prompthunt
/
cog-sdxl-controlnet-face-fix
- Public
- 74 runs
Run prompthunt/cog-sdxl-controlnet-face-fix 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 |
|---|---|---|---|
| lora_weights |
string
|
LoRA weights to use. Leave blank to use the default weights.
|
|
| prompt |
string
|
An astronaut riding a rainbow unicorn
|
Input prompt
|
| negative_prompt |
string
|
|
Input Negative Prompt
|
| image |
string
|
Input image for img2img or inpaint mode
|
|
| mask |
string
|
Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted.
|
|
| width |
integer
|
1024
|
Width of output image
|
| height |
integer
|
1024
|
Height of output image
|
| num_outputs |
integer
|
1
Min: 1 Max: 4 |
Number of images to output.
|
| scheduler |
string
(enum)
|
K_EULER
Options: DDIM, DPMSolverMultistep, HeunDiscrete, DPM++SDEKarras, K_EULER_ANCESTRAL, K_EULER, PNDM |
scheduler
|
| num_inference_steps |
integer
|
50
Min: 1 Max: 500 |
Number of denoising steps
|
| guidance_scale |
number
|
7.5
Min: 1 Max: 50 |
Scale for classifier-free guidance
|
| prompt_strength |
number
|
0.8
Max: 1 |
Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
|
| seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
| refine |
string
(enum)
|
no_refiner
Options: no_refiner, expert_ensemble_refiner, base_image_refiner |
Which refine style to use
|
| high_noise_frac |
number
|
0.8
Max: 1 |
For expert_ensemble_refiner, the fraction of noise to use
|
| refine_steps |
integer
|
For base_image_refiner, the number of steps to refine, defaults to num_inference_steps
|
|
| apply_watermark |
boolean
|
True
|
Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking.
|
| lora_scale |
number
|
0.6
Max: 1 |
LoRA additive scale. Only applicable on trained models.
|
| disable_safety_checker |
boolean
|
True
|
Disable safety checker for generated images. This feature is only available through the API. See [https://replicate.com/docs/how-does-replicate-work#safety](https://replicate.com/docs/how-does-replicate-work#safety)
|
| pose_image |
string
|
Pose image for controlnet
|
|
| controlnet_conditioning_scale |
number
|
0.75
Max: 4 |
How strong the controlnet conditioning is
|
| controlnet_start |
number
|
0
Max: 1 |
When controlnet conditioning starts
|
| controlnet_end |
number
|
1
Max: 1 |
When controlnet conditioning ends
|
| fix_face |
boolean
|
False
|
Fix the face in the image
|
| mask_blur_amount |
number
|
8
|
Amount of blur to apply to the mask.
|
| face_padding |
number
|
2
|
Amount of padding (as percentage) to add to the face bounding box.
|
| face_resize_to |
integer
|
1024
|
Resize the face bounding box to this size (in pixels).
|
| upscale_face |
boolean
|
False
|
Upscale the face using GFPGAN
|
| inpaint_prompt |
string
|
A photo of TOK
|
Input prompt
|
| inpaint_negative_prompt |
string
|
|
Input Negative Prompt
|
| inpaint_num_inference_steps |
integer
|
25
Min: 1 Max: 500 |
Number of denoising steps
|
| inpaint_guidance_scale |
number
|
3
Min: 1 Max: 50 |
Scale for classifier-free guidance
|
| inpaint_strength |
number
|
0.35
Max: 1 |
Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image
|
| inpaint_lora_scale |
number
|
0.6
Max: 1 |
LoRA additive scale. Only applicable on trained models.
|
| inpaint_controlnet_conditioning_scale |
number
|
0.75
Max: 4 |
How strong the controlnet conditioning is
|
| inpaint_controlnet_start |
number
|
0
Max: 1 |
When controlnet conditioning starts
|
| inpaint_controlnet_end |
number
|
1
Max: 1 |
When controlnet conditioning ends
|
{
"type": "object",
"title": "Input",
"properties": {
"mask": {
"type": "string",
"title": "Mask",
"format": "uri",
"x-order": 4,
"description": "Input mask for inpaint mode. Black areas will be preserved, white areas will be inpainted."
},
"seed": {
"type": "integer",
"title": "Seed",
"x-order": 12,
"description": "Random seed. Leave blank to randomize the seed"
},
"image": {
"type": "string",
"title": "Image",
"format": "uri",
"x-order": 3,
"description": "Input image for img2img or inpaint mode"
},
"width": {
"type": "integer",
"title": "Width",
"default": 1024,
"x-order": 5,
"description": "Width of output image"
},
"height": {
"type": "integer",
"title": "Height",
"default": 1024,
"x-order": 6,
"description": "Height of output image"
},
"prompt": {
"type": "string",
"title": "Prompt",
"default": "An astronaut riding a rainbow unicorn",
"x-order": 1,
"description": "Input prompt"
},
"refine": {
"enum": [
"no_refiner",
"expert_ensemble_refiner",
"base_image_refiner"
],
"type": "string",
"title": "refine",
"description": "Which refine style to use",
"default": "no_refiner",
"x-order": 13
},
"fix_face": {
"type": "boolean",
"title": "Fix Face",
"default": false,
"x-order": 23,
"description": "Fix the face in the image"
},
"scheduler": {
"enum": [
"DDIM",
"DPMSolverMultistep",
"HeunDiscrete",
"DPM++SDEKarras",
"K_EULER_ANCESTRAL",
"K_EULER",
"PNDM"
],
"type": "string",
"title": "scheduler",
"description": "scheduler",
"default": "K_EULER",
"x-order": 8
},
"lora_scale": {
"type": "number",
"title": "Lora Scale",
"default": 0.6,
"maximum": 1,
"minimum": 0,
"x-order": 17,
"description": "LoRA additive scale. Only applicable on trained models."
},
"pose_image": {
"type": "string",
"title": "Pose Image",
"format": "uri",
"x-order": 19,
"description": "Pose image for controlnet"
},
"num_outputs": {
"type": "integer",
"title": "Num Outputs",
"default": 1,
"maximum": 4,
"minimum": 1,
"x-order": 7,
"description": "Number of images to output."
},
"face_padding": {
"type": "number",
"title": "Face Padding",
"default": 2,
"x-order": 25,
"description": "Amount of padding (as percentage) to add to the face bounding box."
},
"lora_weights": {
"type": "string",
"title": "Lora Weights",
"x-order": 0,
"description": "LoRA weights to use. Leave blank to use the default weights."
},
"refine_steps": {
"type": "integer",
"title": "Refine Steps",
"x-order": 15,
"description": "For base_image_refiner, the number of steps to refine, defaults to num_inference_steps"
},
"upscale_face": {
"type": "boolean",
"title": "Upscale Face",
"default": false,
"x-order": 27,
"description": "Upscale the face using GFPGAN"
},
"controlnet_end": {
"type": "number",
"title": "Controlnet End",
"default": 1,
"maximum": 1,
"minimum": 0,
"x-order": 22,
"description": "When controlnet conditioning ends"
},
"face_resize_to": {
"type": "integer",
"title": "Face Resize To",
"default": 1024,
"x-order": 26,
"description": "Resize the face bounding box to this size (in pixels)."
},
"guidance_scale": {
"type": "number",
"title": "Guidance Scale",
"default": 7.5,
"maximum": 50,
"minimum": 1,
"x-order": 10,
"description": "Scale for classifier-free guidance"
},
"inpaint_prompt": {
"type": "string",
"title": "Inpaint Prompt",
"default": "A photo of TOK",
"x-order": 28,
"description": "Input prompt"
},
"apply_watermark": {
"type": "boolean",
"title": "Apply Watermark",
"default": true,
"x-order": 16,
"description": "Applies a watermark to enable determining if an image is generated in downstream applications. If you have other provisions for generating or deploying images safely, you can use this to disable watermarking."
},
"high_noise_frac": {
"type": "number",
"title": "High Noise Frac",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 14,
"description": "For expert_ensemble_refiner, the fraction of noise to use"
},
"negative_prompt": {
"type": "string",
"title": "Negative Prompt",
"default": "",
"x-order": 2,
"description": "Input Negative Prompt"
},
"prompt_strength": {
"type": "number",
"title": "Prompt Strength",
"default": 0.8,
"maximum": 1,
"minimum": 0,
"x-order": 11,
"description": "Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image"
},
"controlnet_start": {
"type": "number",
"title": "Controlnet Start",
"default": 0,
"maximum": 1,
"minimum": 0,
"x-order": 21,
"description": "When controlnet conditioning starts"
},
"inpaint_strength": {
"type": "number",
"title": "Inpaint Strength",
"default": 0.35,
"maximum": 1,
"minimum": 0,
"x-order": 32,
"description": "Prompt strength when using img2img / inpaint. 1.0 corresponds to full destruction of information in image"
},
"mask_blur_amount": {
"type": "number",
"title": "Mask Blur Amount",
"default": 8,
"x-order": 24,
"description": "Amount of blur to apply to the mask."
},
"inpaint_lora_scale": {
"type": "number",
"title": "Inpaint Lora Scale",
"default": 0.6,
"maximum": 1,
"minimum": 0,
"x-order": 33,
"description": "LoRA additive scale. Only applicable on trained models."
},
"num_inference_steps": {
"type": "integer",
"title": "Num Inference Steps",
"default": 50,
"maximum": 500,
"minimum": 1,
"x-order": 9,
"description": "Number of denoising steps"
},
"disable_safety_checker": {
"type": "boolean",
"title": "Disable Safety Checker",
"default": true,
"x-order": 18,
"description": "Disable safety checker for generated images. This feature is only available through the API. See [https://replicate.com/docs/how-does-replicate-work#safety](https://replicate.com/docs/how-does-replicate-work#safety)"
},
"inpaint_controlnet_end": {
"type": "number",
"title": "Inpaint Controlnet End",
"default": 1,
"maximum": 1,
"minimum": 0,
"x-order": 36,
"description": "When controlnet conditioning ends"
},
"inpaint_guidance_scale": {
"type": "number",
"title": "Inpaint Guidance Scale",
"default": 3,
"maximum": 50,
"minimum": 1,
"x-order": 31,
"description": "Scale for classifier-free guidance"
},
"inpaint_negative_prompt": {
"type": "string",
"title": "Inpaint Negative Prompt",
"default": "",
"x-order": 29,
"description": "Input Negative Prompt"
},
"inpaint_controlnet_start": {
"type": "number",
"title": "Inpaint Controlnet Start",
"default": 0,
"maximum": 1,
"minimum": 0,
"x-order": 35,
"description": "When controlnet conditioning starts"
},
"inpaint_num_inference_steps": {
"type": "integer",
"title": "Inpaint Num Inference Steps",
"default": 25,
"maximum": 500,
"minimum": 1,
"x-order": 30,
"description": "Number of denoising steps"
},
"controlnet_conditioning_scale": {
"type": "number",
"title": "Controlnet Conditioning Scale",
"default": 0.75,
"maximum": 4,
"minimum": 0,
"x-order": 20,
"description": "How strong the controlnet conditioning is"
},
"inpaint_controlnet_conditioning_scale": {
"type": "number",
"title": "Inpaint Controlnet Conditioning Scale",
"default": 0.75,
"maximum": 4,
"minimum": 0,
"x-order": 34,
"description": "How strong the controlnet conditioning is"
}
}
}
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"
}