kayces / contronet

  • Public
  • 14 runs

Run kayces/contronet with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

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
image
string
Input image
prompt
string
Prompt for the model
num_samples
string (enum)
1

Options:

1, 4

Number of samples (higher values may OOM)
image_resolution
string (enum)
512

Options:

256, 512, 768

Image resolution to be generated
low_threshold
integer
100

Min: 1

Max: 255

Canny line detection low threshold
high_threshold
integer
200

Min: 1

Max: 255

Canny line detection high threshold
ddim_steps
integer
20
Steps
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
a_prompt
string
best quality, extremely detailed
Additional text to be appended to prompt
n_prompt
string
longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality
Negative Prompt
detect_resolution
integer
512

Min: 128

Max: 1024

Resolution at which detection method will be applied)

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{
  "type": "array",
  "items": {
    "type": "string",
    "format": "uri"
  },
  "title": "Output"
}