Image to Image V2

POST

img2img

object

extra

object

enable_nsfw_detection

boolean

nsfw_detection_level

integer

enable_progress_info

object

response_image_type

string

prompt

object

negative_prompt

object

sampler_name

object

batch_size

object

n_iter

object

steps

object

cfg_scale

object

seed

object

height

integer

width

integer

model_name

string

init_images

array

denoising_strength

object

restore_faces

object

sd_vae

object

clip_skip

object

mask

string

mask_blur

integer

resize_mode

object

image_cfg_scale

object

inpainting_fill

object

inpaint_full_res

object

inpaint_full_res_padding

object

inpainting_mask_invert

integer

initial_noise_multiplier

number

img_expire_ttl

integer

sd_refiner

object

checkpoint

string

switch_at

number

controlnet_units

object

model

string

weight

object

input_image

string

module

string

control_mode

object

mask

object

resize_mode

object

processor_res

object

threshold_a

object

threshold_b

object

guidance_start

object

guidance_end

object

pixel_perfect

object

The Image-to-Image V2 API is deprecated and will be removed in the future. Please migrate to Image-to-Image V3.

POST Image to Image V2

This is the image-to-image endpoint. Only a task_id will be returned. You should use the task_id to call the /v2/progress API endpoint in order to retrieve the image generation results. The output is provided in the format of “image/png”. We will gradually phase out the V2 endpoints, and it is recommended to use the V3 endpoints to generate images.

Request Headers

Authorization

string

required

Request Body

extra

object

prompt

string¦null

required

Positive prompt words, separated by commas. If you want to use LoRA, you can call the /v3/model endpoint with the parameter filter.types=lora to retrieve the sd_name_in_api field as the model_name. Remember that the format for LoRA models is <lora:$sd_name:$weight>.

negative_prompt

string¦null

Negative prompt words, separated by commas.

sampler_name

string¦null

required

This denoising process is called sampling because Stable Diffusion generates a new sample image at each step.
Enum: 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++ 2M, DPM++ SDE, DPM++ 2M SDE, DPM++ 2M SDE Heun, 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

batch_size

integer¦null

required

Number of images generated in a single generation. Range: [0, 8]

n_iter

integer¦null

required

Number of generations. Range: [0, 8]

steps

integer¦null

required

Think of steps as iterations of the image creation process. Range: (0, 50]

cfg_scale

number¦null

required

This setting indicates how closely Stable Diffusion will adhere to your prompt. Range: (0, 30]

seed

integer¦null

A seed is a number from which Stable Diffusion generates noise.

height

integer

required

Height of the image. Range: (0, 2048]

width

integer

required

Width of the image. Range: (0, 2048]

model_name

string

required

Name of the stable diffusion model. You can call the /v3/model endpoint with the parameter filter.types=checkpoint to retrieve the sd_name_in_api field as the model_name.

init_images

string[]

required

denoising_strength

number¦null

Indicates how much to transform the reference init_images. Must be between 0 and 1. init_images will be used as a starting point, with more noise added as the strength increases. The number of denoising steps depends on the amount of noise initially added. When denoising_strength is 1, added noise will be maximum, and the denoising process will run for the full number of iterations specified in steps. A value of 1, therefore, essentially ignores init_images.

restore_faces

boolean¦null

Enable Stable Diffusion restore faces plugin.

sd_vae

string¦null

VAE(Variational Auto Encoder),sd_vae can be access in api /v3/model with query params filter.types=vae to retrieve the sd_name field as the sd_vae.

clip_skip

integer¦null

This parameter indicates the number of layers to stop from the bottom during optimization, so clip_skip on 2 would mean, that in SD1.x model where the CLIP has 12 layers, you would stop at 10th layer.

mask

string

Base64 of png, mask of inpaintings.

mask_blur

integer

Sets the degree of blurring of the border of the filled area.

resize_mode

integer¦null

Resize mode, while, 0 represent Just resize, 1 represent Crop and resize, 2 represent Resize and fill, 3 represent Just resize(latent upscale)
Enum: 0, 1, 2, 3

image_cfg_scale

integer¦null

Image cfg scale

inpainting_fill

integer¦null

How to redraw the filled areas. 0: fill, Redraw based on the surrounding color 1: original, Redraw based on the original image 2: latent noise, Change back to noise and redraw 3: latent nothing, based on the color of the filled area
Enum: 0, 1, 2, 3

inpaint_full_res

integer¦null

Specify whether to apply or protect the filled area. 0: Whole picture the entire illustration and change the filled parts. 1: Only masked Draws only the filled area and then restores the original image.
Enum: 0, 1

inpaint_full_res_padding

integer¦null

This settings controls how many additional pixels can be used as a reference point for only masked mode. You can increase the amount if you are having trouble with producing a proper image. This is a numerical value for how much margin to set when Only masked is selected. The downside of increasing this value is that it will decrease the quality of output. Guidance: https://civitai.com/articles/161/basic-inpainting-guide

inpainting_mask_invert

integer

Specify whether to invert the mask. 0 - Inpaint Masked 1 - Inpaint Not Masked
Enum: 0, 1

initial_noise_multiplier

number

Noise multiplier for img2img in settings. This scaling factor is applied to the random latent tensor for img2img. Lowering it reduces flickering.

img_expire_ttl

integer

Image storage time (seconds). Range [0, 604800]

sd_refiner

object

Refiner infos to enhances the image details.

controlnet_units

object[]¦null

ControlNet.

model

string

required

Model to use on the image passed to this unit before using it for conditioning. ***Controlnets for SD 1.5: control_v11e_sd15_ip2p, control_v11e_sd15_shuffle, control_v11f1e_sd15_tile, control_v11f1p_sd15_depth, control_v11p_sd15_canny, control_v11p_sd15_inpaint, control_v11p_sd15_lineart, control_v11p_sd15_mlsd, control_v11p_sd15_normalbae, control_v11p_sd15_openpose, control_v11p_sd15_scribble, control_v11p_sd15_seg, control_v11p_sd15_softedge, control_v11p_sd15s2_lineart_anime, ip-adapter-plus-face_sd15, ip-adapter_sd15_plus, ip-adapter_sd15; ***Controlnets for SDXL: t2i-adapter_diffusers_xl_canny, t2i-adapter_diffusers_xl_depth_midas, t2i-adapter_diffusers_xl_depth_zoe, t2i-adapter_diffusers_xl_lineart, t2i-adapter_diffusers_xl_openpose, t2i-adapter_diffusers_xl_sketch, t2i-adapter_xl_canny, t2i-adapter_xl_openpose, t2i-adapter_xl_sketch, ip-adapter_xl

weight

number¦null

required

weight of this unit. defaults to 1

input_image

string

required

base64 of input image

module

string

required

preprocessor to use on the image passed to this unit before using it for conditioning.
Enum: none, canny, depth, depth_leres, depth_leres++, hed, hed_safe, mediapipe_face, mlsd, normal_map, openpose, openpose_hand, openpose_face, openpose_faceonly, openpose_full, clip_vision, color, pidinet, pidinet_safe, pidinet_sketch, pidinet_scribble, scribble_xdog, scribble_hed, segmentation, threshold, depth_zoe, normal_bae, oneformer_coco, oneformer_ade20k, lineart, lineart_coarse, lineart_anime, lineart_standard, shuffle, tile_resample, invert, lineart_anime_denoise, reference_only, reference_adain, reference_adain+attn, inpaint, inpaint_only, inpaint_only+lama, tile_colorfix, tile_colorfix+sharp, depth_anything

control_mode

integer¦null

required

0 for Balanced,1 for My prompt is more important 2 for ControlNet is more important
Enum: 0, 1, 2

mask

string¦null

Base64 of mask images, support jpg, jpeg and png format images. Only take effect when controlnet_units.model set to control_v11p_sd15_inpaint.

resize_mode

integer¦null

How to resize the input image so as to fit the output resolution of the generation.
Enum: 0, 1, 2

processor_res

integer¦null

Resolution of the preprocessor.

threshold_a

integer¦null

First parameter of the preprocessor, only takes effect when preprocessor accepts arguments.

threshold_b

integer¦null

Second parameter of the preprocessor, only takes effect when preprocessor accepts arguments.

guidance_start

number¦null

ratio of generation where this unit starts to have an effect.

guidance_end

number¦null

ratio of generation where this unit stops to have an effect.

pixel_perfect

boolean¦null

Enable pixel-perfect preprocessor, when set to false, it means not to resize images.

Response

code

integer

msg

string

data

object

Example

request

curl --location 'https://api.novita.ai/v2/img2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
  'extra': {
    'enable_nsfw_detection': false,
    'nsfw_detection_level': 0,
    'enable_progress_info': false
  },
  'prompt': 'Photographic of a woman sitting at a cafe. 35mm photograph, film, bokeh, professional, 4k, highly detailed',
  'negative_prompt': 'ng_deepnegative_v1_75t, badhandv4, (worst quality:2), (low quality:2), (normal quality:2), lowres, ((monochrome)), ((grayscale)), watermark',
  'sampler_name': 'Euler a',
  'batch_size': 1,
  'n_iter': 1,
  'steps': 20,
  'cfg_scale': 7,
  'seed': -1,
  'height': 1024,
  'width': 1024,
  'model_name': 'sd_xl_base_1.0.safetensors',
  'init_images': [
    '{{base64 encoded image}}'
  ],
  'denoising_strength': 0.5,
  'restore_faces': false,
  'sd_vae': 'sdxl_vae.safetensors',
  'clip_skip': 1,
  'mask': '',
  'mask_blur': null,
  'resize_mode': 0,
  'image_cfg_scale': null,
  'inpainting_fill': 0,
  'inpaint_full_res': 0,
  'inpaint_full_res_padding': null,
  'inpainting_mask_invert': 0,
  'initial_noise_multiplier': null,
  'img_expire_ttl': null,
  'sd_refiner': {
    'checkpoint': 'sd_xl_refiner_1.0.safetensors',
    'switch_at': 1
  },
  'controlnet_units': [
    {
      'model': 't2i-adapter_xl_sketch',
      'weight': 0.5,
      'input_image': '{{base64 encoded image}}',
      'module': 'none',
      'control_mode': 0,
      'mask': '',
      'resize_mode': 0,
      'processor_res': null,
      'threshold_a': null,
      'threshold_b': null,
      'guidance_start': null,
      'guidance_end': null,
      'pixel_perfect': false,
      'lowvram': true
    }
  ],
  'controlnet_no_detectmap': true
}'

response

{
  "code": 0,
  "msg": "",
  "data": {
    "task_id": "d4cf3973-8414-4a5e-aa6f-ef54caf73662"
  }
}

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Text to Image V2 Progress

Basic

Model APIs

GPUs

POST Image to Image V2

Request Headers

Request Body

Response

Example

Basic

Model APIs

GPUs

​POST Image to Image V2

​Request Headers

​Request Body

​Response

​Example

POST Image to Image V2

Request Headers

Request Body

Response

Example