Upload and Prepare

Upload 10 to 30 images of the subject and prepare them for AI training.

POST https://api.apiframe.pro/ai-photo-upload

Headers

Name

Value

Content-Type

application/json

Authorization*

Your APIFRAME API Key

Body

Name

Type

Description

images*

[string]

Base64 of 10 to 30 images, to use for AI training. Take a look here for best input images.

ethnicity*

string

Subject ethnicity, one of 'asian', 'black', 'latino', 'middle eastern', 'native american', 'pacific islander', or 'white'

gender*

string

Subject gender, one of 'female' or 'male'

age

integer

The age of the subject

webhook_url

string

The final result and updates of this task will be posted at this URL.

webhook_secret

string

Will be passed as x-webhook-secret in the webhook call headers for authentication.

Response

// Success, the task has been submitted
{
  "task_id": "29e983ca-7e86-4017-a9e3-ef6fe9cd5f2a"
}

This endpoint doesn't generate results instantly, you can use the Fetch endpoint to fetch the result or use webhooks.

The result (posted to the webhook_url or retrieved with the Fetch endpoint) looks like this:

{
    "task_id": "29e983ca-7e86-4017-a9e3-ef6fe9cd5f2a",
    "status": "finished",
    "message": "Images ready for training",
    "expires_at": "2025-02-21T05:48:46.599Z"
}

If the job is not completed, you will get a result like this:

{
   "status": "processing",
   "message": 'Training images are being processed'
}

Code samples

const axios = require('axios');
const data = JSON.stringify({
  "images": [],
  "ethnicity": "asian",
  "gender": "female",
  "webhook_url": "https://........",
  "webhook_secret": "abc123"
});

const config = {
  method: 'post',
  maxBodyLength: Infinity,
  url: 'https://api.apiframe.pro/ai-photo-upload',
  headers: { 
    'Content-Type': 'application/json', 
    'Authorization': 'YOUR_API_KEY'
  },
  data : data
};

axios.request(config)
.then((response) => {
  console.log(JSON.stringify(response.data));
})
.catch((error) => {
  console.log(error);
});

import requests
import json

url = "https://api.apiframe.pro/ai-photo-upload"

payload = json.dumps({
  "images": [],
  "ethnicity": "asian",
  "gender": "female",
  "webhook_url": "https://........",
  "webhook_secret": "abc123"
})
headers = {
  'Content-Type': 'application/json',
  'Authorization': 'YOUR_API_KEY'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

<?php

$curl = curl_init();

curl_setopt_array($curl, array(
  CURLOPT_URL => 'https://api.apiframe.pro/ai-photo-upload',
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => '',
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 0,
  CURLOPT_FOLLOWLOCATION => true,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => 'POST',
  CURLOPT_POSTFIELDS =>'{
    "images": [],
    "ethnicity": "asian",
    "gender": "female",
    "webhook_url": "https://........",
    "webhook_secret": "abc123"
}',
  CURLOPT_HTTPHEADER => array(
    'Content-Type: application/json',
    'Authorization: YOUR_API_KEY'
  ),
));

$response = curl_exec($curl);

curl_close($curl);
echo $response;

OkHttpClient client = new OkHttpClient().newBuilder()
  .build();
MediaType mediaType = MediaType.parse("application/json");
RequestBody body = RequestBody.create(mediaType, "{\r\n    \"images\": \[ \],\r\n   \"ethnicity\": \"asian\",\r\n  \"gender\": \"female\",\r\n    \"webhook_url\": \"https://........\",\r\n    \"webhook_secret\": \"abc123\"\r\n}");
Request request = new Request.Builder()
  .url("https://api.apiframe.pro/ai-photo-upload")
  .method("POST", body)
  .addHeader("Content-Type", "application/json")
  .addHeader("Authorization", "YOUR_API_KEY")
  .build();
Response response = client.newCall(request).execute();

var headers = {
  'Content-Type': 'application/json',
  'Authorization': 'YOUR_API_KEY'
};
var data = json.encode({
  "images": [],
  "ethnicity": "asian",
  "gender": "female",
  "webhook_url": "https://........",
  "webhook_secret": "abc123"
});
var dio = Dio();
var response = await dio.request(
  'https://api.apiframe.pro/ai-photo-upload',
  options: Options(
    method: 'POST',
    headers: headers,
  ),
  data: data,
);

if (response.statusCode == 200) {
  print(json.encode(response.data));
}
else {
  print(response.statusMessage);
}

var client = new HttpClient();
var request = new HttpRequestMessage(HttpMethod.Post, "https://api.apiframe.pro/ai-photo-upload");
request.Headers.Add("Authorization", "YOUR_API_KEY");
var content = new StringContent("{\r\n  \"images\": \[ \],\r\n   \"ethnicity\": \"asian\",\r\n  \"gender\": \"female\",\r\n    \"webhook_url\": \"https://........\",\r\n    \"webhook_secret\": \"abc123\"\r\n}", null, "application/json");
request.Content = content;
var response = await client.SendAsync(request);
response.EnsureSuccessStatusCode();
Console.WriteLine(await response.Content.ReadAsStringAsync());

require "uri"
require "json"
require "net/http"

url = URI("https://api.apiframe.pro/ai-photo-upload")

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

request = Net::HTTP::Post.new(url)
request["Content-Type"] = "application/json"
request["Authorization"] = "YOUR_API_KEY"
request.body = JSON.dump({
  "images": [],
  "ethnicity": "asian",
  "gender": "female",
  "webhook_url": "https://........",
  "webhook_secret": "abc123"
})

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

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Last updated 9 months ago

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