Currently, I've been asked to write CNN code using DL4J using YOLOv2 architecture. But the problem is after the model has complete, I do a simple GUI for validation testing then the image shown is too bright and sometimes the image can be displayed. Im not sure where does this problem comes from whether at earliest stage of training or else. Here, I attach the code that I have for now. For Iterator:
public class faceMaskIterator {
private static final Logger log = org.slf4j.LoggerFactory.getLogger(faceMaskIterator.class);
private static final int seed = 123;
private static Random rng = new Random(seed);
private static String dataDir;
private static Path pathDirectory;
private static InputSplit trainData, testData;
private static final String[] allowedFormats = NativeImageLoader.ALLOWED_FORMATS;
private static final double splitRatio = 0.8;
private static final int nChannels = 3;
public static final int gridWidth = 13;
public static final int gridHeight = 13;
public static final int yolowidth = 416;
public static final int yoloheight = 416;
private static RecordReaderDataSetIterator makeIterator(InputSplit split, Path dir, int batchSize) throws Exception {
ObjectDetectionRecordReader recordReader = new ObjectDetectionRecordReader(yoloheight, yolowidth, nChannels,
gridHeight, gridWidth, new VocLabelProvider(dir.toString()));
recordReader.initialize(split);
RecordReaderDataSetIterator iter = new RecordReaderDataSetIterator(recordReader, batchSize, 1, 1,true);
iter.setPreProcessor(new ImagePreProcessingScaler(0, 1));
return iter;
}
public static RecordReaderDataSetIterator trainIterator(int batchSize) throws Exception {
return makeIterator(trainData, pathDirectory, batchSize);
}
public static RecordReaderDataSetIterator testIterator(int batchSize) throws Exception {
return makeIterator(testData, pathDirectory, batchSize);
}
public static void setup() throws IOException {
log.info("Load data...");
dataDir = Paths.get(
System.getProperty("user.home"),
Helper.getPropValues("dl4j_home.data")
).toString();
pathDirectory = Paths.get(dataDir,"face_mask_dataset");
FileSplit fileSplit = new FileSplit(new File(pathDirectory.toString()),allowedFormats,rng);
PathFilter pathFilter = new RandomPathFilter(rng,allowedFormats);
InputSplit[] sample = fileSplit.sample(pathFilter, splitRatio,1-splitRatio);
trainData = sample[0];
testData = sample[1];
}}
For training:
public class faceMaskPreTrained {
private static final Logger log = LoggerFactory.getLogger(ai.certifai.groupProjek.faceMaskPreTrained.class);
private static int seed = 420;
private static double detectionThreshold = 0.9;
private static int nBoxes = 3;
private static double lambdaNoObj = 0.7;
private static double lambdaCoord = 1.0;
private static double[][] priorBoxes = {{1, 1}, {2, 1}, {1, 2}};
private static int batchSize = 3;
private static int nEpochs = 1;
private static double learningRate = 1e-4;
private static int nClasses = 3;
private static List<String> labels;
private static File modelFilename = new File(System.getProperty("user.dir"), "generated-models/facemask_detector.zip");
private static ComputationGraph model;
private static Frame frame = null;
private static final Scalar GREEN = RGB(0, 255.0, 0);
private static final Scalar YELLOW = RGB(255, 255, 0);
private static final Scalar RED = RGB(255, 0, 0);
private static Scalar[] colormap = {GREEN, YELLOW, RED};
private static String labeltext = null;
public static void main(String[] args) throws Exception {
faceMaskIterator.setup();
RecordReaderDataSetIterator trainIter = faceMaskIterator.trainIterator(batchSize);
RecordReaderDataSetIterator testIter = faceMaskIterator.testIterator(1);
labels = trainIter.getLabels();
if (modelFilename.exists()) {
Nd4j.getRandom().setSeed(seed);
log.info("Load model...");
model = ModelSerializer.restoreComputationGraph(modelFilename);
} else {
Nd4j.getRandom().setSeed(seed);
INDArray priors = Nd4j.create(priorBoxes);
log.info("Build model...");
ComputationGraph pretrained = (ComputationGraph) YOLO2.builder().build().initPretrained();
FineTuneConfiguration fineTuneConf = getFineTuneConfiguration();
model = getComputationGraph(pretrained, priors, fineTuneConf);
System.out.println(model.summary(InputType.convolutional(
faceMaskIterator.yoloheight,
faceMaskIterator.yolowidth,
nClasses)));
log.info("Train model...");
UIServer server = UIServer.getInstance();
StatsStorage storage = new InMemoryStatsStorage();
server.attach(storage);
model.setListeners(new ScoreIterationListener(5), new StatsListener(storage,5));
for (int i = 1; i < nEpochs + 1; i++) {
trainIter.reset();
while (trainIter.hasNext()) {
model.fit(trainIter.next());
}
log.info("*** Completed epoch {} ***", i);
}
ModelSerializer.writeModel(model, modelFilename, true);
System.out.println("Model saved.");
}
// Evaluate the model's accuracy by using the test iterator.
OfflineValidationWithTestDataset(testIter);
// Inference the model and process the webcam stream and make predictions.
doInference();
}
private static ComputationGraph getComputationGraph(ComputationGraph pretrained, INDArray priors, FineTuneConfiguration fineTuneConf) {
return new TransferLearning.GraphBuilder(pretrained)
.fineTuneConfiguration(fineTuneConf)
.removeVertexKeepConnections("conv2d_23")
.removeVertexKeepConnections("outputs")
.addLayer("conv2d_23",
new ConvolutionLayer.Builder(1, 1)
.nIn(1024)
.nOut(nBoxes * (5 + nClasses))
.stride(1, 1)
.convolutionMode(ConvolutionMode.Same)
.weightInit(WeightInit.XAVIER)
.activation(Activation.IDENTITY)
.build(),
"leaky_re_lu_22")
.addLayer("outputs",
new Yolo2OutputLayer.Builder()
.lambdaNoObj(lambdaNoObj)
.lambdaCoord(lambdaCoord)
.boundingBoxPriors(priors.castTo(DataType.FLOAT))
.build(),
"conv2d_23")
.setOutputs("outputs")
.build();
}
private static FineTuneConfiguration getFineTuneConfiguration() {
return new FineTuneConfiguration.Builder()
.seed(seed)
.optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
.gradientNormalization(GradientNormalization.RenormalizeL2PerLayer)
.gradientNormalizationThreshold(1.0)
.updater(new Adam.Builder().learningRate(learningRate).build())
.l2(0.00001)
.activation(Activation.IDENTITY)
.trainingWorkspaceMode(WorkspaceMode.ENABLED)
.inferenceWorkspaceMode(WorkspaceMode.ENABLED)
.build();
}
// Evaluate visually the performance of the trained object detection model
private static void OfflineValidationWithTestDataset(RecordReaderDataSetIterator test) throws InterruptedException {
NativeImageLoader imageLoader = new NativeImageLoader();
CanvasFrame canvas = new CanvasFrame("Validate Test Dataset");
OpenCVFrameConverter.ToMat converter = new OpenCVFrameConverter.ToMat();
org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer yout = (org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer) model.getOutputLayer(0);
Mat convertedMat = new Mat();
Mat convertedMat_big = new Mat();
while (test.hasNext() && canvas.isVisible()) {
org.nd4j.linalg.dataset.DataSet ds = test.next();
INDArray features = ds.getFeatures();
INDArray results = model.outputSingle(features);
List<DetectedObject> objs = yout.getPredictedObjects(results, detectionThreshold);
YoloUtils.nms(objs, 0.4);
Mat mat = imageLoader.asMat(features);
mat.convertTo(convertedMat, CV_8U, 255, 0);
int w = mat.cols() * 2;
int h = mat.rows() * 2;
resize(convertedMat, convertedMat_big, new Size(w, h));
convertedMat_big = drawResults(objs, convertedMat_big, w, h);
canvas.showImage(converter.convert(convertedMat_big));
canvas.waitKey();
}
canvas.dispose();
}
// Stream video frames from Webcam and run them through YOLOv2 model and get predictions
private static void doInference() {
String cameraPos = "front";
int cameraNum = 0;
Thread thread = null;
NativeImageLoader loader = new NativeImageLoader(
faceMaskIterator.yolowidth,
faceMaskIterator.yoloheight,
3,
new ColorConversionTransform(COLOR_BGR2RGB));
ImagePreProcessingScaler scaler = new ImagePreProcessingScaler(0, 1);
if (!cameraPos.equals("front") && !cameraPos.equals("back")) {
try {
throw new Exception("Unknown argument for camera position. Choose between front and back");
} catch (Exception e) {
e.printStackTrace();
}
}
FrameGrabber grabber = null;
try {
grabber = FrameGrabber.createDefault(cameraNum);
} catch (FrameGrabber.Exception e) {
e.printStackTrace();
}
OpenCVFrameConverter.ToMat converter = new OpenCVFrameConverter.ToMat();
try {
grabber.start();
} catch (FrameGrabber.Exception e) {
e.printStackTrace();
}
CanvasFrame canvas = new CanvasFrame("Object Detection");
int w = grabber.getImageWidth();
int h = grabber.getImageHeight();
canvas.setCanvasSize(w, h);
while (true) {
try {
frame = grabber.grab();
} catch (FrameGrabber.Exception e) {
e.printStackTrace();
}
//if a thread is null, create new thread
if (thread == null) {
thread = new Thread(() ->
{
while (frame != null) {
try {
Mat rawImage = new Mat();
//Flip the camera if opening front camera
if (cameraPos.equals("front")) {
Mat inputImage = converter.convert(frame);
flip(inputImage, rawImage, 1);
} else {
rawImage = converter.convert(frame);
}
Mat resizeImage = new Mat();
resize(rawImage, resizeImage, new Size(faceMaskIterator.yolowidth, faceMaskIterator.yoloheight));
INDArray inputImage = loader.asMatrix(resizeImage);
scaler.transform(inputImage);
INDArray outputs = model.outputSingle(inputImage);
org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer yout = (org.deeplearning4j.nn.layers.objdetect.Yolo2OutputLayer) model.getOutputLayer(0);
List<DetectedObject> objs = yout.getPredictedObjects(outputs, detectionThreshold);
YoloUtils.nms(objs, 0.4);
rawImage = drawResults(objs, rawImage, w, h);
canvas.showImage(converter.convert(rawImage));
} catch (Exception e) {
throw new RuntimeException(e);
}
}
});
thread.start();
}
KeyEvent t = null;
try {
t = canvas.waitKey(33);
} catch (InterruptedException e) {
e.printStackTrace();
}
if ((t != null) && (t.getKeyCode() == KeyEvent.VK_Q)) {
break;
}
}
}
private static Mat drawResults(List<DetectedObject> objects, Mat mat, int w, int h) {
for (DetectedObject obj : objects) {
double[] xy1 = obj.getTopLeftXY();
double[] xy2 = obj.getBottomRightXY();
String label = labels.get(obj.getPredictedClass());
int x1 = (int) Math.round(w * xy1[0] / faceMaskIterator.gridWidth);
int y1 = (int) Math.round(h * xy1[1] / faceMaskIterator.gridHeight);
int x2 = (int) Math.round(w * xy2[0] / faceMaskIterator.gridWidth);
int y2 = (int) Math.round(h * xy2[1] / faceMaskIterator.gridHeight);
//Draw bounding box
rectangle(mat, new Point(x1, y1), new Point(x2, y2), colormap[obj.getPredictedClass()], 2, 0, 0);
//Display label text
labeltext = label + " " + String.format("%.2f", obj.getConfidence() * 100) + "%";
int[] baseline = {0};
Size textSize = getTextSize(labeltext, FONT_HERSHEY_DUPLEX, 1, 1, baseline);
rectangle(mat, new Point(x1 + 2, y2 - 2), new Point(x1 + 2 + textSize.get(0), y2 - 2 - textSize.get(1)), colormap[obj.getPredictedClass()], FILLED, 0, 0);
putText(mat, labeltext, new Point(x1 + 2, y2 - 2), FONT_HERSHEY_DUPLEX, 1, RGB(0, 0, 0));
}
return mat;
}
CanvasFrame tries to do gamma correction by default because it's typically needed by cameras used for CV, but cheap webcams usually output gamma corrected images, so make sure to let CanvasFrame know about it this way:
// We should also specify the relative monitor/camera response for proper gamma correction.
CanvasFrame frame = new CanvasFrame("Some Title", CanvasFrame.getDefaultGamma()/grabber.getGamma());
https://github.com/bytedeco/javacv/
I'm making a memory game for school and I'm having a bit of trouble hiding the tiles in my gridpane.
I've got a seperate class where I use my eventhandlers.
I used an ObservableList to fill in my gridpane with tiles but I got no idea how to make them disappear. Thanks for taking a look , I tried to use a FadeTransition in the view class.
View
public class GameView extends GridPane {
private static final int PAREN = 10;
private Label scoreSpeler1;
private Label countDown;
private Label title;
private final static Color backgroundColor = Color.rgb(225, 93, 68);
int waarde = 0;
ObservableList<Button> vakken;
public GameView() {
this.initialiseNodes();
this.layoutNodes();
this.verdwijnWaarde();
this.toonWaarde();
}
private void initialiseNodes() {
scoreSpeler1 = new Label("Score: 0");
countDown = new Label("Tijd: 60");
title = new Label("Memory");
/*knoppen met cijfers*/
vakken = FXCollections.observableArrayList(new ArrayList<>());
for (int i = 0; i < PAREN; i++) {
vakken.add(new Button(String.valueOf(waarde)));
vakken.add(new Button(String.valueOf(waarde)));
waarde++;
}
FXCollections.shuffle(vakken);
}
private void layoutNodes() {
//score en tijd plaatsen
this.add(scoreSpeler1, 0, 0);
this.add(title, 2, 0);
this.add(countDown, 4, 0);
//memory knoppen plaatsen
int k = 0;
for (int i = 0; i < 5; i++) {
for (int j = 0; j < 4; j++) {
this.add(vakken.get(k), i, j + 2);
k++;
}
}
//label uiterlijk
GridPane.setHalignment(countDown, HPos.RIGHT);
GridPane.setHalignment(title, HPos.CENTER);
title.setId("titelGame");
scoreSpeler1.setId("scoreSpeler1");
countDown.setId("countDown");
//button/memory uiterlijk
for (Button button : vakken) {
button.setPrefHeight(120);
button.setPrefWidth(90);
}
//gridpane uiterlijk
this.setGridLinesVisible(false);
this.setBackground(new Background(new BackgroundFill(backgroundColor, null, null)));
this.setHgap(15);
this.setVgap(15);
this.setPadding(new Insets(10, 10, 10, 10));
this.autosize();
this.setAlignment(Pos.CENTER);
}
public void verdwijnWaarde() {
FadeTransition verstopWaardes = new FadeTransition();
verstopWaardes.durationProperty(Duration.seconds(2), this.vakken.get(1));
verstopWaardes.setToValue(0);
verstopWaardes.play();
}
public void toonWaarde() {
FadeTransition toonWaardes = new FadeTransition();
toonWaardes.durationProperty(Duration.seconds(0.5), vakken);
toonWaardes.setToValue(1);
toonWaardes.play();
}
}
presenter
public class GamePresenter {
private MemoryModel model;
private GameView gameView;
public GamePresenter(MemoryModel model, GameView gameView){
this.model = model;
this.gameView = gameView;
addEventHandlers();
}
private void addEventHandlers(){
gameView.setOnMouseClicked(new EventHandler<MouseEvent>() {
#Override
public void handle(MouseEvent mouseEvent) {
gameView.toonWaarde();
}
});
}
private void updateView(){
}
public void addWindowEventHandlers(){
}
}
I want to make an imitative hack System. There will be 3 windows displayed on screen. Each window will show some string Constantly (like some movie scene) . However only the third (the last) window works. So how to make every window show string at the same time?
the frame class as follow:
import java.awt.*;
import java.awt.event.*;
class sys extends Thread {
private static Frame frm;
private static TextArea txa;
private int fsx, fsy, flx, fly, tsx, tsy, tlx, tly;
private String strarr[] = new String[7];
private String frmName;
public sys(String str, String SAEC[]) {
frmName = str;
strarr = SAEC;
}
public void SettingFRM(int sx, int sy, int lx, int ly) {
//frame's location and size
fsx = sx;
fsy = sy;
flx = lx;
fly = ly;
}
public void SettingTXA(int sx, int sy, int lx, int ly) {
//textArea's location and size
tsx = sx;
tsy = sy;
tlx = lx;
tly = ly;
}
public void run() {
frm = new Frame(frmName);
//the exterior design
txa = new TextArea("", 100, 100, TextArea.SCROLLBARS_BOTH);
txa.setBounds(tlx, tly, tsx, tsy);
txa.setBackground(Color.darkGray);
txa.setFont(new Font("Arial", Font.PLAIN, 16));
txa.setForeground(Color.green);
frm.setLayout(null);
frm.setSize(fsx, fsy);
frm.setLocation(flx, fly);
frm.setVisible(true);
frm.setBackground(Color.darkGray);
frm.add(txa);
while (1 != 0) {
txa.append(strarr[(int) (Math.random() * 7)]);// to obtain new string
frm.addWindowListener(new WindowAdapter() {
public void windowClosing(WindowEvent e) {
System.exit(0);
}
});
try {
sleep(200);
} catch (InterruptedException e) {
}
}
}
}
main program as follow:
public class ImitativeHackSystem {
public static void main(String[] args) throws InterruptedException {
//specific string
String strarr[] = new String[9];
strarr[0] = new String("Hacking... Time estimate 25 seconds...\n");
strarr[1] = new String("Retrying...\n");
strarr[2] = new String("Error! Code:e2130443523\n");
strarr[3] = new String("Success! IP:192.168.0.1\n");
strarr[4] = new String("picking datas...\n");
strarr[5] = new String("Anti-system started\n");
strarr[6] = new String("Has been discovering... fake random IP address\n");
strarr[7] = new String("01011010000011001000000011111101010");
strarr[8] = new String("111101010101001101101101010011010");
//object array
sys fhs[] = new sys[3];
for (int i = 0; i < 3; i++)
fhs[i] = new sys("Fake Hacking System", strarr);
fhs[0].SettingTXA(635, 690, 5, 30);
fhs[0].SettingFRM(640, 720, 0, 0);
fhs[1].SettingTXA(635, 330, 5, 30);
fhs[1].SettingFRM(640, 360, 645, 0);
fhs[2].SettingTXA(635, 330, 5, 30);
fhs[2].SettingFRM(640, 360, 645, 365);
//to execute
for (int i = 0; i < 3; i++) {
fhs[i].start();
Thread.sleep(500);
}
}
}
I want to add an image to an array. When I use Node it works, but when I use the same way to add images it does not appear when I run it. Here is my code:
public class PlatForm extends Application {
List<ImageView> platFormList = new ArrayList<>();
private Pane layout;
private Scene scene;
private AnimationTimer platFormTimer;
#Override
public void start(Stage primaryStage) throws Exception {
layout = new Pane();
scene = new Scene(layout,800,500);
primaryStage.setScene(scene);
primaryStage.show();
platFormTimer = new AnimationTimer() {
#Override
public void handle(long now) {
uploadPlatForm();
}
};
platFormTimer.start();
}
public void uploadPlatForm(){
for(ImageView platform : platFormList)
platform.setTranslateX(platform.getTranslateX() + Math.random() * 10);
if (Math.random() < 0.075) {
platFormList.add(newPlatForm());
}
}
private ImageView newPlatForm(){
ImageView platFormImg =
new ImageView(
new Image(getClass().getResourceAsStream("/image/platform.png")
)
);
layout.getChildren().add(platFormImg);
platFormImg.setTranslateY((int)(Math.random() * 14) * 40);
return platFormImg;
}
}
Trying out a simple game implementation
public class PlayerSprite extends Rectangle {
private String name;
private int playerID;
final int TILE = 32;
final int SIZE = 4;
public PlayerSprite(PlayerCharacter player, int id, Paint color) {
super(4, 4, color); //Currently a player takes up 4 points
this.name = player.getName();
this.playerID = id;
}
public int getPlayerSize() {
return SIZE;
}
}
My playerSprites are just rectangles that currently aren't showing. The PlayerSprite constructor is called from an object called LocationHome that extends Region.
public class LocationHome extends Region {
Image homeBGimage;
int lheight, lwidth;
public void LocationHome(Location location) {
this.setStyle("-fx-background-image: url(" + "'images/blackgrid.jpeg'" + ");" + "-fx-background-size: cover;");
lheight = location.getLocationHeight(); //Location method call
lwidth = location.getLocationWidth(); //Location method call
this.setPrefSize(lheight, lwidth);
}
public void placePlayer(PlayerCharacter player) {
//Create a PlayerSprite and position it as wanted
Image img = new Image("images/blackgrid.jpeg");
PlayerSprite playerSprite = new PlayerSprite(player, player.getID(), Color.AQUA);
this.layoutInArea(playerSprite, player.getPosition().getUL().getX(), player.getPosition().getUL().getY(), playerSprite.getPlayerSize(), playerSprite.getPlayerSize(), 0, HPos.CENTER, VPos.BASELINE);
this.getChildren().addAll(playerSprite);
}
}
And then, for my main JavaFX application...
Group rootPane = new Group();
World guiWorld = new WorldImpl(); //This is my game model
BorderPane locationPane = new BorderPane(); //locationPane designated for rendering a Location
guiCharacters = new HashMap<>();
int id=0;
for(PlayerCharacter each : guiWorld.getCharacters()) {
guiCharacters.put(id, each);
gridLocation.placePlayer(each);
id++;
}
locationPane.getChildren().addAll(gridLocation);
rootPane.getChildren().add(locationPane);
currScene = new Scene( rootPane, 1024, 1024 ); //Passing the rootPane/group to currScene
stage.setScene(currScene); //Make currScene contents visible
stage.setTitle("Spoon Game");
stage.show();