mlscade / stable_diffusion_no_ui_inpaint

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Run mlscade/stable_diffusion_no_ui_inpaint 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
generation_type
string (enum)
img2img

Options:

img2img, postprocess

Generation mode
clip_stop_at_last_layers
integer
2

Min: 1

Max: 12

Clip skip
upload_lora
string
Upload LoRA
prompt
string
Prompt
negative_prompt
string
(deformed, distorted, disfigured:1.3), (naked, nude:1.5), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation
Negative prompt
image
string
Input image
image_mask
string
Mask
mask_blur
integer
4
Mask blur
resize_mode
string (enum)
Just resize

Options:

Just resize, Resize and fill

Resize mode
inpainting_mask_invert
string (enum)
Inpaint masked

Options:

Inpaint masked, Inpaint not masked

Mask mode
inpainting_fill
string (enum)
Original

Options:

Fill, Original, Latent noise

Masked content
inpaint_full_res
string (enum)
Whole picture

Options:

Whole picture, Only masked

Inpaint area
inpaint_full_res_padding
integer
32
Only masked padding, pixels
cfg_scale
number
7
CFG scale
denoising_strength
number
0.75
[HR] Denoising strength
seed
integer
Seed. Leave blank for random generation
width
integer
512
Width
height
integer
512
Height
num_outputs
integer
1

Min: 1

Max: 4

Batch size [Doesn't work in postprocess mode].
sampler
string (enum)
Euler a

Options:

DPM++ 2M Karras, DPM++ SDE Karras, DPM++ 2M SDE Exponential, DPM++ 2M SDE Karras, Euler a, Euler, LMS, Heun, DPM2, DPM2 a, DPM++ 2S a, DPM++ SDE, DPM++ 2M SDE, DPM++ 2M SDE Heun Karras, DPM++ 2M SDE Heun Exponential, DPM++ 3M SDE, DPM++ 3M SDE Karras, DPM++ 3M SDE Exponential, DPM fast, DPM adaptive, LMS Karras, DPM2 Karras, DPM2 a Karras, DPM++ 2S a Karras, Restart, DDIM, PLMS, UniPC

Sampling method
sampler_steps
integer
20

Min: 1

Max: 50

Sampling steps [Doesn't work in postprocess mode].
ad_enabled
boolean
False
[adetailer] Enable
ad_model
string (enum)
face_yolov8s

Options:

face_yolov8n, face_yolov8s, hand_yolov8n, person_yolov8n-seg, person_yolov8s-seg, mediapipe_face_full, mediapipe_face_short, mediapipe_face_mesh, mediapipe_face_mesh_eyes_only, deepfashion2_yolov8s-seg, Без модели

[adetailer] ADetailer model
ad_prompt
string
[adetailer] ADetailer prompt
ad_negative_prompt
string
[adetailer] ADetailer negative prompt
ad_use_sampler
boolean
True
[adetailer] Use separate sampler
ad_sampler
string (enum)
Euler a

Options:

DPM++ 2M Karras, DPM++ SDE Karras, DPM++ 2M SDE Exponential, DPM++ 2M SDE Karras, Euler a, Euler, LMS, Heun, DPM2, DPM2 a, DPM++ 2S a, DPM++ SDE, DPM++ 2M SDE, DPM++ 2M SDE Heun Karras, DPM++ 2M SDE Heun Exponential, DPM++ 3M SDE, DPM++ 3M SDE Karras, DPM++ 3M SDE Exponential, DPM fast, DPM adaptive, LMS Karras, DPM2 Karras, DPM2 a Karras, DPM++ 2S a Karras, Restart, DDIM, PLMS, UniPC

[adetailer] ADetailer sampler
ad_confidence
number
0.3
[adetailer] Detection model confidence threshold
ad_dilate_erode
integer
4
[adetailer] Mask erosion (-) / dilation (+)
ad_mask_blur
integer
4
[adetailer] Inpaint mask blur
ad_mask_merge_mode
string (enum)
None

Options:

None, Merge, Merge and Invert

[adetailer] Mask merge mode
ad_denoising_strength
number
0.4
[adetailer] Inpaint denoising strength
ad_inpaint_only_masked
boolean
True
[adetailer] Inpaint only masked
ad_inpaint_only_masked_padding
integer
32
[adetailer] Inpaint only masked padding, pixels
ad_use_inpaint_width_height
boolean
False
[adetailer] Use separate width/height
ad_inpaint_width
integer
512
[adetailer] Inpaint width
ad_inpaint_height
integer
512
[adetailer] Inpaint height

Output schema

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

Schema 
{
  "type": "object",
  "title": "Output",
  "required": [
    "images",
    "seeds",
    "prompt"
  ],
  "properties": {
    "seeds": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "title": "Seeds"
    },
    "images": {
      "type": "array",
      "items": {
        "type": "string",
        "format": "uri"
      },
      "title": "Images"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt"
    }
  }
}