testMSEmotion.groovy

import java.awt.image.BufferedImage;
import com.neuronrobotics.imageprovider.Detection;
import java.util.List;
import javax.imageio.ImageIO;
import java.net.*;
import java.io.BufferedReader;
import org.apache.commons.io.IOUtils;
import com.google.gson.*;

double happyThreshold = 0.9

/*
OpenCVImageProvider camera0=null;
if(DeviceManager.getSpecificDevice(OpenCVImageProvider.class, "camera")==null){
	BowlerStudio.speak("I did not fine a device called camera. Connecting to camera 0.");
	camera0 = new OpenCVImageProvider(0);// grab the first camera
	DeviceManager.addConnection(camera0,"camera");
}else{
	camera0 = (OpenCVImageProvider)DeviceManager.getSpecificDevice(OpenCVImageProvider.class, "camera");
}

// Starting with the connected camera from BowlerStudio
println(camera0)
//Create the default detector using "lbpcascade_frontalface.xml" 
//IObjectDetector detector = new HaarDetector("lbpcascade_frontalface.xml")
// Create the input and display images. The display is where the detector writes its detections overlay on the input image
BufferedImage inputImage = AbstractImageProvider.newBufferImage(640,480)
BufferedImage displayImage = AbstractImageProvider.newBufferImage(640,480)
// Loop checking the camera for faces
while(!Thread.interrupted()){
	camera0.getLatestImage(inputImage,displayImage)               // capture image
	
	// http://stackoverflow.com/questions/8656085/how-to-send-an-image-from-web-service-in-spring
	// Create a byte array output stream.
	ByteArrayOutputStream bao = new ByteArrayOutputStream();

	// Write to output stream
	ImageIO.write(inputImage, "jpg", bao);

    URL u = new URL("https://api.projectoxford.ai/emotion/v1.0/recognize");
    HttpURLConnection conn = (HttpURLConnection) u.openConnection();
    conn.setDoOutput(true);
    conn.setRequestMethod("POST");
    conn.setRequestProperty( "Ocp-Apim-Subscription-Key", "56a40f4cbaba4ee3b4ac8c72c41c54e5" );
    conn.setRequestProperty( "Content-Type", "application/octet-stream");
    conn.setRequestProperty( "Content-Length", String.valueOf(bao.size()));
    OutputStream os = conn.getOutputStream();
    os.write(bao.toByteArray());
    
    int responseCode = conn.getResponseCode();
    if (responseCode != 200) {
        println responseCode;
        String responseMessage = conn.getResponseMessage();
        println responseMessage;
    }

    String s = IOUtils.toString(conn.getInputStream(), "UTF-8");
//    println s
    try {
        JsonArray jsonArray = new JsonParser().parse(s).getAsJsonArray();
        if (jsonArray.size() == 0){
        	println "no face"
        } else {
        	double happiness = jsonArray.get(0).getAsJsonObject().get("scores").getAsJsonObject().get("happiness").getAsDouble()
        	println happiness
        	if (happiness > happyThreshold){
        		println "unhappinize"
        		//slap()
        	}
        }
    
    } catch (Exception e) {
    	 e.printStackTrace()()
    }

	Thread.sleep(2850)
}

*/

Closure calcHome = { BufferedImage inputImage -> 
	ByteArrayOutputStream bao = new ByteArrayOutputStream();

	// Write to output stream
	ImageIO.write(inputImage, "jpg", bao);

    URL u = new URL("https://api.projectoxford.ai/emotion/v1.0/recognize");
    HttpURLConnection conn = (HttpURLConnection) u.openConnection();
    conn.setDoOutput(true);
    conn.setRequestMethod("POST");
    conn.setRequestProperty( "Ocp-Apim-Subscription-Key", "56a40f4cbaba4ee3b4ac8c72c41c54e5" );
    conn.setRequestProperty( "Content-Type", "application/octet-stream");
    conn.setRequestProperty( "Content-Length", String.valueOf(bao.size()));
    OutputStream os = conn.getOutputStream();
    os.write(bao.toByteArray());
    
    int responseCode = conn.getResponseCode();
    if (responseCode != 200) {
        println responseCode;
        String responseMessage = conn.getResponseMessage();
        println responseMessage;
    }

    String s = IOUtils.toString(conn.getInputStream(), "UTF-8");
//    println s
    try {
        JsonArray jsonArray = new JsonParser().parse(s).getAsJsonArray();
        if (jsonArray.size() == 0){
        	println "no face"
        	return true
        } else {
        	double happiness = jsonArray.get(0).getAsJsonObject().get("scores").getAsJsonObject().get("happiness").getAsDouble()
        	println happiness
        	if (happiness > happyThreshold){
        		println "too happy"
        		return true
        	} else {
        		return false
        	}
        }
    
    } catch (Exception e) {
    	 e.printStackTrace()()
    }		
}

return calcHome