> ## Documentation Index
> Fetch the complete documentation index at: https://docs.oxen.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# 🎨 Image Editing

> How to use the image editing API on Oxen.ai.

### Image Editing

The image editing endpoint allows you to edit images using AI models. Simply provide an input image URL and a prompt describing the edits you want to make. To see the list of models that support image editing, visit the [Models](https://www.oxen.ai/ai/models?modalities=image-to-image) page and filter by "Image to Image".

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST \
    https://hub.oxen.ai/api/ai/images/edit \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $OXEN_API_KEY" \
    -d '{
      "model": "Qwen/Qwen-Image-Edit",
      "input_image": "https://example.com/image.png",
      "prompt": "Add a funny hat to the ox",
      "num_inference_steps": 28
    }'
  ```

  ```python Python theme={null}
  import requests
  import os

  response = requests.post(
      "https://hub.oxen.ai/api/ai/images/edit",
      headers={
          "Authorization": f"Bearer {os.getenv('OXEN_API_KEY')}",
          "Content-Type": "application/json"
      },
      json={
          "model": "Qwen/Qwen-Image-Edit",
          "input_image": "https://example.com/image.png",
          "prompt": "Add a funny hat to the ox",
          "num_inference_steps": 28
      }
  )

  # The response contains the edited image URL
  edited_image_url = response.json()["image_url"]
  print(f"Edited image: {edited_image_url}")
  ```
</CodeGroup>

For models that support multiple input images, you can pass an array of image URLs:

<CodeGroup>
  ```bash cURL (multiple images) theme={null}
  curl -X POST \
    https://hub.oxen.ai/api/ai/images/edit \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer $OXEN_API_KEY" \
    -d '{
      "model": "Qwen/Qwen-Image-Edit",
      "input_image": [
        "https://example.com/image1.png",
        "https://example.com/image2.png"
      ],
      "prompt": "Add a funny hat to the ox",
      "num_inference_steps": 28
    }'
  ```

  ```python Python (multiple images) theme={null}
  import requests
  import os

  response = requests.post(
      "https://hub.oxen.ai/api/ai/images/edit",
      headers={
          "Authorization": f"Bearer {os.getenv('OXEN_API_KEY')}",
          "Content-Type": "application/json"
      },
      json={
          "model": "Qwen/Qwen-Image-Edit",
          "input_image": [
              "https://example.com/image1.png",
              "https://example.com/image2.png"
          ],
          "prompt": "Add a funny hat to the ox",
          "num_inference_steps": 28
      }
  )

  edited_image_url = response.json()["image_url"]
  print(f"Edited image: {edited_image_url}")
  ```
</CodeGroup>

## Parameters

* **model**: The model identifier to use for image editing (e.g., `Qwen/Qwen-Image-Edit`)
* **input\_image**: URL of the input image(s) you want to edit. Can be a string (single image URL) or an array of strings (multiple image URLs) for models that support multiple images as input
* **prompt**: Text description of the edits you want to make
* **num\_inference\_steps**: Number of inference steps (optional, defaults vary by model)

## Playground Interface

The model playground allows you to quickly test out the boundaries of any model in the UI. This is a great way to experiment with different prompts and see how the model performs before integrating it into your application.

<img src="https://mintcdn.com/oxenai/ww25tVPcZSq1nsp-/images/inference/image-editing/playground.png?fit=max&auto=format&n=ww25tVPcZSq1nsp-&q=85&s=be8ec68abd60bb7b5029f603320f3429" alt="Image editing playground" className="rounded-xl" noZoom width="3018" height="1582" data-path="images/inference/image-editing/playground.png" />

The generated images automatically get saved to a dataset that you can share with your team, download and use to train your own model, or use in your application.