---
title: Enhancing at the original resolution — Topaz Labs Wonder 4 | Runware Docs
url: https://runware.ai/docs/models/topazlabs-wonder-4/guides/enhancing-at-original-resolution
description: "How to clean up an image with Topaz Wonder 4 without enlarging it: what a factor of 1 returns, when to pick it over 2, and how it fits fixed-size listings."
---
### [Introduction](https://runware.ai/docs/models/topazlabs-wonder-4/guides/enhancing-at-original-resolution#introduction)

Plenty of images are **already big enough and still not usable**. A conference photo shot in a dim auditorium has the pixels for a full-width banner, but it is covered in sensor noise. Setting `upscaleFactor` to 1 runs Wonder 4's full enhancement and **returns the image at its original width and height**.

**Source**:

![A keynote speaker in a dark blazer on a dimly lit conference stage, gesturing with both hands, the frame grainy and soft](https://runware.ai/docs/assets/source-keynote.9QTpdTto_2vXoYk.jpg)

**Wonder 4**:

![The same speaker and stage, clean, with smooth shadows in the auditorium and sharp detail on her face, blazer and hands](https://runware.ai/docs/assets/output-keynote.JJ8UkEcA_2vOOY7.jpg)

*A noisy 2752 px event photo enhanced at a factor of 1, same size in and out. Drag to compare.*

At page width the change reads as a cleaner frame. A 100% crop of the speaker shows **what the noise was hiding**:

![A grainy close-up crop of the speaker's face and open hands, with colored noise across the skin and the blazer](https://runware.ai/docs/assets/crop-source-keynote.CWzCK5t0_2dCrsC.jpg)

*Source · 100% crop*

![The same crop after enhancement, with clean skin texture, defined eyes and sharp fingers](https://runware.ai/docs/assets/crop-output-keynote.PNKfSade_ZXyC6c.jpg)

*Wonder 4 · 100% crop*

The colored grain across her face is gone, and instead of smoothing it into plastic the model **brings back skin texture and the detail in her eyes**. Her fingers and the clicker in her hand have clean edges again.

### [The request](https://runware.ai/docs/models/topazlabs-wonder-4/guides/enhancing-at-original-resolution#the-request)

Only `upscaleFactor` changes from an ordinary upscale:

**TypeScript**:

```typescript
import { createClient } from '@runware/sdk'

const client = await createClient({ apiKey: process.env.RUNWARE_API_KEY })
await client.connect()

const [result] = await client.run({
  model: 'topazlabs:wonder@4',
  upscaleFactor: 1,
  inputs: {
    image: 'https://im.runware.ai/image/os/a14d18/ws/2/ii/2a7c5e9f-4b1d-4e8a-a3c6-6d9f2b5e8a41.jpg'
  }
})
```

**Python**:

```python
import asyncio
import os

from runware import Runware

async def main():
    async with Runware(api_key=os.environ["RUNWARE_API_KEY"]) as client:
        results = await client.run({
            "model": "topazlabs:wonder@4",
            "upscaleFactor": 1,
            "inputs": {
                "image": "https://im.runware.ai/image/os/a14d18/ws/2/ii/2a7c5e9f-4b1d-4e8a-a3c6-6d9f2b5e8a41.jpg"
            }
        })

asyncio.run(main())
```

**cURL**:

```bash
curl https://api.runware.ai/v1 \
  -H "Authorization: Bearer $RUNWARE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "taskType": "upscale",
      "taskUUID": "9e2b6d41-3a8f-4c7e-b5d2-1f7a9c3e6b08",
      "model": "topazlabs:wonder@4",
      "upscaleFactor": 1,
      "inputs": {
        "image": "https://im.runware.ai/image/os/a14d18/ws/2/ii/2a7c5e9f-4b1d-4e8a-a3c6-6d9f2b5e8a41.jpg"
      }
    }
  ]'
```

**CLI**:

```bash
runware run topazlabs:wonder@4 \
  upscaleFactor=1 \
  inputs.image=https://im.runware.ai/image/os/a14d18/ws/2/ii/2a7c5e9f-4b1d-4e8a-a3c6-6d9f2b5e8a41.jpg
```

**JSON**:

```json
{
  "taskType": "upscale",
  "taskUUID": "9e2b6d41-3a8f-4c7e-b5d2-1f7a9c3e6b08",
  "model": "topazlabs:wonder@4",
  "upscaleFactor": 1,
  "inputs": {
    "image": "https://im.runware.ai/image/os/a14d18/ws/2/ii/2a7c5e9f-4b1d-4e8a-a3c6-6d9f2b5e8a41.jpg"
  }
}
```

The result has **exactly the width and height of the source**, so it drops into the same layout slot or asset record the original came from. Everything else works as described in [upscaling images](https://runware.ai/docs/models/topazlabs-wonder-4/guides/upscaling-images): one image in `inputs.image` and no settings, with the model deciding what each region needs.

### [Factor 1 or factor 2](https://runware.ai/docs/models/topazlabs-wonder-4/guides/enhancing-at-original-resolution#factor-1-or-factor-2)

A factor of 1 **never adds pixels**, so it cannot raise the resolution of a small image. Reach for it when the size is already settled:

- **The size is already the one you deliver.** Camera files and 4K frames rarely need to get bigger, and enlarging them only produces a heavier file you would downscale again. A marketplace listing or a storefront template that expects one exact size takes the enhanced image as it is.
- **The source is larger than 64 megapixels.** A factor of 2 tops out at 64 MP of input, so above that a factor of 1 is the only one Wonder 4 accepts. It takes sources up to **256 megapixels and 32,000 pixels on the longest side**. The full table is in [upscaling images](https://runware.ai/docs/models/topazlabs-wonder-4/guides/upscaling-images).

As soon as the deliverable is larger than the source, switch to 2 or more, and the same request **enlarges the image while it cleans it up**.

### [Fixed-size listings](https://runware.ai/docs/models/topazlabs-wonder-4/guides/enhancing-at-original-resolution#fixed-size-listings)

Marketplaces and storefront templates often require one exact image size, and supplier photos tend to arrive **recompressed several times on the way**. This drill shot is already the 2048 × 2048 the listing wants, but the compression has smeared the fine texture on the chuck and the grip:

**Source**:

![A charcoal and orange cordless drill on a white background, with compression artifacts around the chuck and on the grip](https://runware.ai/docs/assets/source-drill.DkGvhbJB_K3D6A.jpg)

**Wonder 4**:

![The same drill at the same size, with a clean white background, a sharp metal chuck and textured rubber on the grip](https://runware.ai/docs/assets/output-drill.DCYKdzHn_Z23uJwp.jpg)

*A heavily compressed 2048 × 2048 product listing enhanced at a factor of 1.*

The crops come from the same 2048 × 2048 frame, which is what the listing will show when a shopper zooms in:

![A close-up crop of the drill chuck, its knurling blurred and haloed by compression](https://runware.ai/docs/assets/crop-source-drill.BysSpHmE_2gH7XG.jpg)

*Source · 100% crop*

![The same crop after enhancement, with a crisp diamond knurl on the chuck and clean metal edges](https://runware.ai/docs/assets/crop-output-drill.BhgNC8x8_Z21flRE.jpg)

*Wonder 4 · 100% crop*

The knurling on the chuck comes back as **a crisp diamond pattern** instead of a haloed blur, while the image keeps the exact dimensions the listing was built for.

### [Tips](https://runware.ai/docs/models/topazlabs-wonder-4/guides/enhancing-at-original-resolution#tips)

1. **Use 1 when the size is already right.** Enlarging a frame you will scale back down adds cost and processing time for nothing.
    
2. **Enhance before the final export.** Run the cleanup on the best copy you have, then let your platform resize or compress it, so the restored detail is the starting point rather than another casualty of recompression.
    
3. **Check very large files against the limit.** A factor of 1 takes up to 256 megapixels and 32,000 pixels on the longest side. Anything bigger is rejected, so downscale it first.
    
4. **Compare at 100%.** Source and result share the same size, so at page width they can look alike. Open both at native resolution, or crop the same region from each, to judge what changed.