prompthunt / cog-sd15-inference-embeds

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Run prompthunt/cog-sd15-inference-embeds 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
weights
string
LoRA weights to use. Leave blank to use the default weights.
prompt
string
An photo of cjw man
Input prompt
negative_prompt
string
Specify things to not see in the output. Supported embeddings: realisticvision-negative-embedding, EasyNegative, FastNegativeV2, BadDream, ng_deepnegative_v1_75t, UnrealisticDream, negative_hand-neg, CyberRealistic_Negative-neg, badhandv4
root_prompt
string
crisp details, neutral expression, high-definition, sharp focus, ambient lighting, masterpiece, cinematic light, cinematic lighting, ultrarealistic, photorealistic, 8k, raw photo, realistic, sharp focus on eyes, symmetrical eyes, intact eyes, hyperrealistic, highest quality, best quality, highly detailed, masterpiece, best quality, extremely detailed 8k wallpaper, masterpiece, best quality, ultra-detailed, best shadow, detailed background, detailed face, detailed eyes, high contrast, best illumination, detailed face, dulux, caustic, dynamic angle, detailed glow. dramatic lighting. highly detailed, insanely detailed hair, symmetrical, intricate details, professionally retouched, 8k high definition. strong bokeh. award winning photo.
Prompt added on top of every prediction
root_negative_prompt
string
old, multiple heads, 2 heads, elongated body, double image, 2 faces, multiple people, double head, <cyberrealistic-neg>, <badhandv4>, <negative-hand>, <baddream> , (nsfw), nsfw, nsfw, nsfw, nude, nude, nude, porn, porn, porn, naked, naked, nude, porn, frilly, frilled, lacy, ruffled, armpit hair, victorian, (sunglasses), (sunglasses), (deformed iris, deformed pupils, semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime:1.4), text, close up, cropped, out of frame, worst quality, low quality, jpeg artifacts, ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, dehydrated, bad anatomy, bad proportions, extra limbs, cloned face, disfigured, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, fused fingers, too many fingers, long neck
Input 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
512
Width of output image
height
integer
512
Height of output image
num_outputs
integer
1

Min: 1

Max: 40

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
should_swap_face
boolean
False
Should swap face
source_image
string
Source image for face swap
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
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
inpaint_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
512
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 cjw man
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
show_debug_images
boolean
False
Show debug images
upscale_final_image
boolean
False
Upscale the final image using GFPGAN
upscale_scale
number
2
Upscale scale
codeformer_fidelity
number
0.7

Max: 1

Codeformer fidelity

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"
}