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xiankgx /controlnet-tile-image-detailer:d0bf83df
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
|
Prompt for the model
|
|
| image |
string
|
Control image for scribble controlnet
|
|
| resolution |
integer
(enum)
|
2560
Options: 2048, 2560, 4096 |
Image resolution
|
| resemblance |
number
|
0.85
Max: 1 |
Conditioning scale for controlnet
|
| creativity |
number
|
0.35
Min: 0.1 Max: 1 |
Denoising strength. 1 means total destruction of the original image
|
| hdr |
number
|
0
Max: 1 |
HDR improvement over the original image
|
| scheduler |
string
(enum)
|
DDIM
Options: DDIM, DPMSolverMultistep, K_EULER_ANCESTRAL, K_EULER |
Choose a scheduler.
|
| steps |
integer
|
20
|
Steps
|
| guidance_scale |
number
|
7
Min: 0.1 Max: 30 |
Scale for classifier-free guidance
|
| seed |
integer
|
Seed
|
|
| negative_prompt |
string
|
teeth, tooth, open mouth, longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, mutant
|
Negative prompt
|
| guess_mode |
boolean
|
False
|
In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.
|
| tile_size |
integer
(enum)
|
512
Options: 128, 256, 374, 512, 768, 1024, 1280 |
Size of partitions of the image. A 1/4 of the final resolution is recommended for optimal.
|
| lora_sharpness_strength |
number
|
4.5
Min: -3 Max: 10 |
Strength of the image's sharpness. For it to be noticeable, it is recommended to use values between 2 and 5.
|
| lora_details_strength |
number
|
1.25
Min: -3 Max: 3 |
Strength of the image's details
|
Output schema
The shape of the response you’ll get when you run this model with an API.
{'format': 'uri', 'title': 'Output', 'type': 'string'}