# Image Upscaler 2x & 4x — Fast AI Super Resolution (`tidydata/image-upscaler-cpu`) Actor

Enlarge images 2x or 4x with neural-network super resolution (FSRCNN): crisper than plain resizing, no GPU or API key needed. PNG, JPG or WebP output with a public link. $4 per 1,000 images.

- **URL**: https://apify.com/tidydata/image-upscaler-cpu.md
- **Developed by:** [tidydata](https://apify.com/tidydata) (community)
- **Categories:** AI, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.20 / 1,000 image enlargeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🔎 Image Upscaler 2x & 4x — super resolution for photos

Enlarge images **2x or 4x** with **neural-network super resolution**: edges are rebuilt instead of just stretched, so the result is **crisper than normal resizing**. No GPU, no API key. Output **PNG, JPG or WebP** with a public link. **$4 per 1,000 images.**

- ✅ Fast neural model (FSRCNN) that runs on CPU: pennies per image
- ✅ Transparency (PNG/WebP alpha) is kept
- ✅ Direct links to JPG, PNG, WebP, HEIC images
- ✅ Input and output sizes reported for every image
- ✅ Good for **old photos, small product pictures, thumbnails to print, game and web assets**

### How to use it

1. Paste direct image links.
2. Choose 2x or 4x and the output format.
3. Run and open the image links in the results.

### Output example

```json
{
  "url": "https://example.com/small.jpg",
  "imageUrl": "https://api.apify.com/v2/key-value-stores/…/records/0000-small-x2.png",
  "scale": 2, "model": "FSRCNN",
  "inputWidth": 640, "inputHeight": 480, "outputWidth": 1280, "outputHeight": 960
}
```

### Pricing

**$0.004 per image enlarged** ($4 per 1,000). Images that fail are free.

### Limits

- Up to 6 megapixels per image. Larger images return a clear message.
- This is a fast, light model: the gain is crisper edges, not miracles. For heavy restoration of very poor images, a GPU model will do more.
- Super resolution adds plausible detail; it cannot recover text or faces that were never in the picture.

### Credits

Model: FSRCNN (Saafke/FSRCNN_Tensorflow), Apache License 2.0, run with OpenCV.

# Actor input Schema

## `urls` (type: `array`):

Direct links to images (JPG, PNG, WebP, HEIC), up to 6 megapixels each. Works best on small and medium images, old photos and thumbnails.

## `scale` (type: `string`):

2 doubles the width and height, 4 quadruples them.

## `format` (type: `string`):

PNG is lossless. JPG and WebP are smaller.

## Actor input object example

```json
{
  "urls": [
    {
      "url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/Canon_40D.jpg"
    }
  ],
  "scale": "2",
  "format": "png"
}
```

# Actor output Schema

## `results` (type: `string`):

One row per result.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "urls": [
        {
            "url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/Canon_40D.jpg"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("tidydata/image-upscaler-cpu").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "urls": [{ "url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/Canon_40D.jpg" }] }

# Run the Actor and wait for it to finish
run = client.actor("tidydata/image-upscaler-cpu").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "urls": [
    {
      "url": "https://raw.githubusercontent.com/ianare/exif-samples/master/jpg/Canon_40D.jpg"
    }
  ]
}' |
apify call tidydata/image-upscaler-cpu --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,tidydata/image-upscaler-cpu"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/6V6oFyxqq8Li5zZY2/builds/yWkeezBq2aEgK4lbV/openapi.json