295-8d90-e1135625f509.jpg"
}
}{
"taskType": "imageMasking",
"taskUUID": "123e1bd7-0d90-429b-9e15-a76f06dcfb17",
"maskImageURL": "https://im.runware.ai/image/os/a10dlim3/ws/4/ii/e382f497-9f8a-4c4f-868b-35efda3bd9a8.jpg",
"cost": 0.0013,
"maskImageUUID": "e382f497-9f8a-4c4f-868b-35efda3bd9a8"
}Candid Paramedic Equipment Check
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:35@15',
settings: {
confidence: 0.5,
maxDetections: 1,
maskPadding: 14,
maskBlur: 6
},
inputs: {
image: 'https://assets.runware.ai/assets/inputs/19e22b6f-b549-4e88-9dae-8d4047b3b8ad.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:35@15",
"settings": {
"confidence": 0.5,
"maxDetections": 1,
"maskPadding": 14,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/19e22b6f-b549-4e88-9dae-8d4047b3b8ad.jpg"
}
})
asyncio.run(main())curl https://api.runware.ai/v1 \
-H "Authorization: Bearer $RUNWARE_API_KEY" \
-H "Content-Type: application/json" \
-d '[
{
"taskType": "imageMasking",
"taskUUID": "b544fd8f-01ad-49a4-8c42-29bba28389af",
"model": "runware:35@15",
"settings": {
"confidence": 0.5,
"maxDetections": 1,
"maskPadding": 14,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/19e22b6f-b549-4e88-9dae-8d4047b3b8ad.jpg"
}
}
]'runware run runware:35@15 \
settings.confidence=0.5 \
settings.maxDetections=1 \
settings.maskPadding=14 \
settings.maskBlur=6 \
inputs.image=https://assets.runware.ai/assets/inputs/19e22b6f-b549-4e88-9dae-8d4047b3b8ad.jpg{
"taskType": "imageMasking",
"taskUUID": "b544fd8f-01ad-49a4-8c42-29bba28389af",
"model": "runware:35@15",
"settings": {
"confidence": 0.5,
"maxDetections": 1,
"maskPadding": 14,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/19e22b6f-b549-4e88-9dae-8d4047b3b8ad.jpg"
}
}{
"taskType": "imageMasking",
"taskUUID": "b544fd8f-01ad-49a4-8c42-29bba28389af",
"maskImageURL": "https://im.runware.ai/image/os/a06dlim3/ws/4/ii/663a85d9-6bad-417c-aa7c-918bdc560fb5.jpg",
"detections": [
{
"index": 154,
"coordinates": [
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]
},
{
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"coordinates": [
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]
},
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]
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]
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]
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]
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]
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],
"cost": 0.0006,
"maskImageUUID": "663a85d9-6bad-417c-aa7c-918bdc560fb5"
}Bouldering Wall Chalk Break
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:35@15',
settings: {
confidence: 0.65,
maxDetections: 1,
maskPadding: 12,
maskBlur: 6
},
inputs: {
image: 'https://assets.runware.ai/assets/inputs/0dacaced-12f4-479b-ba5c-a762670b5cea.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:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 12,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/0dacaced-12f4-479b-ba5c-a762670b5cea.jpg"
}
})
asyncio.run(main())curl https://api.runware.ai/v1 \
-H "Authorization: Bearer $RUNWARE_API_KEY" \
-H "Content-Type: application/json" \
-d '[
{
"taskType": "imageMasking",
"taskUUID": "c6f85a64-0b50-4b66-8248-cf7358136387",
"model": "runware:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 12,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/0dacaced-12f4-479b-ba5c-a762670b5cea.jpg"
}
}
]'runware run runware:35@15 \
settings.confidence=0.65 \
settings.maxDetections=1 \
settings.maskPadding=12 \
settings.maskBlur=6 \
inputs.image=https://assets.runware.ai/assets/inputs/0dacaced-12f4-479b-ba5c-a762670b5cea.jpg{
"taskType": "imageMasking",
"taskUUID": "c6f85a64-0b50-4b66-8248-cf7358136387",
"model": "runware:35@15",
"settings": {
"confidence": 0.65,
"maxDetections": 1,
"maskPadding": 12,
"maskBlur": 6
},
"inputs": {
"image": "https://assets.runware.ai/assets/inputs/0dacaced-12f4-479b-ba5c-a762670b5cea.jpg"
}
}{
"taskType": "imageMasking",
"taskUUID": "c6f85a64-0b50-4b66-8248-cf7358136387",
"maskImageURL": "https://im.runware.ai/image/os/a08dlim3/ws/4/ii/4d8ef410-29bd-4a24-b5f2-1533311ba51d.jpg",
"detections": [
{
"index": 154,
"coordinates": [
627,
212
]
},
{
"index": 155,
"coordinates": [
630,
211
]
},
{
"index": 334,
"coordinates": [
671,
185
]
},
{
"index": 296,
"coordinates": [
661,
186
]
},
{
"index": 293,
"coordinates": [
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186
]
},
{
"index": 334,
"coordinates": [
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185
]
},
{
"index": 386,
"coordinates": [
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]
},
{
"index": 385,
"coordinates": [
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]
},
{
"index": 7,
"coordinates": [
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]
},
{
"index": 163,
"coordinates": [
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]
},
{
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"coordinates": [
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]
},
{
"index": 336,
"coordinates": [
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]
},
{
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"coordinates": [
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]
},
{
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]
},
{
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]
},
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]
},
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]
},
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]
},
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]
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]
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"coordinates": [
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"coordinates": [
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]
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]
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]
},
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]
},
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]
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]
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]
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]
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]
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]
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]
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]
},
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]
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]
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]
},
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]
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]
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]
},
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]
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]
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]
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]
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]
}
],
"cost": 0.0006,
"maskImageUUID": "4d8ef410-29bd-4a24-b5f2-1533311ba51d"
}