FaceID

BETA

Input images

See example prompts in the gallery

Overview

FaceID is a model adapter allowing to generate image while preserving a person identity without fine-tuning. Input images can be as few as just one image. The adapter was trained on human faces and cannot be used for pets or other subjects.

Usage

Generate a placeholder fine-tune dataset which will contain the person images. The fine-tune will not go through training and will be immediately ready.
Generate the image using the FaceID adapter using a syntax similar to LoRA - <faceid:ID:1>

Notes

Use cfg_scale=3
FaceID can work nicely together with Face Swap to improve similarity.
Disable Face-Swap in case your prompt is animation style. Additionally, make sure to select an animated model from the gallery.
For fast generation use the LCM schedulers.
For realistic images, please consider enabling face-correct to improve facial features.
When creating a fine-tune: Base-model is only used as a default for UI generation but does not affect FaceID.
When creating a fine-tune: steps and training_face_correct are not used for FaceID.

API

FaceID is an adapter loaded on top of a base model. As such the inference needs to take place on a model from the gallery. The fine-tune's trained_at is set upon creation and there is no training time. As such no callback is needed.

danger

If you are receiving 422 error model_type=faceid is not supported. Use a checkpoint instead - Change the request URL to https://api.astria.ai/tunes/690204/prompts with 690204 as a hard-coded tune_id of Realistic Vision v5.1 from the gallery. See explanation above.

Step 1: Create fine-tune

POST /tunes

cURL
Node.js
Python

# With images as multipart/form-data
# Hard coded tune id of Realistic Vision v5.1 from the gallery - https://www.astria.ai/gallery/tunes 
# https://www.astria.ai/gallery/tunes/690204/prompts
curl -X POST -H "Authorization: Bearer $API_KEY" https://api.astria.ai/tunes \
          -F tune[title]="John Doe - UUID - 1234-6789-1234-56789" \
          -F tune[name]=man \
          -F tune[model_type]="faceid" \
          -F tune[callback]="https://optional-callback-url.com/webhooks/astria?user_id=1&tune_id=1" \
          -F tune[base_tune_id]=690204 \
          -F "tune[images][][email protected]" \
          -F "tune[images][][email protected]" \
          -F "tune[images][][email protected]" \
          -F "tune[images][][email protected]"

# With image_urls as form-data
curl -X POST -H "Authorization: Bearer $API_KEY" https://api.astria.ai/tunes \
          -F tune[title]="John Doe - UUID - 1234-6789-1234-56789" \
          -F tune[name]=man \
          -F tune[model_type]="faceid" \
          -F tune[callback]="https://optional-callback-url.com/to-your-service-when-ready?user_id=1&tune_id=1" \
          -F tune[base_tune_id]=690204 \
          -F "tune[image_urls][]=https://i.imgur.com/HLHBnl9.jpeg" \
          -F "tune[image_urls][]=https://i.imgur.com/HLHBnl9.jpeg" \
          -F "tune[image_urls][]=https://i.imgur.com/HLHBnl9.jpeg" \
          -F "tune[image_urls][]=https://i.imgur.com/HLHBnl9.jpeg"
          
# As JSON
cat > data.json <<- EOM
{
  "tune": {
    "title": "John Doe - UUID - 1234-6789-1234-56789",
    "name": "man",
    "model_type": "faceid",
    "callback": "https://optional-callback-url.com/to-your-service-when-ready?user_id=1&tune_id=1",
    "image_urls": [
      "https://i.imgur.com/HLHBnl9.jpeg",
      "https://i.imgur.com/HLHBnl9.jpeg",
      "https://i.imgur.com/HLHBnl9.jpeg",
      "https://i.imgur.com/HLHBnl9.jpeg"
    ]
  }
}
EOM

curl -X POST -H"Content-Type: application/json" -H "Authorization: Bearer $API_KEY" --data @data.json  https://api.astria.ai/tunes          

// NodeJS 16
// With image_urls and fetch()
// For NodeJS 18 - do NOT import the below as it is built-in
import fetch from "node-fetch";

const API_KEY = 'sd_XXXXXX';
const DOMAIN = 'https://api.astria.ai';

function createTune() {
  let options = {
    method: 'POST',
    headers: { 'Authorization': 'Bearer ' + API_KEY, 'Content-Type': 'application/json' },
    body: JSON.stringify({
      tune: {
        "title": 'John Doe - UUID - 1234-6789-1234-56789',
        // Hard coded tune id of Realistic Vision v5.1 from the gallery - https://www.astria.ai/gallery/tunes 
        // https://www.astria.ai/gallery/tunes/690204/prompts
        "base_tune_id": 690204,
        "name": "man",
        "model_type": "faceid",
        "image_urls": [
          "https://i.imgur.com/HLHBnl9.jpeg",
          "https://i.imgur.com/HLHBnl9.jpeg",
          "https://i.imgur.com/HLHBnl9.jpeg",
          "https://i.imgur.com/HLHBnl9.jpeg"
        ]
      }
    })
  };
  return fetch(DOMAIN + '/tunes', options)
    .then(r => r.json())
    .then(r => console.log(r))
}

createTune()


/// With form-data, fetch()
// For NodeJS 18 - do NOT import the two below as they are built-in
import fetch from "node-fetch";
import FormData from 'form-data';
import fs from 'fs';

const API_KEY = 'sd_XXXX';
const DOMAIN = 'https://api.astria.ai';
function createTune() {
  let formData = new FormData();
  formData.append('tune[title]', 'John Doe - UUID - 1234-6789-1234-56789');
  formData.append('tune[model_type]', 'faceid');
  // Hard coded tune id of Realistic Vision v5.1 from the gallery - https://www.astria.ai/gallery/tunes 
  // https://www.astria.ai/gallery/tunes/690204/prompts
  formData.append('tune[base_tune_id]', 690204);
  formData.append('tune[name]', 'man');
  // Load all JPGs from ./samples directory and append to FormData
  let files = fs.readdirSync('./samples');
  files.forEach(file => {
    if(file.endsWith('.jpg')) {
      formData.append('tune[images][]', fs.createReadStream(`./samples/${file}`), file);
    }
  });
  formData.append('tune[callback]', 'https://optional-callback-url.com/to-your-service-when-ready?user_id=1&tune_id=1');

  let options = {
    method: 'POST',
    headers: {
      'Authorization': 'Bearer ' + API_KEY
    },
    body: formData
  };
  return fetch(DOMAIN + '/tunes', options)
    .then(r => r.json())
    .then(r => console.log(r));
}

createTune();

import requests
headers = {'Authorization': f'Bearer {API_KEY}'}

def load_image(file_path):
  with open(file_path, "rb") as f:
    return f.read()

# Assuming `tune.images` are already defined in your context
# If not, you should define them before the below code

image_data = load_image("assets/image.jpeg")

data = {
  "tune[title]": "John Doe - UUID - 1234-6789-1234-56789",
  "tune[name]": "man",
  "tune[base_tune_id]": 690204,
  "tune[model_type]": "faceid",
  "tune[token]": "ohwx"
}
files = []

for image in tune.images:
  image_data = load_image(image)  # Assuming image is a file path
  files.append(("tune[images][]", image_data))

API_URL = 'https://api.astria.ai/tunes'
response = requests.post(API_URL, data=data, files=files, headers=headers)
response.raise_for_status()

Response

[
  {
    "id": 1,
    "title": "John Doe",
    "name": "woman",
    "token": "ohwx",
    "base_tune_id": null,
    "args": null,
    "steps": null,
    "face_crop": null,
    "training_face_correct": false,
    "ckpt_url": "https://sdbooth2-production.s3.amazonaws.com/mock",
    "ckpt_urls": [
      "https://sdbooth2-production.s3.amazonaws.com/mock"
    ],
    "eta": "2023-10-02T14:32:40.363Z",
    "trained_at": "2023-10-02T14:32:40.363Z",
    "started_training_at": "2023-10-02T14:32:05.229Z",
    "expires_at": "2023-11-01T14:32:40.363Z",
    "created_at": "2023-10-02T14:32:05.067Z",
    "branch": "sd15",
    "model_type": "faceid",
    "updated_at": "2023-10-02T14:32:40.363Z",
    "url": "https://www.astria.ai/tunes/788416.json",
    "orig_images": [
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock"
    ]
  },
  {
    "id": 775459,
    "title": "Marry Jane",
    "name": null,
    "is_api": false,
    "token": "ohwx",
    "base_tune_id": null,
    "args": null,
    "steps": null,
    "face_crop": null,
    "training_face_correct": null,
    "ckpt_url": "https://sdbooth2-production.s3.amazonaws.com/mock",
    "ckpt_urls": [
      "https://sdbooth2-production.s3.amazonaws.com/mock"
    ],
    "eta": "2023-09-23T16:07:49.137Z",
    "trained_at": "2023-09-23T16:07:49.137Z",
    "started_training_at": "2023-09-23T16:07:37.334Z",
    "expires_at": "2023-10-23T16:07:49.137Z",
    "created_at": "2023-09-23T16:07:36.606Z",
    "branch": "sd15",
    "model_type": "faceid",
    "updated_at": "2023-09-23T16:07:49.138Z",
    "url": "https://www.astria.ai/tunes/775459.json",
    "orig_images": [
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock",
      "https://sdbooth2-production.s3.amazonaws.com/mock"
    ]
  }
 ]

Step 2: Create prompts

POST /tunes/:id/prompts

cURL
Node.js
Python

# Note the hard-coded 690204 which is the tune_id of Realistic Vision v5.1 from the gallery
curl -X POST -H "Authorization: Bearer $API_KEY" https://api.astria.ai/tunes/690204/prompts \
          -F prompt[text]="<faceid:tune_id:strength> woman trekking in the alps" \
          -F prompt[negative_prompt]="" \
          -F prompt[super_resolution]=true \
          -F prompt[face_correct]=true \
          -F prompt[face_swap]=true \
          -F prompt[callback]="https://optional-callback-url.com/to-your-service-when-ready?prompt_id=1" 

const fetch = require('node-fetch');
const FormData = require('form-data');

// Note the hard-coded 690204 which is the tune_id of Realistic Vision v5.1 from the gallery
const API_URL = 'https://api.astria.ai/tunes/690204/prompts';
const API_KEY = 'YOUR_API_KEY'; // Replace with your actual API key
const headers = { Authorization: `Bearer ${API_KEY}` }

const form = new FormData();
form.append('prompt[text]', '<faceid:tune_id:strength> woman trekking in the alps');
form.append('prompt[negative_prompt]', '');
form.append('prompt[super_resolution]', true);
form.append('prompt[face_correct]', true);
form.append('prompt[face_swap]', true);
form.append('prompt[callback]', 'https://optional-callback-url.com/to-your-service-when-ready?prompt_id=1');

fetch(API_URL, {
  method: 'POST',
  headers: headers,
  body: form
}).then(response => response.json())

import requests

# Note the hard-coded 690204 which is the tune_id of Realistic Vision v5.1 from the gallery
API_URL = 'https://api.astria.ai/tunes/690204/prompts'
API_KEY = 'YOUR_API_KEY'  # Replace with your actual API key

headers = {
    'Authorization': f'Bearer {API_KEY}'
}

data = {
  'prompt[text]': '<faceid:tune_id:strength> woman trekking in the alps',
  'prompt[negative_prompt]': '',
  'prompt[super_resolution]': True,
  'prompt[face_correct]': True,
  'prompt[face_swap]': True,
  'prompt[callback]': 'https://optional-callback-url.com/to-your-service-when-ready?prompt_id=1'
}
files = []
files.append((f"tune[prompts_attributes][{i}][input_image]", load_image(prompt['input_image'])))

response = requests.post(API_URL, headers=headers, data=data)

FaceID

Overview​

Usage​

Notes​

API​

Step 1: Create fine-tune​

POST /tunes​

Response​

Step 2: Create prompts​

POST /tunes/:id/prompts​