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usamaehsan/controlnet-x-ip-adapter-realistic-vision-v5
Inpainting || multi-controlnet || single-controlnet || ip-adapter || ip adapter face || ip adapter plus || No ip adapter
Capabilities
Cost
Community model (estimated from hardware time)
Input Parameters
| Name | Type | Description | Default | Constraints |
|---|---|---|---|---|
prompt * | string | Prompt - using compel, use +++ to increase words weight:: doc: https://github.com/damian0815/compel/tree/main/doc || https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#attention-weighting | — | — |
add_more_detail_lora_scale | number | Scale/ weight of more_details lora, more scale = more details, disabled on 0 | 0.5 | — |
brightness_conditioning_scale | number | Conditioning scale for brightness controlnet | 1 | — |
brightness_image | string (uri) | Control image for brightness controlnet | — | — |
color_temprature_slider_lora_weight | number | disabled on 0 | 0 | — |
detail_tweaker_lora_weight | number | disabled on 0 | 0 | — |
disable_safety_check | boolean | Disable safety check. Use at your own risk! | false | — |
epi_noise_offset_lora_weight | number | disabled on 0 | 0 | — |
eta | number | Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise | 0 | — |
film_grain_lora_weight | number | disabled on 0 | 0 | — |
guess_mode | boolean | In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended. | false | — |
guidance_scale | number | Scale for classifier-free guidance | 7 | min: 0.1, max: 30 |
img2img_image | string (uri) | Image2image image | — | — |
img2img_strength | number | img2img strength, does not work when inpainting image is given, 0.1-same image, 0.99-complete destruction of image | 0.5 | — |
inpainting_conditioning_scale | number | Conditioning scale for inpaint controlnet | 1 | — |
inpainting_image | string (uri) | Control image for inpainting controlnet | — | — |
inpainting_strength | number | inpainting strength | 1 | — |
int_kwargs | string | — | "" | — |
ip_adapter_ckpt | string | IP Adapter checkpoint | "ip-adapter_sd15.bin" | ip-adapter_sd15.bin ip-adapter-plus_sd15.bin ip-adapter-plus-face_sd15.bin |
ip_adapter_image | string (uri) | IP Adapter image | — | — |
ip_adapter_weight | number | IP Adapter weight | 1 | — |
lineart_conditioning_scale | number | Conditioning scale for canny controlnet | 1 | — |
lineart_image | string (uri) | Control image for canny controlnet | — | — |
mask_image | string (uri) | mask image for inpainting controlnet | — | — |
max_height | integer | Max height/Resolution of image | 512 | — |
max_width | integer | Max width/Resolution of image | 512 | — |
negative_auto_mask_text | string | // seperated list of objects you dont want to mask - 'hairs // eyes // cloth' | — | — |
negative_prompt | string | Negative prompt - using compel, use +++ to increase words weight//// negative-embeddings available ///// FastNegativeV2 , boring_e621_v4 , verybadimagenegative_v1 || to use them, write their keyword in negative prompt | "Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality" | — |
num_inference_steps | integer | Steps to run denoising | 20 | — |
num_outputs | integer | Number of images to generate | 1 | min: 1, max: 10 |
positive_auto_mask_text | string | // seperated list of objects for mask, AI will auto create mask of these objects, if mask text is given, mask image will not work - 'hairs // eyes // cloth' | — | — |
scheduler | string | Choose a scheduler. | "DDIM" | DDIM DPMSolverMultistep HeunDiscrete K_EULER_ANCESTRAL K_EULER KLMS PNDM UniPCMultistep KDPM2DiscreteScheduler KDPM2AncestralDiscreteScheduler DDPMScheduler DEISMultistepScheduler |
scribble_conditioning_scale | number | Conditioning scale for scribble controlnet | 1 | — |
scribble_image | string (uri) | Control image for scribble controlnet | — | — |
seed | integer | Seed | — | — |
sorted_controlnets | string | Comma seperated string of controlnet names, list of names: tile, inpainting, lineart,depth ,scribble , brightness /// example value: tile, inpainting, lineart | "lineart, tile, inpainting" | — |
tile_conditioning_scale | number | Conditioning scale for tile controlnet | 1 | — |
tile_image | string (uri) | Control image for tile controlnet | — | — |
prompt required string Prompt - using compel, use +++ to increase words weight:: doc: https://github.com/damian0815/compel/tree/main/doc || https://invoke-ai.github.io/InvokeAI/features/PROMPTS/#attention-weighting
add_more_detail_lora_scale number Scale/ weight of more_details lora, more scale = more details, disabled on 0
0.5 brightness_conditioning_scale number Conditioning scale for brightness controlnet
1 brightness_image string Control image for brightness controlnet
color_temprature_slider_lora_weight number disabled on 0
0 detail_tweaker_lora_weight number disabled on 0
0 disable_safety_check boolean Disable safety check. Use at your own risk!
false epi_noise_offset_lora_weight number disabled on 0
0 eta number Controls the amount of noise that is added to the input data during the denoising diffusion process. Higher value -> more noise
0 film_grain_lora_weight number disabled on 0
0 guess_mode boolean In this mode, the ControlNet encoder will try best to recognize the content of the input image even if you remove all prompts. The `guidance_scale` between 3.0 and 5.0 is recommended.
false guidance_scale number Scale for classifier-free guidance
7 min: 0.1, max: 30 img2img_image string Image2image image
img2img_strength number img2img strength, does not work when inpainting image is given, 0.1-same image, 0.99-complete destruction of image
0.5 inpainting_conditioning_scale number Conditioning scale for inpaint controlnet
1 inpainting_image string Control image for inpainting controlnet
inpainting_strength number inpainting strength
1 int_kwargs string "" ip_adapter_ckpt string IP Adapter checkpoint
"ip-adapter_sd15.bin" ip_adapter_image string IP Adapter image
ip_adapter_weight number IP Adapter weight
1 lineart_conditioning_scale number Conditioning scale for canny controlnet
1 lineart_image string Control image for canny controlnet
mask_image string mask image for inpainting controlnet
max_height integer Max height/Resolution of image
512 max_width integer Max width/Resolution of image
512 negative_auto_mask_text string // seperated list of objects you dont want to mask - 'hairs // eyes // cloth'
negative_prompt string Negative prompt - using compel, use +++ to increase words weight//// negative-embeddings available ///// FastNegativeV2 , boring_e621_v4 , verybadimagenegative_v1 || to use them, write their keyword in negative prompt
"Longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality" num_inference_steps integer Steps to run denoising
20 num_outputs integer Number of images to generate
1 min: 1, max: 10 positive_auto_mask_text string // seperated list of objects for mask, AI will auto create mask of these objects, if mask text is given, mask image will not work - 'hairs // eyes // cloth'
scheduler string Choose a scheduler.
"DDIM" scribble_conditioning_scale number Conditioning scale for scribble controlnet
1 scribble_image string Control image for scribble controlnet
seed integer Seed
sorted_controlnets string Comma seperated string of controlnet names, list of names: tile, inpainting, lineart,depth ,scribble , brightness /// example value: tile, inpainting, lineart
"lineart, tile, inpainting" tile_conditioning_scale number Conditioning scale for tile controlnet
1 tile_image string Control image for tile controlnet
50ac06bb9bcf Updated: 2/26/2026 674.7K runs