com.ibm.streamsx.edgevideo.device.NonEdgentFaceDetectApp.java Source code

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Here is the source code for com.ibm.streamsx.edgevideo.device.NonEdgentFaceDetectApp.java

Source

/*
# Licensed Materials - Property of IBM
# Copyright IBM Corp. 2017
 */
package com.ibm.streamsx.edgevideo.device;

import java.util.concurrent.TimeUnit;

import org.opencv.core.Mat;

/**
 * A simple (non-Edgent) face detection demo using OpenCV.  
 * 
 * <p>With appropriate setup, runs on OSX, Raspberry Pi, ...
 * 
 * <p>It opens the camera and grabs and process frames.
 * Each detected face in the frame is "boxed" and the frame is displayed in window.
 * 
 * <p>The OpenCV processing is:
 * <pre>
 * grab a frame -> resize -> toGrayscale -> detect faces -> extract faces -> render
 * </pre>
 * 
 * <p>Type this command before starting the program to ensure
 * that OpenCV will be able to use the Raspberry Pi camera
 * <pre>
 * sudo modprobe bcm2835-v4l2
 * </pre>
 */
public class NonEdgentFaceDetectApp extends AbstractFaceDetectApp {
    long frameCnt;
    long lastReportMillis;
    long startMillis = System.currentTimeMillis();

    public static void main(String args[]) throws Exception {
        new NonEdgentFaceDetectApp().run(args);
    }

    /**
     * Do the continuous face detection processing and render images.
     * @throws Exception
     */
    @Override
    protected void runFaceDetection() throws Exception {

        while (true) {

            // Grab a frame
            stats.getFrame.markStart();
            Mat rawRgbFrame = camera.grabFrame();
            stats.getFrame.markEnd();

            // Process it
            if (!rawRgbFrame.empty()) {

                stats.imgProcess.markStart();
                FacesData facesData = faceDetector.detectFaces(rawRgbFrame);
                stats.imgProcess.markEnd();

                //System.out.println(now()+" - Detected faces : "+data.faces.size());

                // render images
                stats.render.markStart();
                renderImages(facesData);
                stats.render.markEnd();

                // Note: lacks publish data to Enterprise IoT hub
            }

            stats.reportFrameProcessed();

            // Note: lacks ability to dynamically control the poll rate
            // Note the following yields "with fixed delay" vs Topology.poll()'s "at fixed rate" 
            Thread.sleep(TimeUnit.MILLISECONDS.convert(sensorPollValue, sensorPollUnit));
        }

    }

}