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zylim0702/qr_code_controlnet:a7b184fd
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 |
|---|---|---|---|
| url |
string
|
Link Url for QR Code.
|
|
| prompt |
string
|
Prompt for the model
|
|
| canny_image |
string
|
Control image for canny controlnet
|
|
| canny_conditioning_scale |
number
|
1
|
Conditioning scale for canny controlnet
|
| depth_image |
string
|
Control image for depth controlnet
|
|
| depth_conditioning_scale |
number
|
1
|
Conditioning scale for depth controlnet
|
| hed_image |
string
|
Control image for hed controlnet
|
|
| hed_conditioning_scale |
number
|
1
|
Conditioning scale for hed controlnet
|
| hough_image |
string
|
Control image for hough controlnet
|
|
| hough_conditioning_scale |
number
|
1
|
Conditioning scale for hough controlnet
|
| normal_image |
string
|
Control image for normal controlnet
|
|
| normal_conditioning_scale |
number
|
1
|
Conditioning scale for normal controlnet
|
| pose_image |
string
|
Control image for pose controlnet
|
|
| pose_conditioning_scale |
number
|
1
|
Conditioning scale for pose controlnet
|
| scribble_image |
string
|
Control image for scribble controlnet
|
|
| scribble_conditioning_scale |
number
|
1
|
Conditioning scale for scribble controlnet
|
| seg_image |
string
|
Control image for seg controlnet
|
|
| seg_conditioning_scale |
number
|
1
|
Conditioning scale for seg controlnet
|
| qr_conditioning_scale |
number
|
1
|
Conditioning scale for qr controlnet
|
| num_outputs |
integer
|
1
Min: 1 Max: 10 |
Number of images to generate
|
| image_resolution |
integer
(enum)
|
512
Options: 256, 512, 768 |
Resolution of image (smallest dimension)
|
| scheduler |
string
(enum)
|
DDIM
Options: DDIM, DPMSolverMultistep, HeunDiscrete, K_EULER_ANCESTRAL, K_EULER, KLMS, PNDM, UniPCMultistep |
Choose a scheduler.
|
| num_inference_steps |
integer
|
20
|
Steps to run denoising
|
| guidance_scale |
number
|
9
Min: 0.1 Max: 30 |
Scale for classifier-free guidance
|
| seed |
integer
|
Seed
|
|
| eta |
number
|
0
|
Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise
|
| negative_prompt |
string
|
Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
|
Negative prompt
|
| low_threshold |
integer
|
100
Min: 1 Max: 255 |
[canny only] Line detection low threshold
|
| high_threshold |
integer
|
200
Min: 1 Max: 255 |
[canny only] Line detection high threshold
|
| 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.
|
| disable_safety_check |
boolean
|
False
|
Disable safety check. Use at your own risk!
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}