Prediction

ID

fpqg4uiaizgrnc2z4lkub6iyce

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago by @chenxwh

Input

task: Face Restoration
image
broken_image
output_individual

{
  "task": "Face Restoration",
  "image": "https://replicate.delivery/mgxm/9e77a2c1-3448-487e-8899-1843a52a70e2/Solvay_conference_1927.png",
  "broken_image": true,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
  {
    input: {
      task: "Face Restoration",
      image: "https://replicate.delivery/mgxm/9e77a2c1-3448-487e-8899-1843a52a70e2/Solvay_conference_1927.png",
      broken_image: true,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    input={
        "task": "Face Restoration",
        "image": "https://replicate.delivery/mgxm/9e77a2c1-3448-487e-8899-1843a52a70e2/Solvay_conference_1927.png",
        "broken_image": True,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    "input": {
      "task": "Face Restoration",
      "image": "https://replicate.delivery/mgxm/9e77a2c1-3448-487e-8899-1843a52a70e2/Solvay_conference_1927.png",
      "broken_image": true,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf

Prediction

Model

ID

svbqg5vktzgahjhzal5x7bkwku

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago

Input

task: Face Restoration
image
broken_image
output_individual

{
  "task": "Face Restoration",
  "image": "https://replicate.delivery/mgxm/09e67425-bf5b-4a65-ad8d-9e6992add341/Solvay_conference_1927.png",
  "broken_image": true,
  "output_individual": true
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
  {
    input: {
      task: "Face Restoration",
      image: "https://replicate.delivery/mgxm/09e67425-bf5b-4a65-ad8d-9e6992add341/Solvay_conference_1927.png",
      broken_image: true,
      output_individual: true
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    input={
        "task": "Face Restoration",
        "image": "https://replicate.delivery/mgxm/09e67425-bf5b-4a65-ad8d-9e6992add341/Solvay_conference_1927.png",
        "broken_image": True,
        "output_individual": True
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    "input": {
      "task": "Face Restoration",
      "image": "https://replicate.delivery/mgxm/09e67425-bf5b-4a65-ad8d-9e6992add341/Solvay_conference_1927.png",
      "broken_image": true,
      "output_individual": true
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

out.zip

yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf

Prediction

Model

ID

tzyggq3t55gkbai3stsbovb56e

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago by @chenxwh

Input

task: Face Colorization
image
broken_image
output_individual

{
  "task": "Face Colorization",
  "image": "https://replicate.delivery/mgxm/2accac52-d86d-4829-9148-2ca42e65a4ba/762000_gray.png",
  "broken_image": false,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
  {
    input: {
      task: "Face Colorization",
      image: "https://replicate.delivery/mgxm/2accac52-d86d-4829-9148-2ca42e65a4ba/762000_gray.png",
      broken_image: false,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    input={
        "task": "Face Colorization",
        "image": "https://replicate.delivery/mgxm/2accac52-d86d-4829-9148-2ca42e65a4ba/762000_gray.png",
        "broken_image": False,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    "input": {
      "task": "Face Colorization",
      "image": "https://replicate.delivery/mgxm/2accac52-d86d-4829-9148-2ca42e65a4ba/762000_gray.png",
      "broken_image": false,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf

Prediction

Model

ID

cts52g2adzh65g7jalmqae6z6e

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago by @chenxwh

Input

task: Face Colorization
image
broken_image
output_individual

{
  "task": "Face Colorization",
  "image": "https://replicate.delivery/mgxm/158dc779-aa50-4d69-8c6d-cf58665e899e/106000_gray.png",
  "broken_image": false,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
  {
    input: {
      task: "Face Colorization",
      image: "https://replicate.delivery/mgxm/158dc779-aa50-4d69-8c6d-cf58665e899e/106000_gray.png",
      broken_image: false,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    input={
        "task": "Face Colorization",
        "image": "https://replicate.delivery/mgxm/158dc779-aa50-4d69-8c6d-cf58665e899e/106000_gray.png",
        "broken_image": False,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    "input": {
      "task": "Face Colorization",
      "image": "https://replicate.delivery/mgxm/158dc779-aa50-4d69-8c6d-cf58665e899e/106000_gray.png",
      "broken_image": false,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf

Prediction

Model

ID

6vxcqd4fcbhlzf5arlogmk2wji

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago

Input

task: Face Colorization
image
broken_image
output_individual

{
  "task": "Face Colorization",
  "image": "https://replicate.delivery/mgxm/1c2ea4ae-0591-49ee-a023-9102153133f3/813000_gray.png",
  "broken_image": false,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
  {
    input: {
      task: "Face Colorization",
      image: "https://replicate.delivery/mgxm/1c2ea4ae-0591-49ee-a023-9102153133f3/813000_gray.png",
      broken_image: false,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    input={
        "task": "Face Colorization",
        "image": "https://replicate.delivery/mgxm/1c2ea4ae-0591-49ee-a023-9102153133f3/813000_gray.png",
        "broken_image": False,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    "input": {
      "task": "Face Colorization",
      "image": "https://replicate.delivery/mgxm/1c2ea4ae-0591-49ee-a023-9102153133f3/813000_gray.png",
      "broken_image": false,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf

Prediction

Model

ID

iarjnjg2cndexceon2wun25ctm

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago by @chenxwh

Input

task: Face Inpainting
image
broken_image
output_individual

{
  "task": "Face Inpainting",
  "image": "https://replicate.delivery/mgxm/96da59c8-f922-4ead-9857-05b58a13954b/b1.png",
  "broken_image": true,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
  {
    input: {
      task: "Face Inpainting",
      image: "https://replicate.delivery/mgxm/96da59c8-f922-4ead-9857-05b58a13954b/b1.png",
      broken_image: true,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    input={
        "task": "Face Inpainting",
        "image": "https://replicate.delivery/mgxm/96da59c8-f922-4ead-9857-05b58a13954b/b1.png",
        "broken_image": True,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2210792a20342fd95fdc39dd96a9502ea588fd8f873019e24aee7363a70a6adf",
    "input": {
      "task": "Face Inpainting",
      "image": "https://replicate.delivery/mgxm/96da59c8-f922-4ead-9857-05b58a13954b/b1.png",
      "broken_image": true,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69

Prediction

Model

ID

g7u2vfyrprgsfntbnfiq6ee2ki

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago

Input

task: Face Inpainting
image
broken_image
output_individual

{
  "task": "Face Inpainting",
  "image": "https://replicate.delivery/mgxm/efccce70-ec47-4ae1-bb49-c4059ca36537/00001.png",
  "broken_image": false,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
  {
    input: {
      task: "Face Inpainting",
      image: "https://replicate.delivery/mgxm/efccce70-ec47-4ae1-bb49-c4059ca36537/00001.png",
      broken_image: false,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    input={
        "task": "Face Inpainting",
        "image": "https://replicate.delivery/mgxm/efccce70-ec47-4ae1-bb49-c4059ca36537/00001.png",
        "broken_image": False,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    "input": {
      "task": "Face Inpainting",
      "image": "https://replicate.delivery/mgxm/efccce70-ec47-4ae1-bb49-c4059ca36537/00001.png",
      "broken_image": false,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69

Prediction

Model

ID

v73dkux5orgspn46hikibrpy4q

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago by @chenxwh

Input

task: Face Inpainting
image
broken_image
output_individual

{
  "task": "Face Inpainting",
  "image": "https://replicate.delivery/mgxm/ca352931-51d1-473e-bdee-bd723552eef5/00001.png",
  "broken_image": false,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
  {
    input: {
      task: "Face Inpainting",
      image: "https://replicate.delivery/mgxm/ca352931-51d1-473e-bdee-bd723552eef5/00001.png",
      broken_image: false,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    input={
        "task": "Face Inpainting",
        "image": "https://replicate.delivery/mgxm/ca352931-51d1-473e-bdee-bd723552eef5/00001.png",
        "broken_image": False,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    "input": {
      "task": "Face Inpainting",
      "image": "https://replicate.delivery/mgxm/ca352931-51d1-473e-bdee-bd723552eef5/00001.png",
      "broken_image": false,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69

Prediction

Model

ID

txoykvqka5hfbai66fs654ccwe

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago by @chenxwh

Input

task: Face Restoration
image
broken_image
output_individual

{
  "task": "Face Restoration",
  "image": "https://replicate.delivery/mgxm/b4b36b25-2d90-49ce-89a1-b6c94bde24f8/oldphoto6.png",
  "broken_image": false,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
  {
    input: {
      task: "Face Restoration",
      image: "https://replicate.delivery/mgxm/b4b36b25-2d90-49ce-89a1-b6c94bde24f8/oldphoto6.png",
      broken_image: false,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    input={
        "task": "Face Restoration",
        "image": "https://replicate.delivery/mgxm/b4b36b25-2d90-49ce-89a1-b6c94bde24f8/oldphoto6.png",
        "broken_image": False,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    "input": {
      "task": "Face Restoration",
      "image": "https://replicate.delivery/mgxm/b4b36b25-2d90-49ce-89a1-b6c94bde24f8/oldphoto6.png",
      "broken_image": false,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69

Prediction

Model

ID

hfk3cfthdfb4pemcs5efjnllpm

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

over 3 years ago

Input

task: Face Restoration
image
broken_image
output_individual

{
  "task": "Face Restoration",
  "image": "https://replicate.delivery/mgxm/9ad05129-cd64-47ba-8706-35722847284e/womanx4.png",
  "broken_image": false,
  "output_individual": false
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
  {
    input: {
      task: "Face Restoration",
      image: "https://replicate.delivery/mgxm/9ad05129-cd64-47ba-8706-35722847284e/womanx4.png",
      broken_image: false,
      output_individual: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

pip install replicate

Import the client:

import replicate

Run yangxy/gpen using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "yangxy/gpen:2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    input={
        "task": "Face Restoration",
        "image": "https://replicate.delivery/mgxm/9ad05129-cd64-47ba-8706-35722847284e/womanx4.png",
        "broken_image": False,
        "output_individual": False
    }
)

# The yangxy/gpen model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/yangxy/gpen/api#output-schema
    print(item)

To learn more, take a look at the guide on getting started with Python.

Run yangxy/gpen 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": "2684de9bd9d3b41a7a1942c52fb48b9f76c2f0a69d0309e473865da7eb6f5d69",
    "input": {
      "task": "Face Restoration",
      "image": "https://replicate.delivery/mgxm/9ad05129-cd64-47ba-8706-35722847284e/womanx4.png",
      "broken_image": false,
      "output_individual": false
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output