# Novita AI Image to Image API | Generate Images with Stable Diffusion Models

> Utilize the Novita AI Image to Image API to generate high-quality images using Stable Diffusion Models from both images and text prompts. This asynchronous API supports advanced features like ControlNet, Textual Inversion, and NSFW detection to enhance your image generation tasks. Explore comprehensive API documentation and examples.

> 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-img2img

# Image to Image

POST

/

v3

/

async

/

img2img

Try it

Image to Image

cURL

```
curl --request POST \
--url https://api.novita.ai/v3/async/img2img \
--header 'Authorization: <authorization>' \
--header 'Content-Type: <content-type>' \
--data '
{
"extra": {
"response_image_type": "<string>",
"webhook": {
"url": "<string>",
"test_mode": {
"enabled": true,
"return_task_status": "<string>"
}
},
"custom_storage": {
"aws_s3": {
"region": "<string>",
"bucket": "<string>",
"path": "<string>",
"save_to_path_directly": true
}
},
"enterprise_plan": {
"enabled": true
},
"enable_nsfw_detection": true,
"nsfw_detection_level": 123
},
"request": {
"model_name": "<string>",
"image_base64": "<string>",
"prompt": "<string>",
"width": 123,
"height": 123,
"image_num": 123,
"steps": 123,
"guidance_scale": 123,
"sampler_name": "<string>",
"negative_prompt": "<string>",
"sd_vae": "<string>",
"controlnet": {
"units": [
{
"model_name": "<string>",
"image_base64": "<string>",
"strength": 123,
"preprocessor": "<string>",
"guidance_start": 123,
"guidance_end": 123
}
]
},
"seed": 123,
"loras": [
{
"model_name": "<string>",
"strength": 123
}
],
"embeddings": [
{
"model_name": "<string>"
}
],
"clip_skip": 123,
"strength": {},
"ip_adapters": [
{
"model_name": "<string>",
"image_base64": "<string>",
"strength": {}
}
]
}
}
'
```

200

```
{
"task_id": "<string>"
}
```

Generate images with Stable Diffusion Models from Image and Text Prompts.

This is an asynchronous API; only the task_id is returned initially. Use this task_id to query the [Task Result API](/docs/api-reference/model-apis-task-result) to retrieve the results of the image generation.

##

[​](#request-headers)

Request Headers

[​](#param-content-type)

Content-Type

string

required

Enum: `application/json`

[​](#param-authorization)

Authorization

string

required

Bearer authentication format, for example: Bearer {{API Key}}.

##

[​](#request-body)

Request Body

[​](#param-extra)

extra

object

Optional extra parameters for the request.

Show properties

[​](#param-response-image-type)

response_image_type

string

The returned image type. Default is png.

Enum: `png`, `webp`, `jpeg`

[​](#param-webhook)

webhook

object

Webhook settings. More details can be found at [Webhook Documentation](/docs/api-reference/model-apis-webhook).

Show properties

[​](#param-url)

url

string

required

The URL of the webhook endpoint. Novita AI will send the task generated outputs to your specified webhook endpoint.

[​](#param-test-mode)

test_mode

object

By specifying Test Mode, a mock event will be sent to the webhook endpoint.

Show properties

[​](#param-enabled)

enabled

boolean

required

Set to true to enable Test Mode, or false to disable it. The default is false.

[​](#param-return-task-status)

return_task_status

string

required

Control the data content of the mock event. When set to TASK_STATUS_SUCCEED, you’ll receive a normal response; when set to TASK_STATUS_FAILED, you’ll receive an error response.

Enum: `TASK_STATUS_SUCCEED`, `TASK_STATUS_FAILED`

[​](#param-custom-storage)

custom_storage

object

Customer storage settings for saving the generated outputs.
By default, the generated outputs will be saved to Novita AI Storage temporarily and privately.

Show properties

[​](#param-aws-s3)

aws_s3

object

AWS S3 Bucket settings.

Show properties

[​](#param-region)

region

string

required

AWS S3 regions, [more details](https://docs.aws.amazon.com/general/latest/gr/rande.html).

[​](#param-bucket)

bucket

string

required

AWS S3 bucket name.

[​](#param-path)

path

string

required

AWS S3 bucket path for saving generated outputs.

[​](#param-save-to-path-directly)

save_to_path_directly

boolean

Set this option to True to save the generated outputs directly to the specified path without creating any additional directory hierarchy.
If set to False, Novita AI will create an additional directory in the path to save the generated outputs. The default is False.

[​](#param-enterprise-plan)

enterprise_plan

object

Dedicated Endpoints settings, which only take effect for users who have already subscribed to the [Dedicated Endpoints Documentation](/docs/guides/model-apis-dedicated-endpoints).

Show properties

[​](#param-enabled-1)

enabled

boolean

Set to true to schedule this task to use your Dedicated Endpoints’s dedicated resources. Default is false.

[​](#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-request)

request

object

required

Hide properties

[​](#param-model-name)

model_name

string

required

This parameter specifies the name of the model checkpoint. Retrieve the corresponding sd_name value by invoking the [Query Model](/api-reference/model-apis-get-model) API with filter.types=checkpoint as the query parameter.

[​](#param-image-base64)

image_base64

string

required

The base64 of original image, with a maximum resolution of 16 megapixels and a maximum file size of 10 Mb.

[​](#param-prompt)

prompt

string

required

Text input required to guide the image generation, divided by `,` . Range [1, 1024].

[​](#param-width)

width

integer

required

Width of image. Range [128, 2048].

[​](#param-height)

height

integer

required

Height of image. Range [128, 2048].

[​](#param-image-num)

image_num

integer

required

Images numbers generated in one single generation. Range [1, 8].

[​](#param-steps)

steps

integer

required

The number of denoising steps. More steps usually can produce higher quality images, but take more time to generate, Range [1, 100].

[​](#param-guidance-scale)

guidance_scale

number

required

This setting says how close the Stable Diffusion will listen to your prompt, higer guidance forces the model to better follow the prompt, but result in lower quality output. Range [1, 30].

[​](#param-sampler-name)

sampler_name

string

required

This parameter determines the denoising algorithm employed during the sampling phase of Stable Diffusion. Each option represents a distinct method by which the model incrementally generates new images. These algorithms differ significantly in their processing speed, output quality, and the specific characteristics of the images they generate, allowing users to tailor the image generation process to meet precise requirements. Get reference at [A brief introduction to Sampler](/docs/guides/model-apis-sampler).

Enum: `Euler a`, `Euler`, `LMS`, `Heun`, `DPM2`, `DPM2 a`, `DPM++ 2S a`, `DPM++ 2M`, `DPM++ SDE`, `DPM fast`, `DPM adaptive`, `LMS Karras`, `DPM2 Karras`, `DPM2 a Karras`, `DPM++ 2S a Karras`, `DPM++ 2M Karras`, `DPM++ SDE Karras`, `DDIM`, `PLMS`, `UniPC`

[​](#param-negative-prompt)

negative_prompt

string

Text input that specifies what to exclude from the generated images, divided by `,` . Range [1, 1024].

[​](#param-sd-vae)

sd_vae

string

VAE (Variational Auto Encoder). sd_vae can be accessed in the API /v3/models with query params type=vae, like sd_name: customVAE.safetensors. Get reference at [A Brief Introduction to VAE](/docs/guides/model-apis-vae).

[​](#param-controlnet)

controlnet

object

The ControlNet configuration provides a greater degree of control over text-to-image generation by conditioning the model on additional inputs such as edge maps, depth maps, segmentation maps, and keypoints for pose detection.

Show properties

[​](#param-units)

units

object[]

required

Hide properties

[​](#param-model-name-1)

model_name

string

required

Preprocessor 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, control_v1p_sd15_brightness, control_v1p_sd15_qrcode_monster, control_v1p_sd15_qrcode_monster_v2, ***ControlNets for SDXL: controlnet-canny-sdxl-1.0, controlnet-depth-sdxl-1.0, controlnet-openpose-sdxl-1.0, controlnet-softedge-sdxl-1.0

[​](#param-image-base64-1)

image_base64

string

required

base64 of input controlNet image

[​](#param-strength)

strength

number

required

The strength of this unit, defaults to 1. Range [0, 1]; the larger the value, the more biased the effect is towards ControlNet.

[​](#param-preprocessor)

preprocessor

string

Preprocessor to use on the image passed to this unit before using it for conditioning.

Enum: `scribble_hed`, `softedge_hed`, `scribble_hedsafe`, `softedge_hedsafe`, `depth_midas`, `mlsd`, `openpose`, `openpose_face`, `openpose_faceonly`, `openpose_full`, `openpose_hand`, `dwpose`, `scribble_pidinet`, `softedge_pidinet`, `scribble_pidsafe`, `softedge_pidsafe`, `normal_bae`, `lineart_coarse`, `lineart_realistic`, `lineart_anime`, `lineart`, `depth_zoe`, `shuffle`, `mediapipe_face`, `canny`, `depth`, `depth_leres`, `depth_leres++`

[​](#param-guidance-start)

guidance_start

number

Ratio of generation where this unit starts to impact the process. Range [0, 1].

[​](#param-guidance-end)

guidance_end

number

Ratio of generation where this unit stops impacting the process. Range [0, 1].

[​](#param-seed)

seed

integer

A seed is a number from which Stable Diffusion generates noise, which, makes generation deterministic. Using the same seed and set of parameters will produce identical image each time, minimum -1. Defaults to -1.

[​](#param-loras)

loras

object[]

LoRA is a fast and lightweight training method that inserts and trains a significantly smaller number of parameters instead of all the model parameters. Currently supports up to 5 LoRAs.

Show properties

[​](#param-model-name-2)

model_name

string

required

Name of lora, retrieve the corresponding sd_name_in_api value by invoking the [Get Model API](/api-reference/model-apis-get-model) endpoint with filter.types=lora as the query parameter.

[​](#param-strength-1)

strength

number

required

The strength value of lora. The larger the value, the more biased the effect is towards lora, Range [0, 1]

[​](#param-embeddings)

embeddings

object[]

Textual Inversion is a training method for personalizing models by learning new text embeddings from a few example images, currently supports up to 5 embeddings.

Show properties

[​](#param-model-name-3)

model_name

string

required

Name of textual Inversion model, you can call the [Get Model API](/api-reference/model-apis-get-model) endpoint with parameter filter.types=textualinversion to retrieve the sd_name_in_api field as the model_name.

[​](#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, Range [1, 12], get reference at [A brief introduction to Clip Skip](/docs/guides/model-apis-clip-skip).

[​](#param-strength-2)

strength

number(float)¦null

Conceptually, the `strength` indicates the degree to which the reference `image_base64` should be transformed. Must be between 0 and 1. `image_base64` will be used as a starting point, with increasing levels of noise added as the strength value increases. The number of denoising steps depends on the amount of noise initially added. When `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 `image_base64`.

[​](#param-ip-adapters)

ip_adapters

object[]

IP-Adapter is an image prompt adapter that can be plugged into diffusion models to enable image prompting without any changes to the underlying model. Furthermore, adapter can be reused with other models finetuned from the same base model and it can be combined with other adapters like ControlNet, currenlty supports up to 1 IP-Adapter.

Show properties

[​](#param-model-name-4)

model_name

string

required

IP-Adapter model name, if the base model of your checkpoint is SDXL, then you should select ip-adapter_sdxl.bin. Alternatively, if the base model of your checkpoint is SD1.x, then you should select ip-adapter_sd15.bin.

Enum: `ip-adapter_sd15.bin`, `ip-adapter_sdxl.bin`

[​](#param-image-base64-2)

image_base64

string

required

The base64 decoded content for input image.

[​](#param-strength-3)

strength

number(float)

required

Range [0, 1], this value represents the strength of this unit. The larger the value, the more pronounced the effect of the IP-Adapter becomes.

##

[​](#response)

Response

[​](#param-task-id)

task_id

string

Use the task_id to request the [Task Result API](/docs/api-reference/model-apis-task-result) to retrieve the generated outputs.

##

[​](#example)

Example

###

[​](#1-image-to-image-request-with-normal-parameter)

1. Image to image request with normal parameter.

Please set the `Content-Type` header to `application/json` in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported.
`Request:`

```
curl --location 'https://api.novita.ai/v3/async/img2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
"extra": {
"response_image_type": "jpeg"
},
"request": {
"model_name": "sd_xl_base_1.0.safetensors",
"prompt": "a cute dog",
"negative_prompt": "",
"height": 512,
"width": 384,
"image_num": 1,
"steps": 20,
"seed": -1,
"clip_skip": 1,
"guidance_scale": 7.5,
"sampler_name": "Euler a",
"embeddings": [
{
"model_name": "pureerosface_v1_5162.pt"
}
],
"loras": [
{
"model_name": "add_detail_44319",
"strength": 0.7
},
{
"model_name": "more_details_59655",
"strength": 0.7
}
],
"image_base64": "{{Base64 encode image}}"
}
}'
```

`Response:`

```
{
"code": 0,
"msg": "",
"data": {
"task_id": "73fab7c0-e24f-4027-9df0-81ff8ce4bc1f"
}
}
```

Use `task_id` to get images
HTTP status codes in the 2xx range indicate that the request has been successfully accepted, while status codes in the 5xx range indicate internal server errors.
You can get images url in `imgs` of response.
`Request:`

```
curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=73fab7c0-e24f-4027-9df0-81ff8ce4bc1f' \
--header 'Authorization: Bearer {{API Key}}'
```

`Response:`

```
{
"extra": {
"seed": "1434608307"
},
"task": {
"task_id": "73fab7c0-e24f-4027-9df0-81ff8ce4bc1f",
"task_type": "IMG_TO_IMG",
"status": "TASK_STATUS_SUCCEED",
"reason": "",
"eta": 0,
"progress_percent": 0
},
"images": [
{
"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/73fab7c0-e24f-4027-9df0-81ff8ce4bc1f/d54551765e41409fbc80f7c23dc89241.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240115%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240115T083555Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=92dca9221e620d708c29ec525ed50ceb984dda23d8b7a352b4a19be682c8906e",
"image_url_ttl": "3600",
"image_type": "jpeg"
}
],
"videos": []
}
```

###

[​](#2-image-to-image-request-with-controlnet)

2. Image to image request with controlNet.

Please set the `Content-Type` header to `application/json` in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported.
`Request:`

```
curl --location 'https://api.novita.ai/v3/async/img2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
"extra": {
"response_image_type": "jpeg"
},
"request": {
"model_name": "realcartoon25D_v3_240762.safetensors",
"prompt": "1girl",
"negative_prompt": "bad quality, bad anatomy, worst quality, low quality, lowres, extra fingers, blur, blurry, ugly, wrong proportions, watermark, image artifacts, bad eyes, bad hands, bad arms",
"height": 1024,
"width": 1024,
"image_num": 1,
"steps": 20,
"seed": -1,
"clip_skip": 1,
"guidance_scale": 7,
"sampler_name": "Euler",
"controlnet": {
"units": [
{
"model_name": "control_v11p_sd15_openpose",
"image_base64": "{{Base64 encode image}}",
"strength": 0.5,
"preprocessor": "openpose"
}
]
},
"image_base64": "{{Base64 encode image}}"
}
}'
```

`Response:`

```
{
"code": 0,
"msg": "",
"data": {
"task_id": "5867de36-7b76-4dc7-876e-818e3ffe683e"
}
}
```

Use `task_id` to get images
HTTP status codes in the 2xx range indicate that the request has been successfully accepted, while status codes in the 5xx range indicate internal server errors.
You can get images url in `imgs` of response.
`Request:`

```
curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=5867de36-7b76-4dc7-876e-818e3ffe683e' \
--header 'Authorization: Bearer {{API Key}}'
```

`Response:`

```
{
"extra": {
"seed": "632855931",
"enable_nsfw_detection": false
},
"task": {
"task_id": "5867de36-7b76-4dc7-876e-818e3ffe683e",
"task_type": "IMG_TO_IMG",
"status": "TASK_STATUS_SUCCEED",
"reason": "",
"eta": 0,
"progress_percent": 0
},
"images": [
{
"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/5867de36-7b76-4dc7-876e-818e3ffe683e/6569906512e14c2da82d74e69882b3a4.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240307%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240307T064348Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=f506cd2dc7ed7526bfe1cf4074722a1178efe242db6ca56e1e7dbca9b67230d2",
"image_url_ttl": "3600",
"image_type": "jpeg",
"nsfw_detection_result": null
}
],
"videos": []
}
```

###

[​](#3-image-to-image-request-with-textual-inversion-embedding)

3. Image to image request with Textual Inversion(embedding).

Please set the `Content-Type` header to `application/json` in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported.
`Request for textual inversion names:`

```
curl --location --request GET 'https://api.novita.ai/v3/model?filter.visibility=public&pagination.limit=100&pagination.cursor=c_0&filter.types=textualinversion&filter.source=civitai' \
--header 'Authorization: Bearer {{API Key}}' | jq '.models[].sd_name'
```

`Response:`

```
"epiCPhotoGasm-colorfulPhoto-neg_108119.pt"
"epiCNegative_66017.pt"
"verybadimagenegative_v1.3_21434.pt"
"FastNegativeV2_65067.pt"
"AS-YoungV2.pt"
"AS-YoungV2-neg.pt"
"AS-YoungestV2.pt"
"AS-YoungerV2.pt"
"AS-MidAged.pt"
"AS-Elderly.pt"
"AS-Adult.pt"
"AS-Adult-neg.pt"
"Adult.pt"
"MidAged.pt"
"unaestheticXLv13_98060.safetensors"
"unaestheticXL_Sky3.1_134255.safetensors"
"EasyNegativeV2_75525.safetensors"
"BadDream_53202.pt"
"UnrealisticDream_53204.pt"
"negative_hand-neg_43127.pt"
"bad_prompt_version2-neg_42594.pt"
"Asian-Less-Toon_39763.pt"
"badhandv4_16755.pt"
"easynegative_8955.safetensors"
"aestheticc-65800_8615.pt"
"corneo_side_deepthroat_6490.pt"
"corneo_tentacle_sex.pt"
"By bad artist -neg_6310.pt"
"dpthrt_5441.pt"
"ng_deepnegative_v1_75t_5845.pt"
"pureerosface_v1_5162.pt"
```

`Request:`

```
curl --location 'https://api.novita.ai/v3/async/img2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
"extra": {
"response_image_type": "jpeg"
},
"request": {
"model_name": "realcartoon25D_v3_240762.safetensors",
"prompt": "dark theme girl",
"negative_prompt": "",
"height": 1024,
"width": 1024,
"image_num": 1,
"steps": 20,
"seed": 123,
"clip_skip": 1,
"guidance_scale": 7.5,
"sampler_name": "Euler a",
"embeddings": [
{
"model_name": "badhandv4_16755.pt"
},
{
"model_name": "BadDream_53202.pt"
}
],
"image_base64": "{{Base64 encode image}}"
}
}'
```

`Response:`

```
{
"code": 0,
"msg": "",
"data": {
"task_id": "6411f576-1c62-48b4-a0d5-427488721159"
}
}
```

Use `task_id` to get images
HTTP status codes in the 2xx range indicate that the request has been successfully accepted, while status codes in the 5xx range indicate internal server errors.
You can get images url in `imgs` of response.
`Request:`

```
curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=6411f576-1c62-48b4-a0d5-427488721159' \
--header 'Authorization: Bearer {{API Key}}'
```

`Response:`

```
{
"extra": {
"seed": "170871295",
"enable_nsfw_detection": false
},
"task": {
"task_id": "6411f576-1c62-48b4-a0d5-427488721159",
"task_type": "IMG_TO_IMG",
"status": "TASK_STATUS_SUCCEED",
"reason": "",
"eta": 0,
"progress_percent": 0
},
"images": [
{
"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/6411f576-1c62-48b4-a0d5-427488721159/ede3a87d667e4371abc687b9ede03938.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240307%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240307T065015Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=228bb2254bf7de328814c89b200287ab903f7f5690033f810c745ae7be902b76",
"image_url_ttl": "3600",
"image_type": "jpeg",
"nsfw_detection_result": null
}
],
"videos": []
}
```

###

[​](#4-img2img-request-with-nsfw_detection)

4. Img2img request with nsfw_detection.

When set `enable_nsfw_detection` true, NSFW detection will be enabled, incurring an additional cost of $0.0015 for each generated image.
`nsfw_detection_level`, nsfw check level, ranging from 0 to 2, with higher levels indicating stricter NSFW detection criteria. The default value is 0. The following table lists the NSFW detection criteria for each level.

- 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.

Please set the `Content-Type` header to `application/json` in your HTTP request to indicate that you are sending JSON data. Currently, only JSON format is supported.
`Request:`

```
curl --location 'https://api.novita.ai/v3/async/img2img' \
--header 'Authorization: Bearer {{API Key}}' \
--header 'Content-Type: application/json' \
--data '{
"extra": {
"response_image_type": "jpeg",
"enable_nsfw_detection": true,
"nsfw_detection_level": 2
},
"request": {
"model_name": "chilloutmix_NiPrunedFp32Fix.safetensors",
"prompt": "a cute dog",
"negative_prompt": "",
"height": 512,
"width": 384,
"image_num": 1,
"steps": 20,
"seed": 123,
"clip_skip": 1,
"guidance_scale": 7.5,
"sampler_name": "Euler a",
"embeddings": [
{
"model_name": "pureerosface_v1_5162.pt"
}
],
"loras": [
{
"model_name": "MS_Real_AssSpread",
"strength": 0.7
},
{
"model_name": "MS_Real_Cameltoe_Lite",
"strength": 0.9
}
],
"controlnet": {
"units": [
{
"model_name": "control_v11f1e_sd15_tile",
"image_base64": "{{Base64 encode image}}",
"strength": 1,
"preprocessor": "openpose"
}
]
},
"image_base64": "{{Base64 encode image}}"
}
}'
```

`Response:`

```
{
"code": 0,
"msg": "",
"data": {
"task_id": "741597cc-8e27-4932-9d75-34f07b96413e"
}
}
```

Use `task_id` to get images
HTTP status codes in the 2xx range indicate that the request has been successfully accepted, while status codes in the 5xx range indicate internal server errors.
You can get images url in `imgs` of response.
There are two results in reponse.

-
`enable_nsfw_detection`, when return with `true` means NSFW detection is enabled.

-
`nsfw_detection_result`, presenting an array of NSFW detection outcomes for each image. The order of elements in the nsfw_detection_result array corresponds one-to-one with the sequence of images in the `images` field in the response. The `valid` field denotes the success of the NSFW detection process, while the `confidence` field, ranging from 0 to 100, signifies the confidence level of the NSFW detection result. Higher confidence values, nearing 100, suggest a greater likelihood of the corresponding image containing NSFW content.

`Request:`

```
curl --location --request GET 'https://api.novita.ai/v3/async/task-result?task_id=741597cc-8e27-4932-9d75-34f07b96413e' \
--header 'Authorization: Bearer {{API Key}}'
```

`Response:`

```
{
"extra": {
"seed": "3183986171",
"enable_nsfw_detection": true
},
"task": {
"task_id": "741597cc-8e27-4932-9d75-34f07b96413e",
"task_type": "TXT_TO_IMG",
"status": "TASK_STATUS_SUCCEED",
"reason": "",
"eta": 0,
"progress_percent": 0
},
"images": [
{
"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/741597cc-8e27-4932-9d75-34f07b96413e/6e38c309732f4241b99f75e54ffdb54a.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240124%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240124T141031Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=9edf916b9f3148207953140d0ec545a468e50fc80e635d4a7fa182c67989ced8",
"image_url_ttl": "3600",
"image_type": "jpeg",
"nsfw_detection_result": {
"valid": true,
"confidence": 0
}
},
{
"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/741597cc-8e27-4932-9d75-34f07b96413e/b8346c9cbe494102be2a28f29c0005b1.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240124%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240124T141031Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=d81316dea2446aab04cd5e559504a2a8fa7245958d766afd8f372e7e8fb02fb9",
"image_url_ttl": "3600",
"image_type": "jpeg",
"nsfw_detection_result": {
"valid": true,
"confidence": 0
}
},
{
"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/741597cc-8e27-4932-9d75-34f07b96413e/f6e0f939a5e4466990595445a41e75ef.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240124%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240124T141031Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=6d719fe7e4e6cb0f93ec07616b20e968f659b12102e4b11c866016780eb2eb6c",
"image_url_ttl": "3600",
"image_type": "jpeg",
"nsfw_detection_result": {
"valid": true,
"confidence": 0
}
},
{
"image_url": "https://faas-output-image.s3.ap-southeast-1.amazonaws.com/prod/741597cc-8e27-4932-9d75-34f07b96413e/ddbc7d39db1d4468bd3c9d92556b99ee.jpeg?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASVPYCN6LRCW3SOUV%2F20240124%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Date=20240124T141031Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&x-id=GetObject&X-Amz-Signature=259a5d358175132a2c0adfcd23142bb8227cd6e68052b99779686956c04a713a",
"image_url_ttl": "3600",
"image_type": "jpeg",
"nsfw_detection_result": {
"valid": true,
"confidence": 0
}
}
],
"videos": []
}
```

Last modified on January 14, 2026