Prediction

ID

fdd673pi4fbwhpmybti4aq2i5i

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago

Input

image
model: Hayao

{
  "image": "https://replicate.delivery/mgxm/f73705ac-9df1-4131-9050-3b5809b11855/132.jpg",
  "model": "Hayao"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
  {
    input: {
      image: "https://replicate.delivery/mgxm/f73705ac-9df1-4131-9050-3b5809b11855/132.jpg",
      model: "Hayao"
    }
  }
);

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 ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    input={
        "image": "https://replicate.delivery/mgxm/f73705ac-9df1-4131-9050-3b5809b11855/132.jpg",
        "model": "Hayao"
    }
)

# The ptran1203/pytorch-animegan 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/ptran1203/pytorch-animegan/api#output-schema
    print(item)

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

Run ptran1203/pytorch-animegan 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": "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    "input": {
      "image": "https://replicate.delivery/mgxm/f73705ac-9df1-4131-9050-3b5809b11855/132.jpg",
      "model": "Hayao"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd

Prediction

Model

ID

ew5xz6de4bbbbaqoqye7pnghjy

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago

Input

image
model: Hayao

{
  "image": "https://replicate.delivery/mgxm/b21ebb59-30f0-4c25-beae-70d42f0a77d7/136.jpg",
  "model": "Hayao"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
  {
    input: {
      image: "https://replicate.delivery/mgxm/b21ebb59-30f0-4c25-beae-70d42f0a77d7/136.jpg",
      model: "Hayao"
    }
  }
);

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 ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    input={
        "image": "https://replicate.delivery/mgxm/b21ebb59-30f0-4c25-beae-70d42f0a77d7/136.jpg",
        "model": "Hayao"
    }
)

# The ptran1203/pytorch-animegan 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/ptran1203/pytorch-animegan/api#output-schema
    print(item)

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

Run ptran1203/pytorch-animegan 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": "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    "input": {
      "image": "https://replicate.delivery/mgxm/b21ebb59-30f0-4c25-beae-70d42f0a77d7/136.jpg",
      "model": "Hayao"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd

Prediction

Model

ID

m6rzj2l57vanlo2kofszvzbvdm

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago

Input

image
model: Hayao

{
  "image": "https://replicate.delivery/mgxm/69e8c071-a65b-4fc6-8f56-99c8ee8656db/146.jpg",
  "model": "Hayao"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
  {
    input: {
      image: "https://replicate.delivery/mgxm/69e8c071-a65b-4fc6-8f56-99c8ee8656db/146.jpg",
      model: "Hayao"
    }
  }
);

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 ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    input={
        "image": "https://replicate.delivery/mgxm/69e8c071-a65b-4fc6-8f56-99c8ee8656db/146.jpg",
        "model": "Hayao"
    }
)

# The ptran1203/pytorch-animegan 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/ptran1203/pytorch-animegan/api#output-schema
    print(item)

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

Run ptran1203/pytorch-animegan 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": "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    "input": {
      "image": "https://replicate.delivery/mgxm/69e8c071-a65b-4fc6-8f56-99c8ee8656db/146.jpg",
      "model": "Hayao"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd

Prediction

Model

ID

pejgbl25f5hzhlwvg4inot36q4

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago

Input

image
model: Hayao

{
  "image": "https://replicate.delivery/mgxm/148b2895-4ff2-4560-88eb-629b8ac828bc/155.jpg",
  "model": "Hayao"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
  {
    input: {
      image: "https://replicate.delivery/mgxm/148b2895-4ff2-4560-88eb-629b8ac828bc/155.jpg",
      model: "Hayao"
    }
  }
);

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 ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    input={
        "image": "https://replicate.delivery/mgxm/148b2895-4ff2-4560-88eb-629b8ac828bc/155.jpg",
        "model": "Hayao"
    }
)

# The ptran1203/pytorch-animegan 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/ptran1203/pytorch-animegan/api#output-schema
    print(item)

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

Run ptran1203/pytorch-animegan 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": "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    "input": {
      "image": "https://replicate.delivery/mgxm/148b2895-4ff2-4560-88eb-629b8ac828bc/155.jpg",
      "model": "Hayao"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd

Prediction

Model

ID

7vduriritnazncvpd5olzyrcda

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago

Input

image
model: Hayao

{
  "image": "https://replicate.delivery/mgxm/004d08ba-c2c0-435a-8565-516f4445bd8a/142.jpg",
  "model": "Hayao"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
  {
    input: {
      image: "https://replicate.delivery/mgxm/004d08ba-c2c0-435a-8565-516f4445bd8a/142.jpg",
      model: "Hayao"
    }
  }
);

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 ptran1203/pytorch-animegan using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    input={
        "image": "https://replicate.delivery/mgxm/004d08ba-c2c0-435a-8565-516f4445bd8a/142.jpg",
        "model": "Hayao"
    }
)

# The ptran1203/pytorch-animegan 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/ptran1203/pytorch-animegan/api#output-schema
    print(item)

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

Run ptran1203/pytorch-animegan 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": "ptran1203/pytorch-animegan:163ba05100a2385815d4e56e9276ff70de824d0d3672f0c3e5634c319c5102dd",
    "input": {
      "image": "https://replicate.delivery/mgxm/004d08ba-c2c0-435a-8565-516f4445bd8a/142.jpg",
      "model": "Hayao"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output