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tonyhopkins994 /test:dc76c828
Input schema
The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.
| Field | Type | Default value | Description |
|---|---|---|---|
| prompt |
string
|
Living Room, high quality, best quality, highres, high resolution, highly detailed, realistic, ultrarealistic, photorealistic, 4K, 8K
|
Input prompt
|
| negative_prompt |
string
|
blurry, distorted, low quality, worst quality, unrealistic, sketch, cartoon, artificial
|
Negative Prompt
|
| seed |
string
|
-1
|
Random generation seed
|
| num_inference_steps |
integer
|
30
Min: 1 Max: 500 |
Number of denoising steps
|
| guidance_scale |
number
|
7.5
Min: 1 Max: 50 |
Scale for classifier-free guidance
|
| strength |
number
|
1
Max: 1 |
Inpainting strength; 0 equates to no change, 1 equates to complete destruction of initial image
|
| num_outputs |
integer
|
1
Min: 1 Max: 6 |
Number of images to output
|
| upscale |
string
(enum)
|
None
Options: None, 2x, 3x |
Upscale resolution
|
| input_image |
string
|
Source image for inpainting, base64 encoded string
|
|
| mask_image |
string
|
Image mask for inpainting, base64 encoded string
|
|
| ip_adapter_scale |
number
|
0.5
Max: 1 |
IP adapter guidance strength
|
| ip_adapter_image |
string
|
Input image for IP adapter, base64 encoded string
|
|
| normal_image |
string
|
Input image for normal controlnet, base64 encoded string
|
|
| depth_image |
string
|
Input image for depth controlnet, base64 encoded string
|
|
| mlsd_image |
string
|
Input image for mlsd controlnet, base64 encoded string
|
|
| seg_image |
string
|
Input image for segmentation controlnet, base64 encoded string
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'items': {'type': 'string'}, 'title': 'Output', 'type': 'array'}