Face Avatar

The concept of a "Face Avatar" involves the creation of images where the face maintains a consistent appearance across multiple generated Images. To achieve this, you start with an initial facial image and provide it as a reference. Using this reference, a sophisticated model goes to work, crafting new images while keeping the facial features in line with the original picture. In essence, the model uses your input to generate images where the face remains faithful to the structure and characteristics you've specified in your prompt. This way, you can effortlessly create a series of images with a consistent and recognizable face.

Working insights :

In this model, the default prompt settings includes a prompt, “SFW Content, black plain background, joyous dating profile, VECTOR CARTOON ILLUSTRATION, half-body shot portrait enjoyable pleasing pleasurable nice {gender_word}, looking at camera, Relaxed, Charming, Cordial, Gracious, 5 o clock shadow, 3d bitmoji avatar render, pixar, high def textures 8k, highly detailed, 3d render, award winning, no background elements".

If you provide a custom prompt, it will override these default settings. To include a specific gender in your custom prompt, you must explicitly mention it in custom prompt. If you prefer to use the default settings without specifying any custom prompt, simply pass None in the prompt parameter. Subsequently, you can define the gender by using the gender parameter, which will apply the specified gender to the default image configuration.

Face Avatar API

POST /getImageToImage

Headers

Name Value

Name	Value
Content-Type	`application/json`
Authorization	`Bearer <token>`

Content-Type

application/json

Authorization

Bearer <token>

Body

Name Type Description

Name	Type	Description
app_id	string	-> Each model is uniquely characterized by its own `app_id`.
image	string	-> The `file_url` parameter specifies the URL of an existing image that will be used as a reference for the generation process. -> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.
prompt	string	-> The `prompt` parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.
batch	int	-> The `batch` parameter allows you to specify the number of images to generate at once. -> The valid range for this parameter is between 1 and 8.
height	int	-> The `height` parameter represents the vertical dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels.
width	int	-> The `width` parameter represents the horizontal dimension of an image. -> The valid range for the parameter is between 256 and 1536 pixels.
celery	bool	-> The `celery` parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique `task_id`. This `task_id` allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.
num_inference_steps	int	-> The `num_inference_steps` parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation. -> The valid range for the `num_inference_steps` parameter is between 1 and 50.
guidance_scale	float	-> The `guidance_scale` parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation. -> The valid range for the `guidance_scale` parameter is between 1 and 30.
negative_prompt	string	-> The `negative_prompt` parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.
gender	string	-> The `gender` parameter is used to guide the image generation model towards producing outputs with a specific gender representation. This can help avoid gender-related confusion or bias in the AI model's outputs.
remove_background	bool	-> When the `remove_background` parameter is enabled, the background of the generated image will be removed and replaced with a transparent background.
bg_color	string	-> The `bg_color` parameter allows you to set the background color of the generated image. The color value should be provided in hexadecimal format (e.g., `#FFFFFF` for white).

app_id

string

-> Each model is uniquely characterized by its own app_id.

image

string

-> The file_url parameter specifies the URL of an existing image that will be used as a reference for the generation process.

-> If the original image dimensions exceed 1536x1536 pixels, the image will be adjusted to fit within this size while preserving the original aspect ratio.

prompt

string

-> The prompt parameter is the textual input that guides the image generation process. This prompt serves as an artistic compass, shaping the visual output.

batch

int

-> The batch parameter allows you to specify the number of images to generate at once.

-> The valid range for this parameter is between 1 and 8.

height

int

-> The height parameter represents the vertical dimension of an image.

-> The valid range for the parameter is between 256 and 1536 pixels.

width

int

-> The width parameter represents the horizontal dimension of an image.

-> The valid range for the parameter is between 256 and 1536 pixels.

celery

bool

-> The celery parameter is used for queuing tasks that require extended processing time. When you enqueue a task, you receive a unique task_id. This task_id allows you to check the task's status later using the task status API, which is useful for managing and tracking long-running tasks.

num_inference_steps

int

-> The num_inference_steps parameter represents the number of denoising iterations to perform during the image generation process. Generally, more iterations can result in higher-quality images, but they also increase the time required for generation.

-> The valid range for the num_inference_steps parameter is between 1 and 50.

guidance_scale

float

-> The guidance_scale parameter determines how closely the generated image adheres to the provided prompt. Higher values result in the model following the prompt more closely, while lower values allow for more creative deviation.

-> The valid range for the guidance_scale parameter is between 1 and 30.

negative_prompt

string

-> The negative_prompt parameter allows you to specify content that you want the image generation model to avoid or minimize in the output. This can be useful for excluding certain visual elements or styles that you do not want to be present in the generated image.

gender

string

-> The gender parameter is used to guide the image generation model towards producing outputs with a specific gender representation. This can help avoid gender-related confusion or bias in the AI model's outputs.

remove_background

bool

-> When the remove_background parameter is enabled, the background of the generated image will be removed and replaced with a transparent background.

bg_color

string

-> The bg_color parameter allows you to set the background color of the generated image. The color value should be provided in hexadecimal format (e.g., #FFFFFF for white).

Response

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

{
  "time_required": "",
  "error": "",
  "error_data": "",
  "input": "",
  "output": "",
  "app_id": "",
  "task_id": "",
  "status": ""
}

Run the API

To test this API, please use the following link:

https://app.theneo.io/api-runner/qolaba/ml-apis/api-reference/face-avatar-3

PreviousFace Consistency NextImage Variation

Last updated 6 months ago