ControlNet with Civitai
Stable Diffusion with ControlNet
This widget supports multiple actions. For a more comprehensive understanding of its functionality, we recommend reviewing the following documentation carefully.
You need to pass both the action and other input parameters of the chosen action to your module_config
Try it in the Widget Center
Click this url to try this widget and copy the Pro Config template.
Usage
Generate Picture with ControlNet
action txt2img
Input Parameters
action
string
The action of ControlNet, txt2img or img2img
txt2img
model
string
The model id from civitai (SD1.5, SDXL 1.0, PlaygroundV2). How to get it? Click on a model page on civitai, and copy the series number within the download link.
64094
controlnet_model
string
The ControlNet model id from civitai. How to get it? Click on a model page on civitai, and copy the series number within the download link.
10971
image
string
The input image, can be a url or base64 sting
no_mask
boolean
Whether to use mask
False
mask
string
The correspond mask, can be a url or base64 sting. 1 for mask region
prompt
string
The text prompt for ControlNet. Add lora? add `` to your prompt. `$id` is the series number and `$weight` is the lora weight you want (always set to 1.0). You can use multiple loras.
negative_prompt
string
The negative prompt for ControlNet.
(worst quality, low quality:1.4),(malformed hands:1.4),(poorly drawn hands:1.4),(mutated fingers:1.4),(extra limbs:1.35),(poorly drawn face:1.4),bad leg,strange leg, poor eyes, full screen of face
controlnet_module
string
The ControNet module
none
guidance_start
number
ControlNet guidance start
0
guidance_end
number
ControlNet guidance end
1
control_mode
string
The improved guess mode
Balanced
weight
number
The weight of the controlnet model
1
resize_mode
string
Four modes for output shape calculation: (1) Keep: keep original shape, (2) Certain: based on input width/length (divisible by 32), (3,4) min/max ratio: keep aspect ratio, the resize factor is the min/max of (h/H, w/W).
certain
threshold_a
integer
The threshold A for controlnet model
64
threshold_b
integer
The threshold B for controlnet model
64
steps
integer
Steps for sampler to step whle sampling
25
cfg_scale
number
Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results. Default to 7.
7.0
sampler
string
Sampler for diffusion model inference
DPM++ 2M
height
integer
Height of the generated images
512
width
integer
Width of the generated images
512
seed
integer
Random seed for generation process. -1 means random seed
-1
clip_skip
integer
Early stopping parameter for CLIP model; 1 is stop at last layer as usual, 2 is stop at penultimate layer, etc.
1
Output Parameters
url
string
The url of generated image, stored in the cloud. Only temporarily effective, will be cleared in a few hours.
image
Output Example
Inpaint with ControlNet
action img2img
Input Parameters
action
string
The action of ControlNet, txt2img or img2img
txt2img
model
string
The model id from civitai (SD1.5, SDXL 1.0, PlaygroundV2). How to get it? Click on a model page on civitai, and copy the series number within the download link.
64094
controlnet_model
string
The ControlNet model id from civitai. How to get it? Click on a model page on civitai, and copy the series number within the download link.
10971
image
string
The input image, can be a url or base64 sting
no_mask
boolean
Whether to use mask
False
mask
string
The correspond mask, can be a url or base64 sting. 1 for mask region
prompt
string
The text prompt for ControlNet. Add lora? add `` to your prompt. `$id` is the series number and `$weight` is the lora weight you want (always set to 1.0). You can use multiple loras.
negative_prompt
string
The negative prompt for ControlNet.
(worst quality, low quality:1.4),(malformed hands:1.4),(poorly drawn hands:1.4),(mutated fingers:1.4),(extra limbs:1.35),(poorly drawn face:1.4),bad leg,strange leg, poor eyes, full screen of face
controlnet_module
string
The ControNet module
none
guidance_start
number
ControlNet guidance start
0
guidance_end
number
ControlNet guidance end
1
control_mode
string
The improved guess mode
Balanced
weight
number
The weight of the controlnet model
1
resize_mode
string
Four modes for output shape calculation: (1) Keep: keep original shape, (2) Certain: based on input width/length (divisible by 32), (3,4) min/max ratio: keep aspect ratio, the resize factor is the min/max of (h/H, w/W).
certain
threshold_a
integer
The threshold A for controlnet model
64
threshold_b
integer
The threshold B for controlnet model
64
steps
integer
Steps for sampler to step whle sampling
25
cfg_scale
number
Classifier Free Guidance Scale - how strongly the image should conform to prompt - lower values produce more creative results. Default to 7.
7.0
sampler
string
Sampler for diffusion model inference
DPM++ 2M
height
integer
Height of the generated images
512
width
integer
Width of the generated images
512
seed
integer
Random seed for generation process. -1 means random seed
-1
clip_skip
integer
Early stopping parameter for CLIP model; 1 is stop at last layer as usual, 2 is stop at penultimate layer, etc.
1
mask_blur
integer
Mask blur refers to the feathering of a mask (from edges to inside the mask), adjusted between 0-64. A smaller value results in sharper edges. Default to 4
4
inpainting_fill
integer
Choose the fill content in mask: 0 - fill, 1 - original, 2 - latent noise, 3 - latent nothing
1
inpainting_mask_invert
integer
0 - Inpaint masked region, 1 - Inpaint not masked region
0
denoising_strength
number
Strength of image transfomation during inpainting precess. High means more influence during transformation
0.7
Output Parameters
url
string
The url of generated image, stored in the cloud. Only temporarily effective, will be cleared in a few hours.
image
Output Example
Last updated