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zylim0702 /qr_code_controlnet:628e604e

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
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)
768

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
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'}