Prediction

ID

djlzjw76zvgqpl7pe5fq3daf5e

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago by @chenxwh

Input

image
model_type: celeb

{
  "image": "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png",
  "model_type": "celeb"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png",
      model_type: "celeb"
    }
  }
);

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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    input={
        "image": "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png",
        "model_type": "celeb"
    }
)

# The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema
    print(item)

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

Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    "input": {
      "image": "https://replicate.delivery/mgxm/0fbe6e1d-facd-439b-8be8-305ba4600cf1/16.png",
      "model_type": "celeb"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Loading...

jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e

Prediction

Model

ID

nodd7572kjgnnnfctamhvb7u7m

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago by @chenxwh

Input

image
model_type: celeb

{
  "image": "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png",
  "model_type": "celeb"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png",
      model_type: "celeb"
    }
  }
);

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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    input={
        "image": "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png",
        "model_type": "celeb"
    }
)

# The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema
    print(item)

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

Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    "input": {
      "image": "https://replicate.delivery/mgxm/65b81636-0467-4a4e-97f4-1d854104dac7/253.png",
      "model_type": "celeb"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Loading...

jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e

Prediction

Model

ID

eug4gtwtrnb4royjzg24l3nrle

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago by @chenxwh

Input

image
model_type: celeb

{
  "image": "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png",
  "model_type": "celeb"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png",
      model_type: "celeb"
    }
  }
);

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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    input={
        "image": "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png",
        "model_type": "celeb"
    }
)

# The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema
    print(item)

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

Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    "input": {
      "image": "https://replicate.delivery/mgxm/80831344-f209-4a61-a33e-5e77ff0242e3/334.png",
      "model_type": "celeb"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Loading...

jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e

Prediction

Model

ID

3exzbtvdlnablcwr5dzpfkbr34

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago by @chenxwh

Input

image
model_type: celeb

{
  "image": "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png",
  "model_type": "celeb"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png",
      model_type: "celeb"
    }
  }
);

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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    input={
        "image": "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png",
        "model_type": "celeb"
    }
)

# The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema
    print(item)

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

Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    "input": {
      "image": "https://replicate.delivery/mgxm/53d168c1-8274-48c3-8f6b-97d19af7d598/36.png",
      "model_type": "celeb"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Loading...

jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e

Prediction

Model

ID

rkakzczsqbdu5mmv45bd3ray6e

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago

Input

image
model_type: celeb

{
  "image": "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png",
  "model_type": "celeb"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png",
      model_type: "celeb"
    }
  }
);

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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    input={
        "image": "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png",
        "model_type": "celeb"
    }
)

# The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema
    print(item)

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

Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    "input": {
      "image": "https://replicate.delivery/mgxm/35deb1f3-cf7a-4657-81e5-e8bfbf15e838/110.png",
      "model_type": "celeb"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Loading...

jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e

Prediction

Model

ID

brfrihkqurbonoh7xxjs7isdpm

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago by @chenxwh

Input

image
model_type: celeb

{
  "image": "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png",
  "model_type": "celeb"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png",
      model_type: "celeb"
    }
  }
);

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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    input={
        "image": "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png",
        "model_type": "celeb"
    }
)

# The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema
    print(item)

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

Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    "input": {
      "image": "https://replicate.delivery/mgxm/a9c159f6-8a4d-4dde-8af2-fe52abfc8f92/217.png",
      "model_type": "celeb"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Loading...

jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e

Prediction

Model

ID

veeeh5afrrhbfj6xahp6gbuevq

Status

Succeeded

Source

Web

Hardware

–

Total duration

–

Created

almost 4 years ago

Input

image
model_type: general

{
  "image": "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png",
  "model_type": "general"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
  {
    input: {
      image: "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png",
      model_type: "general"
    }
  }
);

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 jingyunliang/hcflow-sr using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    input={
        "image": "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png",
        "model_type": "general"
    }
)

# The jingyunliang/hcflow-sr 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/jingyunliang/hcflow-sr/api#output-schema
    print(item)

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

Run jingyunliang/hcflow-sr 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": "jingyunliang/hcflow-sr:097da1ab008e9ead60886ce9fa4bd156f21ae36142785d642354680f6dd25e9e",
    "input": {
      "image": "https://replicate.delivery/mgxm/8c0b1717-9f07-41ea-8a80-5ebcf207f5b7/butterfly.png",
      "model_type": "general"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Loading...