Prediction

ID

ttaz3dll45genc3blr7oziwnmq

Status

Succeeded

Source

Web

Hardware

–

Total duration

52.6s

Created

almost 3 years ago

Input

image
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/ddcaf605-d06f-4fdb-996e-aa4266dfddbe/palace.png",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/ddcaf605-d06f-4fdb-996e-aa4266dfddbe/palace.png",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/ddcaf605-d06f-4fdb-996e-aa4266dfddbe/palace.png",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/ddcaf605-d06f-4fdb-996e-aa4266dfddbe/palace.png",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

4.3 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

4jxq7slysndjhhhbnxyeeqru5u

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.2s

Created

almost 3 years ago

Input

image
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/793f4c1a-34b2-4999-aa21-5c49a72767ff/wm_fnb_0010.png",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/793f4c1a-34b2-4999-aa21-5c49a72767ff/wm_fnb_0010.png",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/793f4c1a-34b2-4999-aa21-5c49a72767ff/wm_fnb_0010.png",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/793f4c1a-34b2-4999-aa21-5c49a72767ff/wm_fnb_0010.png",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

bmnasufm3nf7bpavpj6pov6vkm

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.1s

Created

almost 3 years ago by @chenxwh

Input

image
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/fbbc7700-69a6-4be8-8a08-41a75037066f/Flowers.png",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/fbbc7700-69a6-4be8-8a08-41a75037066f/Flowers.png",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/fbbc7700-69a6-4be8-8a08-41a75037066f/Flowers.png",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/fbbc7700-69a6-4be8-8a08-41a75037066f/Flowers.png",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.9 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

ybjqplh6ivfp7pki336on5m55u

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.2s

Created

almost 3 years ago by @cszn

Input

image
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/81f186cd-dfb0-4609-b4be-e5e00d3781b5/00038.png",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/81f186cd-dfb0-4609-b4be-e5e00d3781b5/00038.png",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/81f186cd-dfb0-4609-b4be-e5e00d3781b5/00038.png",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/81f186cd-dfb0-4609-b4be-e5e00d3781b5/00038.png",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.9 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

gaek2rcwgzd7hkcamgjkmykq3i

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.6s

Created

almost 3 years ago

Input

image: %E4%B8%8B%E8%BD%BD_1.jfif
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/2ea54917-7461-4170-8315-1ba4b1555bca/%E4%B8%8B%E8%BD%BD_1.jfif",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/2ea54917-7461-4170-8315-1ba4b1555bca/%E4%B8%8B%E8%BD%BD_1.jfif",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/2ea54917-7461-4170-8315-1ba4b1555bca/%E4%B8%8B%E8%BD%BD_1.jfif",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/2ea54917-7461-4170-8315-1ba4b1555bca/%E4%B8%8B%E8%BD%BD_1.jfif",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.3 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

gksvkezekfh6pkk7dxu25xklfm

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.4s

Created

almost 3 years ago

Input

image
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/2a9f49bd-264e-4fd8-8e2e-dcfeaea5e1c5/bbdc6fac861955a7.jpg",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/2a9f49bd-264e-4fd8-8e2e-dcfeaea5e1c5/bbdc6fac861955a7.jpg",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/2a9f49bd-264e-4fd8-8e2e-dcfeaea5e1c5/bbdc6fac861955a7.jpg",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/2a9f49bd-264e-4fd8-8e2e-dcfeaea5e1c5/bbdc6fac861955a7.jpg",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

bdpt5xf3vfa4ljfwop5rcvl7le

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.5s

Created

almost 3 years ago

Input

image: %E4%B8%8B%E8%BD%BD_2.jfif
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/a8c6dbad-30c7-46ce-957f-0fafc599977b/%E4%B8%8B%E8%BD%BD_2.jfif",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/a8c6dbad-30c7-46ce-957f-0fafc599977b/%E4%B8%8B%E8%BD%BD_2.jfif",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/a8c6dbad-30c7-46ce-957f-0fafc599977b/%E4%B8%8B%E8%BD%BD_2.jfif",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/a8c6dbad-30c7-46ce-957f-0fafc599977b/%E4%B8%8B%E8%BD%BD_2.jfif",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.3 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

wnzgaj3qhjgubeclcmkslghlly

Status

Succeeded

Source

Web

Hardware

–

Total duration

2.3s

Created

almost 3 years ago

Input

image
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/a02cd478-db93-4eef-bd1b-da1ace35b35f/6.png",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/a02cd478-db93-4eef-bd1b-da1ace35b35f/6.png",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/a02cd478-db93-4eef-bd1b-da1ace35b35f/6.png",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/a02cd478-db93-4eef-bd1b-da1ace35b35f/6.png",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.0 seconds

cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26

Prediction

Model

ID

7mirp7nfjnam3bqfbqinrcotyu

Status

Succeeded

Source

Web

Hardware

–

Total duration

3.0s

Created

almost 3 years ago

Input

image
model_name: real image denoising

{
  "image": "https://replicate.delivery/mgxm/f23844fe-a04d-4c04-94de-dd54a333511e/7.jpeg",
  "model_name": "real image denoising"
}

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

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

const output = await replicate.run(
  "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
  {
    input: {
      image: "https://replicate.delivery/mgxm/f23844fe-a04d-4c04-94de-dd54a333511e/7.jpeg",
      model_name: "real image denoising"
    }
  }
);

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

output = replicate.run(
    "cszn/scunet:df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    input={
        "image": "https://replicate.delivery/mgxm/f23844fe-a04d-4c04-94de-dd54a333511e/7.jpeg",
        "model_name": "real image denoising"
    }
)
print(output)

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

Run cszn/scunet 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": "df9a3c1dbc6c1f7f4c2d244f68dffa2699a169cf5e701e0d6a009bf6ff507f26",
    "input": {
      "image": "https://replicate.delivery/mgxm/f23844fe-a04d-4c04-94de-dd54a333511e/7.jpeg",
      "model_name": "real image denoising"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

2.8 seconds