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Todo// put next steps for developer here |
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| API credentials |
| API URL |
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https://seva360.com/care/developer/predict
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| Secret key |
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/* required java version jdk1.8 or latest */
import java.io.File;
import java.io.FileInputStream;
import java.io.FileWriter;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.OutputStreamWriter;
import java.net.HttpURLConnection;
import java.net.URL;
import java.net.URLEncoder;
import java.util.Base64;
import java.util.Scanner;
import com.google.gson.Gson;
/* download gson.jar from=> https://repo1.maven.org/maven2/com/google/code/gson/gson/2.6.2/gson-2.6.2.jar */
public class SevamobRestAPISample {
//Sevamob AI Developer URL
public String sevamobDeveloperURL = "https://seva360.com/care/developer/predict";
//your email id
public String email= "place your email here" ;
//your secretKey
public String secretKey= "place your key here" ;
//Name of the module
public String module = "model name here"; //blood/urine/sputum/vision
//To specify the type of detection
public String detect = "all"; // or cellCount
//Threashold value
public float threshold = .7F;
String path = ""; // Complete path to your file
String filename = ""; // Name of the file
public static void main(String[] args) throws IOException{
SevamobRestAPISample ai = new SevamobRestAPISample();
ai.sendPredictionData();
}
public void sendPredictionData() throws IOException{
//Get Encoded Image
String base64Image = encodeFromFile(path, filename);
System.out.println(base64Image); // It prints the image in base64 encoding
//Prepare the array of base 64 images and pass the jsonarray
String[] sampleImages = {base64Image,base64Image}; //you can pass multiple sample images
Gson g = new Gson();
String jsonImageArray = g.toJson(sampleImages);
HttpURLConnection connection = (HttpURLConnection) new URL(sevamobDeveloperURL).openConnection();
connection.setRequestMethod("POST");
String postData = "emailId=" + URLEncoder.encode(email);
postData += "&module=" + URLEncoder.encode(module);
postData += "&secretKey=" + URLEncoder.encode(secretKey);
postData += "&detect=" + URLEncoder.encode(detect);
postData += "&images=" + URLEncoder.encode(jsonImageArray);
postData += "&threshold =" + 7;
connection.setDoOutput(true);
OutputStreamWriter wr = new OutputStreamWriter(connection.getOutputStream());
wr.write(postData);
wr.flush();
String response = "";
int responseCode = connection.getResponseCode();
if(responseCode == 200){
System.out.println("POST was successful.");
Scanner scanner = new Scanner(connection.getInputStream());
while(scanner.hasNextLine()){
response += scanner.nextLine();
response += "\n";
}
scanner.close();
System.out.println(response);
try {
FileWriter file = new FileWriter(path+"\\sevamobPredictResponse.json");
file.write(response);
file.close();
System.out.println("Response sevaed in sevamobPredictResponse.json file at " +path );
}catch (Exception e) {
// TODO: handle exception
}
}
else if(responseCode == 401){
System.out.println("Wrong data.");
}
}
/**
* It Encodes a File in Base 64 String , Encoding = US-ASCAII
* @param filename
* @return
* @throws java.io.IOException
*/
public static String encodeFromFile( String path, String filename )
throws java.io.IOException {
String base64Image = "";
File file = new File(path+"\\"+filename);
try (FileInputStream imageInFile = new FileInputStream(file)) {
// Reading a Image file from file system
byte imageData[] = new byte[(int) file.length()];
imageInFile.read(imageData);
base64Image = Base64.getEncoder().encodeToString(imageData);
} catch (FileNotFoundException e) {
System.out.println("Image not found" + e);
} catch (IOException ioe) {
System.out.println("Exception while reading the Image " + ioe);
}
return base64Image;
} // end encodeFromFile
}
<![CDATA[
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="X-UA-Compatible" content="ie=edge">
<title>Sevamob AI - Java Script Client</title>
<script>
function sendPredictionData()
{
var imageB64 = document.getElementById('imageB64').value;
var sample_img = [];
sample_img[0] = imageB64; //You can add multiple base64 images in this array and then pass it as json array
//alert('sending image to predict = ' + imageB64);
document.getElementById("predict_responseDiv").style.display = '';
var postData = "emailId=YOUR_EMAIL_ID";
postData += "&module=" + encodeURI("model name"); //blood/urine/vision/sputum
postData += "&secretKey=" + encodeURI("YOUR_SECRET_KEY");
postData += "&detect=" + encodeURI("all");
postData += "&images=" + encodeURIComponent(JSON.stringify(sample_img ));//imageB64);
postData += "&threshold =" + 7; // TBD : We May remove this if found not useful
var ajaxRequest = new XMLHttpRequest();
ajaxRequest.onreadystatechange = function(){
if(ajaxRequest.readyState == 4){
if(ajaxRequest.status == 200){
//var person = JSON.parse(ajaxRequest.responseText);
var responseText = ajaxRequest.responseText;
//alert('got = ' + responseText);
document.getElementById("predict_response").value = responseText;
}
}
}
ajaxRequest.open('POST', 'https://seva360.com/care/developer/predict');
ajaxRequest.setRequestHeader("Content-type", "application/x-www-form-urlencoded");
ajaxRequest.send(postData);
}
function readFile()
{
if (this.files && this.files[0])
{
var FR= new FileReader();
FR.addEventListener("load", function(e) {
document.getElementById("img").src = e.target.result;
document.getElementById("img").style.display = '';
var imageB64 = e.target.result.substring(e.target.result.indexOf('base64,')+7);
document.getElementById("imageB64").value = imageB64;
// document.getElementById("imageB64").innerHTML = e.target.result;
});
FR.readAsDataURL( this.files[0] );
}
}
</script>
</head>
<body>
<h1>Sevamob AI - Java Script Client Demo</h1>
<p>(Upload a jpg file)</p>
<input id="base64ImageValueDiv" type='file'>
<p><img id="img" height="150" style="display: none;"></p>
Base64 Encoded Image <br><textarea id="imageB64" rows="5"></textarea>
<p>
<button type="button" onclick="sendPredictionData()">Send</button>
</p>
<script>
document.getElementById("base64ImageValueDiv").addEventListener("change", readFile);
</script>
<div id="predict_responseDiv" style="display: none;"><h3>AI-Prediction Response</h3>
<textarea id="predict_response" rows="8" cols="50"> please wait.....</textarea>
</div>
</body>
</html>
]]>
<![CDATA[
Sample Image
<p><img id="img" height="150" src="PATH_TO_IMAGE"></p>
<?php
// Get the image and convert into string
$img = file_get_contents('PATH_TO_IMAGE');
// Encode the image string data into base64
$imgdata = base64_encode($img);
//create array of base64 images
$jsonImageArray = array($imgdata);
$jsonImgStr = json_encode($jsonImageArray);
echo 'Base64 Encoded Image <br><textarea id="imageB64" rows="5">'.$imgdata.'</textarea> <br><br>Please wait...';
$key = urlencode("YOUR_SECRET_KEY_HERE");
$postData = 'emailId=YOUR_EMAIL_ID_HERE';
$postData = $postData.'&secretKey='.$key;
$postData = $postData.'&module=MODULE_NAME_HERE'; //blood/urine/vision/sputum
$postData = $postData.'&detect=all';
$postData = $postData.'&images='.urlencode($jsonImgStr);
$postData = $postData.'&threshold=.7';
$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, "PREDICT_URL_HERE");
curl_setopt($ch, CURLOPT_POST, 1);
curl_setopt($ch, CURLOPT_POSTFIELDS, $postData);
//$result = curl_exec($ch);
?>
<div id="predict_responseDiv" >
<h3>AI-Prediction Response</h3>
<textarea id="predict_response" rows="8" cols="50">
Please wait.......<?php curl_exec($ch); ?>
</textarea>
</div>
<?php
//print_r($result);
curl_close($ch);
?>
]]>
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| About us |
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seva360.com is an artificial intelligence enabled healthcare platform for patients, providers and developers. It is operated by Sevamob Ventures USA.
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The patients get the following benefits:
- Manage their health and get access to relevant information and services
- Maintain and track electronic medical record
- Find doctors. Schedule appointments (video, clinic or home) and request second opinions
- Participate in support groups. Post testimonials on medical professionals whose services they use
- Maintain health statistics like blood sugar, weight etc in a care journal for ongoing care by the medical professionals
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The medical professionals get the following benefits:
- Generate more revenue and offer better care, based on relevant data and electronic medical record
- Get patient leads through referrals and requests for appointments (video, clinic or home) and web consutlations
- Streamlined care through practice management, artificial intelligence
- Take long term care of patients via care journals in home care
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The developers get the following benefits:
- Quickly integrate Sevamob AI in their web or mobile application via a REST API
- Analyze blood, vision, urine and sputum samples with a simple call
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