# lazymix+ v4 inpaint

> AI model for generating stable diffusion content

## Overview

- **Model ID**: `lazymixv4-inpaint`
- **Category**: stable diffusion
- **Provider**: modelslab
- **Status**: model_ready
- **Screenshot**: `https://assets.modelslab.com/generations/11e54402-481a-460b-928b-05c6c72a1e59-0.png`

## API Information

This model can be used via our HTTP API. See the API documentation and usage examples below.

### Endpoint

- **URL**: `https://modelslab.com/api/v6/images/inpaint`
- **Method**: POST

### Parameters

- **`prompt`** (required): 
  - Type: textarea
  - Example: Please enter a prompt here

- **`init_image`** (required): Upload the image you want a part to be replaced
  - Type: file (image/jpeg,image/png,image/webp)
  - Example: Please upload image

- **`mask_image`** (required): upload mask image for the part of the image you want to replace a part
  - Type: file (image/jpeg,image/png,image/webp)
  - Example: Upload mask image 

- **`strength`** (required): Strength controls how much the output follows the prompt vs. the original image. 1 = more prompt-driven, 0.1 = minimal change, more like the original
  - Type: number (range: 0.1-1)

- **`samples`** (optional): 
  - Type: number (range: 1-4)

- **`model_id`** (optional): 
  - Type: select (options: lazymixv4-inpaint, v51_inpainting, realistic-vision-v6.0-b1-inpaint-n)

- **`steps`** (optional): 
  - Type: number (range: 21-31)

- **`scheduler`** (optional): 
  - Type: select (options: DPM++ 2M, Euler, Euler a)

- **`track_id`** (optional): ID for webhook identification
  - Type: number

## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://modelslab.com/api/v6/images/inpaint \
  --header "Content-Type: application/json" \
  --data '{
    "key": "YOUR_API_KEY",
    "model_id": "lazymixv4-inpaint",
    "prompt": "wearing black bodycon dress",
    "init_image": "https://assets.modelslab.com/generations/ae796f25-7c05-4415-8fc5-8bc1f7c06e12",
    "mask_image": "https://assets.modelslab.com/generations/71177163-a6f0-4cec-a048-1644eb47a5c2",
    "strength": "1.0",
    "samples": "1",
    "steps": "31",
    "scheduler": "DPMSolverMultistepScheduler",
    "track_id": "0"
  }'
```

### Python

```python
import requests

response = requests.post(
    "https://modelslab.com/api/v6/images/inpaint",
    headers={
        "Content-Type": "application/json"
    },
    json={
        "key": "YOUR_API_KEY",
        "model_id": "lazymixv4-inpaint",
        "prompt": "wearing black bodycon dress",
        "init_image": "https://assets.modelslab.com/generations/ae796f25-7c05-4415-8fc5-8bc1f7c06e12",
        "mask_image": "https://assets.modelslab.com/generations/71177163-a6f0-4cec-a048-1644eb47a5c2",
        "strength": "1.0",
        "samples": "1",
        "steps": "31",
        "scheduler": "DPMSolverMultistepScheduler",
        "track_id": "0"
    }
)

print(response.json())
```

### JavaScript

```javascript
fetch("https://modelslab.com/api/v6/images/inpaint", {
  method: "POST",
  headers: {
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    "key": "YOUR_API_KEY",
    "model_id": "lazymixv4-inpaint",
    "prompt": "wearing black bodycon dress",
    "init_image": "https://assets.modelslab.com/generations/ae796f25-7c05-4415-8fc5-8bc1f7c06e12",
    "mask_image": "https://assets.modelslab.com/generations/71177163-a6f0-4cec-a048-1644eb47a5c2",
    "strength": "1.0",
    "samples": "1",
    "steps": "31",
    "scheduler": "DPMSolverMultistepScheduler",
    "track_id": "0"
  })
})
.then(response => response.json())
.then(data => console.log(data));
```

## Links

- [Model Playground](https://modelslab.com/models/replace-object-inpaint/lazymixv4-inpaint)
- [API Documentation](https://docs.modelslab.com)
- [ModelsLab Platform](https://modelslab.com)