# Text to Image V2 - Documentation

> For the complete documentation index, see [llms.txt](/llms.txt). Markdown is available with `Accept: text/markdown` and `.md` URL variants.

Source: /docs/api-reference/model-apis-text-to-image-v2-deprecated

# Text to Image V2

POST

/

v2

/

txt2img

Try it

Text to Image V2

cURL

```
curl --request POST \
--url https://api.novita.ai/v2/txt2img \
--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": "<string>",
"negative_prompt": "<string>",
"sampler_name": "<string>",
"batch_size": 123,
"n_iter": 123,
"steps": 123,
"cfg_scale": 123,
"seed": 123,
"height": 123,
"width": 123,
"model_name": "<string>",
"restore_faces": true,
"restore_faces_model": null,
"sd_vae": {},
"clip_skip": 123,
"enable_hr": {},
"hr_upscaler": {},
"hr_scale": {},
"hr_resize_x": {},
"hr_resize_y": {},
"img_expire_ttl": {},
"sd_refiner": {
"checkpoint": "<string>",
"switch_at": 123
},
"controlnet_units": {
"model": "<string>",
"weight": {},
"input_image": "<string>",
"module": "<string>",
"control_mode": {},
"mask": {},
"resize_mode": {},
"processor_res": 123,
"threshold_a": 123,
"threshold_b": 123,
"guidance_start": 123,
"guidance_end": 123,
"pixel_perfect": true
}
}
'
```

```
import requestsurl = "https://api.novita.ai/v2/txt2img"payload = { "extra": { "enable_nsfw_detection": True, "nsfw_detection_level": 123, "enable_progress_info": {}, "response_image_type": "<string>" }, "prompt": "<string>", "negative_prompt": "<string>", "sampler_name": "<string>", "batch_size": 123, "n_iter": 123, "steps": 123, "cfg_scale": 123, "seed": 123, "height": 123, "width": 123, "model_name": "<string>", "restore_faces": True, "restore_faces_model": None, "sd_vae": {}, "clip_skip": 123, "enable_hr": {}, "hr_upscaler": {}, "hr_scale": {}, "hr_resize_x": {}, "hr_resize_y": {}, "img_expire_ttl": {}, "sd_refiner": { "checkpoint": "<string>", "switch_at": 123 }, "controlnet_units": { "model": "<string>", "weight": {}, "input_image": "<string>", "module": "<string>", "control_mode": {}, "mask": {}, "resize_mode": {}, "processor_res": 123, "threshold_a": 123, "threshold_b": 123, "guidance_start": 123, "guidance_end": 123, "pixel_perfect": True }}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: '<string>', negative_prompt: '<string>', sampler_name: '<string>', batch_size: 123, n_iter: 123, steps: 123, cfg_scale: 123, seed: 123, height: 123, width: 123, model_name: '<string>', restore_faces: true, restore_faces_model: null, sd_vae: {}, clip_skip: 123, enable_hr: {}, hr_upscaler: {}, hr_scale: {}, hr_resize_x: {}, hr_resize_y: {}, img_expire_ttl: {}, sd_refiner: {checkpoint: '<string>', switch_at: 123}, controlnet_units: { model: '<string>', weight: {}, input_image: '<string>', module: '<string>', control_mode: {}, mask: {}, resize_mode: {}, processor_res: 123, threshold_a: 123, threshold_b: 123, guidance_start: 123, guidance_end: 123, pixel_perfect: true } })};fetch('https://api.novita.ai/v2/txt2img', 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/txt2img", 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' => '<string>', 'negative_prompt' => '<string>', 'sampler_name' => '<string>', 'batch_size' => 123, 'n_iter' => 123, 'steps' => 123, 'cfg_scale' => 123, 'seed' => 123, 'height' => 123, 'width' => 123, 'model_name' => '<string>', 'restore_faces' => true, 'restore_faces_model' => null, 'sd_vae' => [ ], 'clip_skip' => 123, 'enable_hr' => [ ], 'hr_upscaler' => [ ], 'hr_scale' => [ ], 'hr_resize_x' => [ ], 'hr_resize_y' => [ ], 'img_expire_ttl' => [ ], 'sd_refiner' => [ 'checkpoint' => '<string>', 'switch_at' => 123 ], 'controlnet_units' => [ 'model' => '<string>', 'weight' => [ ], 'input_image' => '<string>', 'module' => '<string>', 'control_mode' => [ ], 'mask' => [ ], 'resize_mode' => [ ], 'processor_res' => 123, 'threshold_a' => 123, 'threshold_b' => 123, 'guidance_start' => 123, 'guidance_end' => 123, 'pixel_perfect' => true ] ]), 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 mainimport (	"fmt"	"strings"	"net/http"	"io")func main() {	url := "https://api.novita.ai/v2/txt2img"	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\": \"<string>\",\n \"negative_prompt\": \"<string>\",\n \"sampler_name\": \"<string>\",\n \"batch_size\": 123,\n \"n_iter\": 123,\n \"steps\": 123,\n \"cfg_scale\": 123,\n \"seed\": 123,\n \"height\": 123,\n \"width\": 123,\n \"model_name\": \"<string>\",\n \"restore_faces\": true,\n \"restore_faces_model\": null,\n \"sd_vae\": {},\n \"clip_skip\": 123,\n \"enable_hr\": {},\n \"hr_upscaler\": {},\n \"hr_scale\": {},\n \"hr_resize_x\": {},\n \"hr_resize_y\": {},\n \"img_expire_ttl\": {},\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\": 123,\n \"threshold_a\": 123,\n \"threshold_b\": 123,\n \"guidance_start\": 123,\n \"guidance_end\": 123,\n \"pixel_perfect\": true\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/txt2img") .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\": \"<string>\",\n \"negative_prompt\": \"<string>\",\n \"sampler_name\": \"<string>\",\n \"batch_size\": 123,\n \"n_iter\": 123,\n \"steps\": 123,\n \"cfg_scale\": 123,\n \"seed\": 123,\n \"height\": 123,\n \"width\": 123,\n \"model_name\": \"<string>\",\n \"restore_faces\": true,\n \"restore_faces_model\": null,\n \"sd_vae\": {},\n \"clip_skip\": 123,\n \"enable_hr\": {},\n \"hr_upscaler\": {},\n \"hr_scale\": {},\n \"hr_resize_x\": {},\n \"hr_resize_y\": {},\n \"img_expire_ttl\": {},\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\": 123,\n \"threshold_a\": 123,\n \"threshold_b\": 123,\n \"guidance_start\": 123,\n \"guidance_end\": 123,\n \"pixel_perfect\": true\n }\n}") .asString();
```

```
require 'uri'require 'net/http'url = URI("https://api.novita.ai/v2/txt2img")http = Net::HTTP.new(url.host, url.port)http.use_ssl = truerequest = 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\": \"<string>\",\n \"negative_prompt\": \"<string>\",\n \"sampler_name\": \"<string>\",\n \"batch_size\": 123,\n \"n_iter\": 123,\n \"steps\": 123,\n \"cfg_scale\": 123,\n \"seed\": 123,\n \"height\": 123,\n \"width\": 123,\n \"model_name\": \"<string>\",\n \"restore_faces\": true,\n \"restore_faces_model\": null,\n \"sd_vae\": {},\n \"clip_skip\": 123,\n \"enable_hr\": {},\n \"hr_upscaler\": {},\n \"hr_scale\": {},\n \"hr_resize_x\": {},\n \"hr_resize_y\": {},\n \"img_expire_ttl\": {},\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\": 123,\n \"threshold_a\": 123,\n \"threshold_b\": 123,\n \"guidance_start\": 123,\n \"guidance_end\": 123,\n \"pixel_perfect\": true\n }\n}"response = http.request(request)puts response.read_body
```

200

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

The Text-to-Image V2 API is deprecated and will be removed in the future. Please migrate to [Text-to-Image V3](/docs/api-reference/model-apis-txt2img).

##

[​](#post-text-to-image-v2)

POST Text to Image V2

The text-to-image endpoint will return only a `task_id`. You should use the `task_id` to call the /v2/progress API endpoint to retrieve the image generation results. We will gradually phase out the V2 endpoints. It is recommended to use the V3 endpoints to generate images.

##

[​](#request-headers)

Request Headers

[​](#param-authorization)

Authorization

string

required

##

[​](#request-body)

Request Body

[​](#param-extra)

extra

object

Show properties

[​](#param-enable-nsfw-detection)

enable_nsfw_detection

boolean

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

[​](#param-nsfw-detection-level)

nsfw_detection_level

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`

[​](#param-enable-progress-info)

enable_progress_info

boolean¦null

You will receive empty preview images if `enable_progress_info` is set to false.

[​](#param-response-image-type)

response_image_type

string

The format of the returned images; default: png

Enum: `png`, `jpeg`

[​](#param-prompt)

prompt

string

required

Positive prompt words, separated by `,`. 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>`.

[​](#param-negative-prompt)

negative_prompt

string

required

Negative prompt words, separated by `,`.

[​](#param-sampler-name)

sampler_name

string

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`

[​](#param-batch-size)

batch_size

integer

required

The number of images generated in one single generation. Range: [0, 8]

[​](#param-n-iter)

n_iter

integer

required

The number of generations. Range: [0, 8]

[​](#param-steps)

steps

integer

required

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

[​](#param-cfg-scale)

cfg_scale

integer

required

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

[​](#param-seed)

seed

integer

required

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

[​](#param-height)

height

integer

required

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

[​](#param-width)

width

integer

required

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

[​](#param-model-name)

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`.

[​](#param-restore-faces)

restore_faces

boolean

required

Enable the Stable Diffusion face restoration plugin.

[​](#param-restore-faces-model)

restore_faces_model

null

required

[​](#param-sd-vae)

sd_vae

string¦null

VAE (Variational Auto Encoder). `sd_vae` can be accessed in the API /v3/model with query parameters `filter.types=vae` to retrieve the `sd_name` field as the `sd_vae`.

[​](#param-clip-skip)

clip_skip

integer

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.

[​](#param-enable-hr)

enable_hr

boolean¦null

Hires.fix function switch.

[​](#param-hr-upscaler)

hr_upscaler

string¦null

Upscalers model names. AI upscalers are models trained with massive amounts of data.

Enum: `Latent`, `ESRGAN_4x`, `R-ESRGAN 4x+`, `R-ESRGAN 4x+ Anime6B`

[​](#param-hr-scale)

hr_scale

number¦null

The magnification factor of the image, if params hr_resize_x and hr_resize_y are set, this parameter will be ignored.

Enum: `1`, `2`

[​](#param-hr-resize-x)

hr_resize_x

integer¦null

The target image width, the maximum image size is 2048, only take effect when parameters hr_scale=1.

[​](#param-hr-resize-y)

hr_resize_y

integer¦null

The target image hight, the maximum image size is 2048, only take effect when parameters hr_scale=1.

[​](#param-img-expire-ttl)

img_expire_ttl

integer¦null

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

[​](#param-sd-refiner)

sd_refiner

object¦null

Refiner infos to enhances the image details.

Show properties

[​](#param-checkpoint)

checkpoint

string

required

Refiner checkpoint name. Currently only `sd_xl_refiner_1.0.safetensors` supported.

Enum: `sd_xl_refiner_1.0.safetensors`

[​](#param-switch-at)

switch_at

number

required

weight of refiner, from 0 to 1.

[​](#param-controlnet-units)

controlnet_units

object[]¦null

ControlNet.

Show properties

[​](#param-model)

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

[​](#param-weight)

weight

number¦null

required

weight of this unit. defaults to 1

[​](#param-input-image)

input_image

string

required

base64 of input image

[​](#param-module)

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`

[​](#param-control-mode)

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`

[​](#param-mask)

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.

[​](#param-resize-mode)

resize_mode

integer¦null

How to resize the input image so as to fit the output resolution of the generation. 0 represent JUST_RESIZE, 1 represent RESIZE_OR_CORP, 2 represent RESIZE_AND_FILL

Enum: `0`, `1`, `2`

[​](#param-processor-res)

processor_res

integer

Resolution of the preprocessor.

[​](#param-threshold-a)

threshold_a

integer

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

[​](#param-threshold-b)

threshold_b

integer

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

[​](#param-guidance-start)

guidance_start

number

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

[​](#param-guidance-end)

guidance_end

number

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

[​](#param-pixel-perfect)

pixel_perfect

boolean

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

##

[​](#response)

Response

[​](#param-code)

code

integer

[​](#param-msg)

msg

string

[​](#param-data)

data

object

Show properties

[​](#param-task-id)

task_id

string

[​](#param-warn)

warn

string

##

[​](#example)

Example

request

```
curl --location 'https://api.novita.ai/v2/txt2img' \
--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': 'Luxury suite design, Spacious suite area, Luxuriously plush large bed, Refined office desk, Carefully selected furniture for the luxurious suite, High-end and opulent decor, Private office and lounge area, Comfortably luxurious office chair, Amenities for luxury travelers, Premium bedding and linens, Uniquely designed lighting fixtures, Luxurious suite curtain design, Private work corner, Luxurious amenities, Lavish lounge area, Sophisticated indoor plant, decorations, Exquisite luxury design, Exclusive services for the luxury suite, Luxury color scheme. Exclusive furniture for the luxury suite, a bedroom with a large bed and a desk',
'negative_prompt': '(badhandv4:1.2),(worst quality:2),(low quality:2),(normal quality:2),lowres,bad anatomy,bad hands,((monochrome)),((grayscale)) watermark,moles, easynegative ng_deepnegative_v1_75t, (oversized head:2), (big head:2), (deformed face:1.5),( blurry face:2), bad eyes, irregular eyes, asymmetric eyes, ugly, teeth, (navel:0.9), artefact, jpg artefact, blurry face, blurry, blurred, pixelated, bad eyes, crossed eyes, blurry eyes',
'sampler_name': 'DPM++ 2M Karras',
'batch_size': 1,
'n_iter': 1,
'steps': 25,
'cfg_scale': 7,
'seed': -1,
'height': 512,
'width': 512,
'model_name': 'sd_xl_base_0.9.safetensors',
'restore_faces': false,
'restore_faces_model': '',
'sd_vae': '',
'clip_skip': 1,
'enable_hr': false,
'hr_upscaler': 'Latent',
'hr_scale': 1,
'hr_resize_x': null,
'hr_resize_y': null,
'img_expire_ttl': null,
'sd_refiner': {
'checkpoint': 'sd_xl_refiner_1.0.safetensors',
'switch_at': null
},
'controlnet_units': [
{
'model': '',
'weight': null,
'input_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
}
]
}'
```

response

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

Last modified on January 14, 2026