Image to Image V2

curl --request POST \
  --url https://api.novita.ai/v2/img2img \
  --header 'Authorization: <authorization>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "extra": {
    "enable_nsfw_detection": true,
    "nsfw_detection_level": 123,
    "enable_progress_info": {},
    "response_image_type": "<string>"
  },
  "prompt": {},
  "negative_prompt": {},
  "sampler_name": {},
  "batch_size": {},
  "n_iter": {},
  "steps": {},
  "cfg_scale": {},
  "seed": {},
  "height": 123,
  "width": 123,
  "model_name": "<string>",
  "init_images": [
    "<string>"
  ],
  "denoising_strength": {},
  "restore_faces": {},
  "sd_vae": {},
  "clip_skip": {},
  "mask": "<string>",
  "mask_blur": 123,
  "resize_mode": {},
  "image_cfg_scale": {},
  "inpainting_fill": {},
  "inpaint_full_res": {},
  "inpaint_full_res_padding": {},
  "inpainting_mask_invert": 123,
  "initial_noise_multiplier": 123,
  "img_expire_ttl": 123,
  "sd_refiner": {
    "checkpoint": "<string>",
    "switch_at": 123
  },
  "controlnet_units": {
    "model": "<string>",
    "weight": {},
    "input_image": "<string>",
    "module": "<string>",
    "control_mode": {},
    "mask": {},
    "resize_mode": {},
    "processor_res": {},
    "threshold_a": {},
    "threshold_b": {},
    "guidance_start": {},
    "guidance_end": {},
    "pixel_perfect": {}
  }
}
'

import requests

url = "https://api.novita.ai/v2/img2img"

payload = {
    "extra": {
        "enable_nsfw_detection": True,
        "nsfw_detection_level": 123,
        "enable_progress_info": {},
        "response_image_type": "<string>"
    },
    "prompt": {},
    "negative_prompt": {},
    "sampler_name": {},
    "batch_size": {},
    "n_iter": {},
    "steps": {},
    "cfg_scale": {},
    "seed": {},
    "height": 123,
    "width": 123,
    "model_name": "<string>",
    "init_images": ["<string>"],
    "denoising_strength": {},
    "restore_faces": {},
    "sd_vae": {},
    "clip_skip": {},
    "mask": "<string>",
    "mask_blur": 123,
    "resize_mode": {},
    "image_cfg_scale": {},
    "inpainting_fill": {},
    "inpaint_full_res": {},
    "inpaint_full_res_padding": {},
    "inpainting_mask_invert": 123,
    "initial_noise_multiplier": 123,
    "img_expire_ttl": 123,
    "sd_refiner": {
        "checkpoint": "<string>",
        "switch_at": 123
    },
    "controlnet_units": {
        "model": "<string>",
        "weight": {},
        "input_image": "<string>",
        "module": "<string>",
        "control_mode": {},
        "mask": {},
        "resize_mode": {},
        "processor_res": {},
        "threshold_a": {},
        "threshold_b": {},
        "guidance_start": {},
        "guidance_end": {},
        "pixel_perfect": {}
    }
}
headers = {
    "Authorization": "<authorization>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: '<authorization>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    extra: {
      enable_nsfw_detection: true,
      nsfw_detection_level: 123,
      enable_progress_info: {},
      response_image_type: '<string>'
    },
    prompt: {},
    negative_prompt: {},
    sampler_name: {},
    batch_size: {},
    n_iter: {},
    steps: {},
    cfg_scale: {},
    seed: {},
    height: 123,
    width: 123,
    model_name: '<string>',
    init_images: ['<string>'],
    denoising_strength: {},
    restore_faces: {},
    sd_vae: {},
    clip_skip: {},
    mask: '<string>',
    mask_blur: 123,
    resize_mode: {},
    image_cfg_scale: {},
    inpainting_fill: {},
    inpaint_full_res: {},
    inpaint_full_res_padding: {},
    inpainting_mask_invert: 123,
    initial_noise_multiplier: 123,
    img_expire_ttl: 123,
    sd_refiner: {checkpoint: '<string>', switch_at: 123},
    controlnet_units: {
      model: '<string>',
      weight: {},
      input_image: '<string>',
      module: '<string>',
      control_mode: {},
      mask: {},
      resize_mode: {},
      processor_res: {},
      threshold_a: {},
      threshold_b: {},
      guidance_start: {},
      guidance_end: {},
      pixel_perfect: {}
    }
  })
};

fetch('https://api.novita.ai/v2/img2img', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.novita.ai/v2/img2img",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'extra' => [
        'enable_nsfw_detection' => true,
        'nsfw_detection_level' => 123,
        'enable_progress_info' => [
                
        ],
        'response_image_type' => '<string>'
    ],
    'prompt' => [
        
    ],
    'negative_prompt' => [
        
    ],
    'sampler_name' => [
        
    ],
    'batch_size' => [
        
    ],
    'n_iter' => [
        
    ],
    'steps' => [
        
    ],
    'cfg_scale' => [
        
    ],
    'seed' => [
        
    ],
    'height' => 123,
    'width' => 123,
    'model_name' => '<string>',
    'init_images' => [
        '<string>'
    ],
    'denoising_strength' => [
        
    ],
    'restore_faces' => [
        
    ],
    'sd_vae' => [
        
    ],
    'clip_skip' => [
        
    ],
    'mask' => '<string>',
    'mask_blur' => 123,
    'resize_mode' => [
        
    ],
    'image_cfg_scale' => [
        
    ],
    'inpainting_fill' => [
        
    ],
    'inpaint_full_res' => [
        
    ],
    'inpaint_full_res_padding' => [
        
    ],
    'inpainting_mask_invert' => 123,
    'initial_noise_multiplier' => 123,
    'img_expire_ttl' => 123,
    'sd_refiner' => [
        'checkpoint' => '<string>',
        'switch_at' => 123
    ],
    'controlnet_units' => [
        'model' => '<string>',
        'weight' => [
                
        ],
        'input_image' => '<string>',
        'module' => '<string>',
        'control_mode' => [
                
        ],
        'mask' => [
                
        ],
        'resize_mode' => [
                
        ],
        'processor_res' => [
                
        ],
        'threshold_a' => [
                
        ],
        'threshold_b' => [
                
        ],
        'guidance_start' => [
                
        ],
        'guidance_end' => [
                
        ],
        'pixel_perfect' => [
                
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <authorization>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.novita.ai/v2/img2img"

	payload := strings.NewReader("{\n  \"extra\": {\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123,\n    \"enable_progress_info\": {},\n    \"response_image_type\": \"<string>\"\n  },\n  \"prompt\": {},\n  \"negative_prompt\": {},\n  \"sampler_name\": {},\n  \"batch_size\": {},\n  \"n_iter\": {},\n  \"steps\": {},\n  \"cfg_scale\": {},\n  \"seed\": {},\n  \"height\": 123,\n  \"width\": 123,\n  \"model_name\": \"<string>\",\n  \"init_images\": [\n    \"<string>\"\n  ],\n  \"denoising_strength\": {},\n  \"restore_faces\": {},\n  \"sd_vae\": {},\n  \"clip_skip\": {},\n  \"mask\": \"<string>\",\n  \"mask_blur\": 123,\n  \"resize_mode\": {},\n  \"image_cfg_scale\": {},\n  \"inpainting_fill\": {},\n  \"inpaint_full_res\": {},\n  \"inpaint_full_res_padding\": {},\n  \"inpainting_mask_invert\": 123,\n  \"initial_noise_multiplier\": 123,\n  \"img_expire_ttl\": 123,\n  \"sd_refiner\": {\n    \"checkpoint\": \"<string>\",\n    \"switch_at\": 123\n  },\n  \"controlnet_units\": {\n    \"model\": \"<string>\",\n    \"weight\": {},\n    \"input_image\": \"<string>\",\n    \"module\": \"<string>\",\n    \"control_mode\": {},\n    \"mask\": {},\n    \"resize_mode\": {},\n    \"processor_res\": {},\n    \"threshold_a\": {},\n    \"threshold_b\": {},\n    \"guidance_start\": {},\n    \"guidance_end\": {},\n    \"pixel_perfect\": {}\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "<authorization>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.novita.ai/v2/img2img")
  .header("Authorization", "<authorization>")
  .header("Content-Type", "application/json")
  .body("{\n  \"extra\": {\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123,\n    \"enable_progress_info\": {},\n    \"response_image_type\": \"<string>\"\n  },\n  \"prompt\": {},\n  \"negative_prompt\": {},\n  \"sampler_name\": {},\n  \"batch_size\": {},\n  \"n_iter\": {},\n  \"steps\": {},\n  \"cfg_scale\": {},\n  \"seed\": {},\n  \"height\": 123,\n  \"width\": 123,\n  \"model_name\": \"<string>\",\n  \"init_images\": [\n    \"<string>\"\n  ],\n  \"denoising_strength\": {},\n  \"restore_faces\": {},\n  \"sd_vae\": {},\n  \"clip_skip\": {},\n  \"mask\": \"<string>\",\n  \"mask_blur\": 123,\n  \"resize_mode\": {},\n  \"image_cfg_scale\": {},\n  \"inpainting_fill\": {},\n  \"inpaint_full_res\": {},\n  \"inpaint_full_res_padding\": {},\n  \"inpainting_mask_invert\": 123,\n  \"initial_noise_multiplier\": 123,\n  \"img_expire_ttl\": 123,\n  \"sd_refiner\": {\n    \"checkpoint\": \"<string>\",\n    \"switch_at\": 123\n  },\n  \"controlnet_units\": {\n    \"model\": \"<string>\",\n    \"weight\": {},\n    \"input_image\": \"<string>\",\n    \"module\": \"<string>\",\n    \"control_mode\": {},\n    \"mask\": {},\n    \"resize_mode\": {},\n    \"processor_res\": {},\n    \"threshold_a\": {},\n    \"threshold_b\": {},\n    \"guidance_start\": {},\n    \"guidance_end\": {},\n    \"pixel_perfect\": {}\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.novita.ai/v2/img2img")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = '<authorization>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"extra\": {\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123,\n    \"enable_progress_info\": {},\n    \"response_image_type\": \"<string>\"\n  },\n  \"prompt\": {},\n  \"negative_prompt\": {},\n  \"sampler_name\": {},\n  \"batch_size\": {},\n  \"n_iter\": {},\n  \"steps\": {},\n  \"cfg_scale\": {},\n  \"seed\": {},\n  \"height\": 123,\n  \"width\": 123,\n  \"model_name\": \"<string>\",\n  \"init_images\": [\n    \"<string>\"\n  ],\n  \"denoising_strength\": {},\n  \"restore_faces\": {},\n  \"sd_vae\": {},\n  \"clip_skip\": {},\n  \"mask\": \"<string>\",\n  \"mask_blur\": 123,\n  \"resize_mode\": {},\n  \"image_cfg_scale\": {},\n  \"inpainting_fill\": {},\n  \"inpaint_full_res\": {},\n  \"inpaint_full_res_padding\": {},\n  \"inpainting_mask_invert\": 123,\n  \"initial_noise_multiplier\": 123,\n  \"img_expire_ttl\": 123,\n  \"sd_refiner\": {\n    \"checkpoint\": \"<string>\",\n    \"switch_at\": 123\n  },\n  \"controlnet_units\": {\n    \"model\": \"<string>\",\n    \"weight\": {},\n    \"input_image\": \"<string>\",\n    \"module\": \"<string>\",\n    \"control_mode\": {},\n    \"mask\": {},\n    \"resize_mode\": {},\n    \"processor_res\": {},\n    \"threshold_a\": {},\n    \"threshold_b\": {},\n    \"guidance_start\": {},\n    \"guidance_end\": {},\n    \"pixel_perfect\": {}\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "code": 123,
  "msg": "<string>",
  "data": {
    "task_id": "<string>",
    "warn": "<string>"
  }
}

POST

img2img

Image to Image V2

curl --request POST \
  --url https://api.novita.ai/v2/img2img \
  --header 'Authorization: <authorization>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "extra": {
    "enable_nsfw_detection": true,
    "nsfw_detection_level": 123,
    "enable_progress_info": {},
    "response_image_type": "<string>"
  },
  "prompt": {},
  "negative_prompt": {},
  "sampler_name": {},
  "batch_size": {},
  "n_iter": {},
  "steps": {},
  "cfg_scale": {},
  "seed": {},
  "height": 123,
  "width": 123,
  "model_name": "<string>",
  "init_images": [
    "<string>"
  ],
  "denoising_strength": {},
  "restore_faces": {},
  "sd_vae": {},
  "clip_skip": {},
  "mask": "<string>",
  "mask_blur": 123,
  "resize_mode": {},
  "image_cfg_scale": {},
  "inpainting_fill": {},
  "inpaint_full_res": {},
  "inpaint_full_res_padding": {},
  "inpainting_mask_invert": 123,
  "initial_noise_multiplier": 123,
  "img_expire_ttl": 123,
  "sd_refiner": {
    "checkpoint": "<string>",
    "switch_at": 123
  },
  "controlnet_units": {
    "model": "<string>",
    "weight": {},
    "input_image": "<string>",
    "module": "<string>",
    "control_mode": {},
    "mask": {},
    "resize_mode": {},
    "processor_res": {},
    "threshold_a": {},
    "threshold_b": {},
    "guidance_start": {},
    "guidance_end": {},
    "pixel_perfect": {}
  }
}
'

import requests

url = "https://api.novita.ai/v2/img2img"

payload = {
    "extra": {
        "enable_nsfw_detection": True,
        "nsfw_detection_level": 123,
        "enable_progress_info": {},
        "response_image_type": "<string>"
    },
    "prompt": {},
    "negative_prompt": {},
    "sampler_name": {},
    "batch_size": {},
    "n_iter": {},
    "steps": {},
    "cfg_scale": {},
    "seed": {},
    "height": 123,
    "width": 123,
    "model_name": "<string>",
    "init_images": ["<string>"],
    "denoising_strength": {},
    "restore_faces": {},
    "sd_vae": {},
    "clip_skip": {},
    "mask": "<string>",
    "mask_blur": 123,
    "resize_mode": {},
    "image_cfg_scale": {},
    "inpainting_fill": {},
    "inpaint_full_res": {},
    "inpaint_full_res_padding": {},
    "inpainting_mask_invert": 123,
    "initial_noise_multiplier": 123,
    "img_expire_ttl": 123,
    "sd_refiner": {
        "checkpoint": "<string>",
        "switch_at": 123
    },
    "controlnet_units": {
        "model": "<string>",
        "weight": {},
        "input_image": "<string>",
        "module": "<string>",
        "control_mode": {},
        "mask": {},
        "resize_mode": {},
        "processor_res": {},
        "threshold_a": {},
        "threshold_b": {},
        "guidance_start": {},
        "guidance_end": {},
        "pixel_perfect": {}
    }
}
headers = {
    "Authorization": "<authorization>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: '<authorization>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    extra: {
      enable_nsfw_detection: true,
      nsfw_detection_level: 123,
      enable_progress_info: {},
      response_image_type: '<string>'
    },
    prompt: {},
    negative_prompt: {},
    sampler_name: {},
    batch_size: {},
    n_iter: {},
    steps: {},
    cfg_scale: {},
    seed: {},
    height: 123,
    width: 123,
    model_name: '<string>',
    init_images: ['<string>'],
    denoising_strength: {},
    restore_faces: {},
    sd_vae: {},
    clip_skip: {},
    mask: '<string>',
    mask_blur: 123,
    resize_mode: {},
    image_cfg_scale: {},
    inpainting_fill: {},
    inpaint_full_res: {},
    inpaint_full_res_padding: {},
    inpainting_mask_invert: 123,
    initial_noise_multiplier: 123,
    img_expire_ttl: 123,
    sd_refiner: {checkpoint: '<string>', switch_at: 123},
    controlnet_units: {
      model: '<string>',
      weight: {},
      input_image: '<string>',
      module: '<string>',
      control_mode: {},
      mask: {},
      resize_mode: {},
      processor_res: {},
      threshold_a: {},
      threshold_b: {},
      guidance_start: {},
      guidance_end: {},
      pixel_perfect: {}
    }
  })
};

fetch('https://api.novita.ai/v2/img2img', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.novita.ai/v2/img2img",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'extra' => [
        'enable_nsfw_detection' => true,
        'nsfw_detection_level' => 123,
        'enable_progress_info' => [
                
        ],
        'response_image_type' => '<string>'
    ],
    'prompt' => [
        
    ],
    'negative_prompt' => [
        
    ],
    'sampler_name' => [
        
    ],
    'batch_size' => [
        
    ],
    'n_iter' => [
        
    ],
    'steps' => [
        
    ],
    'cfg_scale' => [
        
    ],
    'seed' => [
        
    ],
    'height' => 123,
    'width' => 123,
    'model_name' => '<string>',
    'init_images' => [
        '<string>'
    ],
    'denoising_strength' => [
        
    ],
    'restore_faces' => [
        
    ],
    'sd_vae' => [
        
    ],
    'clip_skip' => [
        
    ],
    'mask' => '<string>',
    'mask_blur' => 123,
    'resize_mode' => [
        
    ],
    'image_cfg_scale' => [
        
    ],
    'inpainting_fill' => [
        
    ],
    'inpaint_full_res' => [
        
    ],
    'inpaint_full_res_padding' => [
        
    ],
    'inpainting_mask_invert' => 123,
    'initial_noise_multiplier' => 123,
    'img_expire_ttl' => 123,
    'sd_refiner' => [
        'checkpoint' => '<string>',
        'switch_at' => 123
    ],
    'controlnet_units' => [
        'model' => '<string>',
        'weight' => [
                
        ],
        'input_image' => '<string>',
        'module' => '<string>',
        'control_mode' => [
                
        ],
        'mask' => [
                
        ],
        'resize_mode' => [
                
        ],
        'processor_res' => [
                
        ],
        'threshold_a' => [
                
        ],
        'threshold_b' => [
                
        ],
        'guidance_start' => [
                
        ],
        'guidance_end' => [
                
        ],
        'pixel_perfect' => [
                
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: <authorization>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.novita.ai/v2/img2img"

	payload := strings.NewReader("{\n  \"extra\": {\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123,\n    \"enable_progress_info\": {},\n    \"response_image_type\": \"<string>\"\n  },\n  \"prompt\": {},\n  \"negative_prompt\": {},\n  \"sampler_name\": {},\n  \"batch_size\": {},\n  \"n_iter\": {},\n  \"steps\": {},\n  \"cfg_scale\": {},\n  \"seed\": {},\n  \"height\": 123,\n  \"width\": 123,\n  \"model_name\": \"<string>\",\n  \"init_images\": [\n    \"<string>\"\n  ],\n  \"denoising_strength\": {},\n  \"restore_faces\": {},\n  \"sd_vae\": {},\n  \"clip_skip\": {},\n  \"mask\": \"<string>\",\n  \"mask_blur\": 123,\n  \"resize_mode\": {},\n  \"image_cfg_scale\": {},\n  \"inpainting_fill\": {},\n  \"inpaint_full_res\": {},\n  \"inpaint_full_res_padding\": {},\n  \"inpainting_mask_invert\": 123,\n  \"initial_noise_multiplier\": 123,\n  \"img_expire_ttl\": 123,\n  \"sd_refiner\": {\n    \"checkpoint\": \"<string>\",\n    \"switch_at\": 123\n  },\n  \"controlnet_units\": {\n    \"model\": \"<string>\",\n    \"weight\": {},\n    \"input_image\": \"<string>\",\n    \"module\": \"<string>\",\n    \"control_mode\": {},\n    \"mask\": {},\n    \"resize_mode\": {},\n    \"processor_res\": {},\n    \"threshold_a\": {},\n    \"threshold_b\": {},\n    \"guidance_start\": {},\n    \"guidance_end\": {},\n    \"pixel_perfect\": {}\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "<authorization>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.novita.ai/v2/img2img")
  .header("Authorization", "<authorization>")
  .header("Content-Type", "application/json")
  .body("{\n  \"extra\": {\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123,\n    \"enable_progress_info\": {},\n    \"response_image_type\": \"<string>\"\n  },\n  \"prompt\": {},\n  \"negative_prompt\": {},\n  \"sampler_name\": {},\n  \"batch_size\": {},\n  \"n_iter\": {},\n  \"steps\": {},\n  \"cfg_scale\": {},\n  \"seed\": {},\n  \"height\": 123,\n  \"width\": 123,\n  \"model_name\": \"<string>\",\n  \"init_images\": [\n    \"<string>\"\n  ],\n  \"denoising_strength\": {},\n  \"restore_faces\": {},\n  \"sd_vae\": {},\n  \"clip_skip\": {},\n  \"mask\": \"<string>\",\n  \"mask_blur\": 123,\n  \"resize_mode\": {},\n  \"image_cfg_scale\": {},\n  \"inpainting_fill\": {},\n  \"inpaint_full_res\": {},\n  \"inpaint_full_res_padding\": {},\n  \"inpainting_mask_invert\": 123,\n  \"initial_noise_multiplier\": 123,\n  \"img_expire_ttl\": 123,\n  \"sd_refiner\": {\n    \"checkpoint\": \"<string>\",\n    \"switch_at\": 123\n  },\n  \"controlnet_units\": {\n    \"model\": \"<string>\",\n    \"weight\": {},\n    \"input_image\": \"<string>\",\n    \"module\": \"<string>\",\n    \"control_mode\": {},\n    \"mask\": {},\n    \"resize_mode\": {},\n    \"processor_res\": {},\n    \"threshold_a\": {},\n    \"threshold_b\": {},\n    \"guidance_start\": {},\n    \"guidance_end\": {},\n    \"pixel_perfect\": {}\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.novita.ai/v2/img2img")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = '<authorization>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"extra\": {\n    \"enable_nsfw_detection\": true,\n    \"nsfw_detection_level\": 123,\n    \"enable_progress_info\": {},\n    \"response_image_type\": \"<string>\"\n  },\n  \"prompt\": {},\n  \"negative_prompt\": {},\n  \"sampler_name\": {},\n  \"batch_size\": {},\n  \"n_iter\": {},\n  \"steps\": {},\n  \"cfg_scale\": {},\n  \"seed\": {},\n  \"height\": 123,\n  \"width\": 123,\n  \"model_name\": \"<string>\",\n  \"init_images\": [\n    \"<string>\"\n  ],\n  \"denoising_strength\": {},\n  \"restore_faces\": {},\n  \"sd_vae\": {},\n  \"clip_skip\": {},\n  \"mask\": \"<string>\",\n  \"mask_blur\": 123,\n  \"resize_mode\": {},\n  \"image_cfg_scale\": {},\n  \"inpainting_fill\": {},\n  \"inpaint_full_res\": {},\n  \"inpaint_full_res_padding\": {},\n  \"inpainting_mask_invert\": 123,\n  \"initial_noise_multiplier\": 123,\n  \"img_expire_ttl\": 123,\n  \"sd_refiner\": {\n    \"checkpoint\": \"<string>\",\n    \"switch_at\": 123\n  },\n  \"controlnet_units\": {\n    \"model\": \"<string>\",\n    \"weight\": {},\n    \"input_image\": \"<string>\",\n    \"module\": \"<string>\",\n    \"control_mode\": {},\n    \"mask\": {},\n    \"resize_mode\": {},\n    \"processor_res\": {},\n    \"threshold_a\": {},\n    \"threshold_b\": {},\n    \"guidance_start\": {},\n    \"guidance_end\": {},\n    \"pixel_perfect\": {}\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "code": 123,
  "msg": "<string>",
  "data": {
    "task_id": "<string>",
    "warn": "<string>"
  }
}

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

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

string

required

Request Body

object

Show properties

boolean

When set to true, NSFW detection will be enabled, incurring an additional cost of $0.0015 for each generated image.

integer

*** 0 - Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols. *** 1 - Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols; Non-Explicit Nudity, Obstructed Intimate Parts, Kissing on the Lips. *** 2 - Explicit Nudity, Explicit Sexual Activity, Sex Toys; Hate Symbols; Non-Explicit Nudity, Obstructed Intimate Parts, Kissing on the Lips; Female Swimwear or Underwear, Male Swimwear or Underwear.
Enum: 0, 1, 2

boolean¦null

You will receive empty preview images after setting enable_progress_info to false.

string

The format of returned images, default: png
Enum: png, jpeg

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>.

string¦null

Negative prompt words, separated by commas.

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

integer¦null

required

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

integer¦null

required

Number of generations. Range: [0, 8]

integer¦null

required

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

number¦null

required

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

integer¦null

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

integer

required

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

integer

required

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

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.

string[]

required

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.

boolean¦null

Enable Stable Diffusion restore faces plugin.

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.

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.

string

Base64 of png, mask of inpaintings.

integer

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

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

integer¦null

Image cfg scale

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

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

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

integer

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

number

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

integer

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

object

Refiner infos to enhances the image details.

Show properties

string

required

Refiner checkpoint name. Currently only sd_xl_refiner_1.0.safetensors supported.
Enum: sd_xl_refiner_1.0.safetensors

number

required

Weight of refiner. From 0 to 1

object[]¦null

ControlNet.

Show properties

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

number¦null

required

weight of this unit. defaults to 1

string

required

base64 of input image

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

integer¦null

required

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

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.

integer¦null

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

integer¦null

Resolution of the preprocessor.

integer¦null

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

integer¦null

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

number¦null

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

number¦null

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

boolean¦null

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

Response

integer

string

object

Show properties

string

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"
  }
}

Last modified on July 24, 2026

Text to Image V2 Progress

⌘I

Overview

Basic

Quota

Team Budget

API Key Model Access

Model APIs

GPUs

Image to Image V2

POST Image to Image V2

Request Headers

Request Body

Response

Example

​POST Image to Image V2

​Request Headers

​Request Body

​Response

​Example

POST Image to Image V2

Request Headers

Request Body

Response

Example