# Topaz Adjust Image

> Professional color and lighting correction powered by Topaz Labs. Adjust V2 fixes exposure, White Balance corrects color casts, Colorize adds color to black-and-white photos. Best for one-click photo correction.


## Overview

- **Endpoint**: `https://fal.run/topaz/adjust/image`
- **Model ID**: `topaz/adjust/image`
- **Category**: image-to-image
- **Kind**: inference
**Tags**: adjust, image



## Pricing

Your request will cost **$0.08** per 24 megapixels with Adjust V2, White Balance or Colorize. Output keeps the source resolution, so most photos cost **$0.08**.

For more details, see [fal.ai pricing](https://fal.ai/pricing).

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:


- **`image_url`** (`string`, _required_):
  Url of the image to process
  - Examples: "https://storage.googleapis.com/falserverless/model_tests/codeformer/codeformer_poor_1.jpeg"

- **`output_format`** (`OutputFormatEnum`, _optional_):
  Output format of the processed image. Default value: `"jpeg"`
  - Default: `"jpeg"`
  - Options: `"jpeg"`, `"png"`

- **`model`** (`ModelEnum`, _optional_):
  Color & lighting correction. Adjust V2 fixes exposure/lighting; White Balance corrects color; Colorize adds color to B&W images. Default value: `"Adjust V2"`
  - Default: `"Adjust V2"`
  - Options: `"Adjust V2"`, `"White Balance"`, `"Colorize"`



**Required Parameters Example**:

```json
{
  "image_url": "https://storage.googleapis.com/falserverless/model_tests/codeformer/codeformer_poor_1.jpeg"
}
```

**Full Example**:

```json
{
  "image_url": "https://storage.googleapis.com/falserverless/model_tests/codeformer/codeformer_poor_1.jpeg",
  "output_format": "jpeg",
  "model": "Adjust V2"
}
```


### Output Schema

The API returns the following output format:

- **`image`** (`File`, _required_):
  The upscaled image.



**Example Response**:

```json
{
  "image": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  }
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/topaz/adjust/image \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "image_url": "https://storage.googleapis.com/falserverless/model_tests/codeformer/codeformer_poor_1.jpeg"
   }'
```

### Python

Ensure you have the Python client installed:

```bash
pip install fal-client
```

Then use the API client to make requests:

```python
import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "topaz/adjust/image",
    arguments={
        "image_url": "https://storage.googleapis.com/falserverless/model_tests/codeformer/codeformer_poor_1.jpeg"
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)
```

### JavaScript

Ensure you have the JavaScript client installed:

```bash
npm install --save @fal-ai/client
```

Then use the API client to make requests:

```javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("topaz/adjust/image", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/model_tests/codeformer/codeformer_poor_1.jpeg"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);
```


## Additional Resources

### Documentation

- [Model Playground](https://fal.ai/models/topaz/adjust/image)
- [API Documentation](https://fal.ai/models/topaz/adjust/image/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=topaz/adjust/image)

### fal.ai Platform

- [Platform Documentation](https://fal.ai/docs/documentation)
- [Python Client](https://fal.ai/docs/api-reference/client-libraries/python)
- [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript)

### Other agent-readable surfaces

This file covers one model. To find anything else:

- [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs
- [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page
- [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined
- Any other model: `https://fal.ai/models/<endpoint-id>/llms.txt`