Alpha-0.1 Commit
Tested working on Linux system in development environment. Input pictures are stretched to fit their slots. Configuration lies within the source files.dev
Peery
8 years ago
parent
26c183c1e5
commit
9152b37c9f
@ -0,0 +1,122 @@
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package peery;
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import java.awt.image.BufferedImage;
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import java.io.File;
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import java.util.ArrayList;
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import java.util.HashMap;
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import peery.file.FileHandler;
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import peery.log.Log;
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import peery.log.LogLevel;
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import peery.picture.ImageAnalyzer;
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public class Mosaic {
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public static final String versionString = "Alpha-0.1";
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private static final String outputName = "Output";
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private static final int gridX = 100, gridY = 100, targetMulti = 4,
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alphaThreshhold = 30,
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adaptionCount = 300;
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private static final double adaptionStep = 1.1, gridErrorThresh = 0.15;
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/*
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*
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* TODO improve performance during closest match search. -> Loads ALOT of images
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* TODO investigate picture stretching -> is ImageUtils.resizeImage() even used?
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* TODO investigate why so few slots are actually present, I specified way more! <---
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*
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*
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* TODO alphaThreshhold is currently dead
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*/
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public FileHandler fh;
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public ImageAnalyzer ia;
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public Mosaic(){
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fh = new FileHandler("resources");
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Log.log(LogLevel.Info, "Starting Mosaic "+versionString);
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ia = new ImageAnalyzer(fh);
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createMosaic();
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}
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public void createMosaic(){
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ia.rasterizeTarget(gridX, gridY, targetMulti, gridErrorThresh, adaptionCount, adaptionStep);
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HashMap<String, Integer> index = fh.loadIndex();
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//Loading index
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if(index == null){
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Log.log(LogLevel.Info, "No index loaded. Working with empty one ...");
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index = new HashMap<String, Integer>();
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}
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//
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//Preparing Setup
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ArrayList<String> fileList = fh.listInputFiles();
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Log.log(LogLevel.Info, "Starting classification of Input now ...");
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int count = 0;
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for(String path: fileList){
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Log.log(LogLevel.Info, "Processing file "+(count++)+"/"+fileList.size()+" ...");
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File file = new File(path);
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BufferedImage img = fh.loadImage(file);
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if(img == null){
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continue;
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}
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int rgb = ia.classifyImage(img, file, alphaThreshhold);
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fh.appendToIndex(index, file, rgb);
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}
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Log.log(LogLevel.Info, "Finished classification. Index is ready for production. Reloading index ...");
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index = fh.loadIndex();
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Log.log(LogLevel.Debug, "Canvas is "+ia.canvas.getWidth()+"x"+ia.canvas.getHeight()+" big.");
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Log.log(LogLevel.Debug, "Grid will span "+ia.slotWidth*gridX+"x"+ia.slotHeight*gridY+" .");
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Log.log(LogLevel.Info, "Starting classification of target slots.");
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count = 0;
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int maxSlot = ia.slotX*ia.slotY;
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int[][] slotRGBs = new int[ia.slotX][ia.slotY];
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for(int x = 0; x < ia.slotX; x++){
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for(int y = 0; y < ia.slotY; y++){
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Log.log(LogLevel.Info, "Processing slot "+(count++)+"/"+maxSlot+" ...");
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slotRGBs[x][y] = ia.classifySlot(x, y, ia.target);
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}
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}
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Log.log(LogLevel.Info, "Finished classification of target slots.");
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Log.log(LogLevel.Info, "Matching indexed Images on slots ...");
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count = 0;
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ArrayList<File> fileHolder = new ArrayList<File>();
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ArrayList<BufferedImage> imgHolder = new ArrayList<BufferedImage>();
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for(int x = 0; x < slotRGBs.length; x++){
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for(int y = 0; y < slotRGBs[x].length; y++){
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Log.log(LogLevel.Info, "Matching slot "+(count++)+"/"+maxSlot+" ...");
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HashMap<String, Integer> matches = ia.matchClosestIndex(index, slotRGBs[x][y], 0);
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String match = matches.keySet().toArray()[0].toString();
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File file = new File(fh.InputImagesFolder+fh.fs+match);
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/*
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BufferedImage plain = new BufferedImage(ia.slotWidth, ia.slotHeight, BufferedImage.TYPE_INT_RGB);
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Graphics2D g2 = (Graphics2D) plain.getGraphics();
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g2.setColor(new Color(slotRGBs[x][y]));
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g2.fillRect(0, 0, plain.getWidth(), plain.getHeight());
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g2.dispose();
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ia.placeImage(x, y, plain);
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*/
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BufferedImage img;
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if(!fileHolder.contains(file)){
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fileHolder.add(file);
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img = fh.loadImage(file);
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imgHolder.add(img);
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}else{
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int i = fileHolder.indexOf(file);
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img = imgHolder.get(i);
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}
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ia.placeImage(x, y, img);
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}
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}
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Log.log(LogLevel.Info, "Finished matching. Output is done ...");
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fh.saveImage(ia.canvas, new File(fh.OutputFolder+fh.fs+outputName+"-"+fh.OutputFolder.listFiles().length+".png"));
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}
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public static void main(String[] args){
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new Mosaic();
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}
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}
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@ -1,67 +0,0 @@
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package peery.picture;
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import java.awt.Color;
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import java.awt.image.BufferedImage;
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import java.awt.image.ColorModel;
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import java.io.File;
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import peery.file.FileHandler;
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import peery.log.Log;
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import peery.log.LogLevel;
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public class Classifier {
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public BufferedImage target;
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public Classifier(FileHandler fh){
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BufferedImage target = fh.loadImage(fh.TargetImageFile);
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}
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public void rasterizeTarget(){
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}
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/**
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* Plain calculation of average Color of an Image via RGB.
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* Takes average of RGB values of each pixel.
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* Does not account for alpha.
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* @param img Image to process
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* @param alphaThreshhold value under which pixels are discarded
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* @return RGB value of the average color
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*/
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public int classifyImage(BufferedImage img, File file, int alphaTreshhold){
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int width = img.getWidth();
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int height = img.getHeight();
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Log.log(LogLevel.Debug, "Starting classification of "+file.getPath()+" with width:"+
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width+" and height:"+height+" ...");
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ColorModel cm = ColorModel.getRGBdefault();
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float red = 0, green = 0, blue = 0;
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int pixels = 0;
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for(int x = 0; x < img.getWidth(); x++){
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for(int y = 0; y < img.getHeight(); y++){
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int rgb = img.getRGB(x, y);
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red += cm.getRed(rgb);
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blue += cm.getBlue(rgb);
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green += cm.getGreen(rgb);
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pixels++;
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}
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}
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red = red/pixels;
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green = green/pixels;
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blue = blue/pixels;
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int rgb = new Color((int)red, (int)green, (int)blue).getRGB();
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Log.log(LogLevel.Debug, "Classified "+file.getPath()+" with following rgb result: value:"+rgb+
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" red:"+red+", green:"+green+", blue:"+blue);
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return rgb;
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}
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public static void main(String[] args){
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FileHandler fh = new FileHandler("/home/peery/Software_Projects/EclipseWorkspace/Picture Mosaic/resources");
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BufferedImage[] bfs = fh.loadAllImages();
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Classifier cl = new Classifier(fh);
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cl.classifyImage(bfs[0], new File("DEBUG_VALUE"), 30);
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System.out.println(fh.loadBiggestDimension());
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}
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}
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@ -0,0 +1,238 @@
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package peery.picture;
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import java.awt.Color;
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import java.awt.Dimension;
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import java.awt.Graphics2D;
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import java.awt.image.BufferedImage;
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import java.awt.image.ColorModel;
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import java.io.File;
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import java.text.DecimalFormat;
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import java.util.HashMap;
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import peery.file.FileHandler;
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import peery.log.Log;
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import peery.log.LogLevel;
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public class ImageAnalyzer {
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public BufferedImage target;
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private FileHandler fh;
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private Dimension /*biggestInputSize,*/ targetSize;
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public int slotWidth, slotHeight, slotX, slotY;
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public BufferedImage canvas;
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public ImageAnalyzer(FileHandler fh){
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this.fh = fh;
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this.target = fh.loadImage(fh.TargetImageFile);
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}
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public void rasterizeTarget(int gridX, int gridY, float targetSizeMultiplier, double gridErrorThresh, int adaptionThreshhold, double adaptionStep){
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Log.log(LogLevel.Info, "Rasterizing target image ...");
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Log.log(LogLevel.Info, "Aiming for "+gridX+"*"+gridY+"="+(gridX*gridY)+" tiles ...");
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//this.biggestInputSize = this.fh.loadBiggestDimension();
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this.targetSize = new Dimension(this.target.getWidth(), this.target.getHeight());
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//TMP
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int count = 0;
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DecimalFormat df = new DecimalFormat("#");
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while(true){
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double realSlotWidth = ((targetSize.width*targetSizeMultiplier)/gridX);
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double realSlotHeight = ((targetSize.height*targetSizeMultiplier)/gridY);
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Log.log(LogLevel.Debug, "Perfect slot Size would be "+realSlotWidth+"x"+realSlotHeight);
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double widthLoss = Math.abs(realSlotWidth - Double.parseDouble(df.format(realSlotWidth)));
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double heightLoss = Math.abs(realSlotHeight - Double.parseDouble(df.format(realSlotHeight)));
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if(widthLoss > gridErrorThresh || heightLoss > gridErrorThresh){
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Log.log(LogLevel.Critical, "Grid misplacement error exceeded threshhold! Error is width:"+widthLoss+" height:"+heightLoss);
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if(widthLoss > gridErrorThresh){
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gridX *= adaptionStep;
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}
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if(heightLoss > gridErrorThresh){
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gridY *= adaptionStep;
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}
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Log.log(LogLevel.Info, "This is the "+(++count)+". adaption to ease the error.");
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Log.log(LogLevel.Info, "Aiming for "+gridX+"*"+gridY+"="+(gridX*gridY)+" tiles ...");
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if(count > adaptionThreshhold){
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Log.log(LogLevel.Critical, "Could not adapt to grid misplacement error! The result might be cut off or missing parts!");
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break;
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}
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continue;
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}else{
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break;
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}
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}
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slotWidth = (int) ((targetSize.width*targetSizeMultiplier)/gridX);
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slotHeight = (int) ((targetSize.height*targetSizeMultiplier)/gridY);
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//
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Log.log(LogLevel.Debug, "Target will be "+(int)(targetSize.width*targetSizeMultiplier)
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+"x"+(int)(targetSize.height*targetSizeMultiplier)+" big.");
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Log.log(LogLevel.Debug, "Slots are "+slotWidth+"x"+slotHeight+" big.");
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slotX = gridX;
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slotY = gridY;
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//ia.slotWidth*gridX+"x"+ia.slotHeight*gridY
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//canvas = new BufferedImage((int)(targetSize.getWidth()*targetSizeMultiplier), (int)(targetSize.getHeight()*targetSizeMultiplier), BufferedImage.TYPE_INT_ARGB);
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canvas = new BufferedImage(slotWidth*gridX, slotHeight*gridY, BufferedImage.TYPE_INT_ARGB);
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Graphics2D g2 = (Graphics2D) canvas.getGraphics();
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g2.setColor(Color.BLACK);
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g2.fillRect(0, 0, canvas.getWidth(), canvas.getHeight());
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}
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/**
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* Compares the given rgb value with the index and returns a HashMap of the closest hits.
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* Unlikely to yield more than 1 result without deviationPercentage
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* @param index
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* @param rgb
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* @param deviation How much the matches can be different from the perfect match, and still be taken.
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* @return
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*/
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public HashMap<String, Integer> matchClosestIndex(HashMap<String, Integer> index, int rgb, int deviation){
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Log.log(LogLevel.Debug, "Searching for closest match for rgb:"+rgb+" in the index with deviation of "+deviation+".");
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assert(deviation < 100 && 0 <= deviation);
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if(index == null){
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Log.log(LogLevel.Critical, "No Index was given for rgb matching. Loading it from file ...");
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index = this.fh.loadIndex();
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}
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HashMap<String, Double> metrics = new HashMap<String, Double>();
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double currBest = -1;
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for(String key: index.keySet()){
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double metric = getMetric(index.get(key), rgb);
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metrics.put(key, metric);
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if(currBest > metric || currBest == -1){
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currBest = metric;
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}
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}
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Log.log(LogLevel.Info, "Calculated all metrics for rgb:"+rgb+" !");
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HashMap<String, Integer> matches = new HashMap<String, Integer>();
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for(String key: metrics.keySet()){
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if(metrics.get(key) == currBest || metrics.get(key) < currBest+(currBest*(deviation/(double)100))){
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matches.put(key, index.get(key));
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}
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}
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Log.log(LogLevel.Debug, "Grabbed all good matches for rgb:"+rgb+" ! Got "+matches.size()+" ...");
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return matches;
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}
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/**
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* Calculates the euclidian metric of two given rgb values.
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* @param rgb1
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* @param rgb2
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* @return
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*/
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private double getMetric(int rgb1, int rgb2){
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ColorModel cm = ColorModel.getRGBdefault();
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double result = Math.sqrt(Math.pow((cm.getRed(rgb1)-cm.getRed(rgb2)), 2)+
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Math.pow(cm.getGreen(rgb1)-cm.getGreen(rgb2), 2)+
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Math.pow(cm.getBlue(rgb1)-cm.getBlue(rgb2), 2));
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return result;
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}
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/**
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* Places the given input in its specified slot (gridX, gridY) on the canvas.
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* Assumes and checks boundaries calculated by rasterizeTarget().
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* @param gridX
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* @param gridY
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* @param input
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* @param canvas
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* @return
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*/
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public void placeImage(int gridX, int gridY, BufferedImage input){
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assert(gridX < slotX && gridY < slotY);
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assert(input.getWidth() < slotWidth && input.getHeight() < slotHeight);
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Graphics2D g2 = (Graphics2D)canvas.getGraphics();
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g2.drawImage(input, gridX*slotWidth, gridY*slotHeight, slotWidth, slotHeight, null);
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g2.dispose();
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}
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/**
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* Plain calculation of average Color of an Image via RGB.
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* Takes average of RGB values of each pixel.
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* Does not account for alpha.
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* @param img Image to process
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* @param alphaThreshhold value under which pixels are discarded
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* @return RGB value of the average color
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*/
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public int classifyImage(BufferedImage img, File file, int alphaTreshhold){
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int width = img.getWidth();
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int height = img.getHeight();
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Log.log(LogLevel.Debug, "Starting classification of "+file.getName()+" with width:"+
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width+" and height:"+height+" ...");
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ColorModel cm = ColorModel.getRGBdefault();
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float red = 0, green = 0, blue = 0;
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int pixels = 0;
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for(int x = 0; x < img.getWidth(); x++){
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for(int y = 0; y < img.getHeight(); y++){
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int rgb = img.getRGB(x, y);
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red += cm.getRed(rgb);
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blue += cm.getBlue(rgb);
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green += cm.getGreen(rgb);
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pixels++;
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}
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}
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red = red/pixels;
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green = green/pixels;
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blue = blue/pixels;
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int rgb = new Color((int)red, (int)green, (int)blue).getRGB();
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Log.log(LogLevel.Info, "Classified "+file.getPath()+" with following rgb result: value:"+rgb+
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" red:"+red+", green:"+green+", blue:"+blue);
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return rgb;
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}
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public int classifySlot(int gridX, int gridY, BufferedImage target){
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int slotWidth = target.getWidth()/slotX,
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slotHeight = target.getHeight()/slotY;
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BufferedImage subImage = target.getSubimage(gridX*slotWidth, gridY*slotHeight, slotWidth, slotHeight);
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Log.log(LogLevel.Debug, "Slicing slot "+gridX+"x"+gridY+" out of the target for classification ...");
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ColorModel cm = ColorModel.getRGBdefault();
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float red = 0, green = 0, blue = 0;
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int pixels = 0;
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for(int x = 0; x < subImage.getWidth(); x++){
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for(int y = 0; y < subImage.getHeight(); y++){
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int rgb = subImage.getRGB(x, y);
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red += cm.getRed(rgb);
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green += cm.getGreen(rgb);
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blue += cm.getBlue(rgb);
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pixels++;
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}
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}
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red = red/pixels;
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green = green/pixels;
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blue = blue/pixels;
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int rgb = new Color((int)red, (int)green, (int)blue).getRGB();
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Log.log(LogLevel.Debug, "Classified slot "+gridX+"x"+gridY+" with following rgb result: value:"+rgb+
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" red:"+red+", green:"+green+", blue:"+blue);
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return rgb;
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}
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/*
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public static void main(String[] args){
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System.out.println("ZHE DEBUG");
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/*
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FileHandler fh = new FileHandler("/home/peery/Software_Projects/EclipseWorkspace/Picture Mosaic/resources");
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ImageAnalyzer ia = new ImageAnalyzer(fh);
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HashMap<String, Integer> index = fh.loadIndex();
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for(File f: fh.InputImagesFolder.listFiles()){
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BufferedImage img = fh.loadImage(f);
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if(img == null){
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continue;
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}
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int indexValue = ia.classifyImage(img, f, 30);
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fh.appendToIndex(index, f, indexValue);
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}
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index = fh.loadIndex();
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System.out.println(index.get("Peery-sketch.png"));
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System.out.println(index.get("rasd"));
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System.out.println(index.get("Larry the Tiger - Candy Shop Logo (Gift).png"));
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System.out.println(ia.matchClosestIndex(index, -10744103, 5));
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//BufferedImage img = ImageUtils.resizeImage(fh.loadImage(fh.InputImagesFolder.listFiles()[0]), new Dimension(500, 300), false);
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//fh.saveImage(img, new File("/home/peery/Software_Projects/EclipseWorkspace/Picture Mosaic/resources/resize-test.png"));
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}*/
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}
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@ -0,0 +1,41 @@
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package peery.picture;
|
||||
|
||||
import java.awt.Dimension;
|
||||
import java.awt.Graphics2D;
|
||||
import java.awt.Image;
|
||||
import java.awt.image.BufferedImage;
|
||||
|
||||
public class ImageUtils {
|
||||
|
||||
public static BufferedImage resizeImage(BufferedImage input, Dimension targetSize, boolean keepRatio){
|
||||
Image tmp;
|
||||
BufferedImage img;
|
||||
if(!keepRatio){
|
||||
tmp = input.getScaledInstance((int)targetSize.getWidth(), (int)targetSize.getHeight(), Image.SCALE_SMOOTH);
|
||||
img = new BufferedImage(tmp.getWidth(null), tmp.getHeight(null), BufferedImage.TYPE_INT_ARGB);
|
||||
|
||||
Graphics2D g2 = (Graphics2D) img.getGraphics();
|
||||
g2.drawImage(tmp, 0, 0, null);
|
||||
g2.dispose();
|
||||
return img;
|
||||
}
|
||||
if(targetSize.getWidth() > targetSize.getHeight()){
|
||||
tmp = input.getScaledInstance(-1, (int)targetSize.getHeight(), Image.SCALE_SMOOTH);
|
||||
img = new BufferedImage(tmp.getWidth(null), tmp.getHeight(null), BufferedImage.TYPE_INT_ARGB);
|
||||
|
||||
Graphics2D g2 = (Graphics2D) img.getGraphics();
|
||||
g2.drawImage(tmp, 0, 0, null);
|
||||
g2.dispose();
|
||||
return img;
|
||||
}else{
|
||||
tmp = input.getScaledInstance((int)targetSize.getWidth(), -1, Image.SCALE_SMOOTH);
|
||||
img = new BufferedImage(tmp.getWidth(null), tmp.getHeight(null), BufferedImage.TYPE_INT_ARGB);
|
||||
|
||||
Graphics2D g2 = (Graphics2D) img.getGraphics();
|
||||
g2.drawImage(tmp, 0, 0, null);
|
||||
g2.dispose();
|
||||
return img;
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue