Java FImage.process方法代码示例

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void analyseImage(FImage image) {
	final FImage sharpness = image.process(sharpProcessor);
	final FImage variance = image.process(varProcessor);

	double Qbokeh = 0;
	int validBlocks = 0;
	for (int y = 0; y < sharpness.height; y++) {
		for (int x = 0; x < sharpness.width; x++) {
			if (variance.pixels[y][x] >= varThreshold) {
				Qbokeh += sharpness.pixels[y][x] > 0.5 ? 1 : 0;
				validBlocks++;
			}
		}
	}
	Qbokeh /= (validBlocks);

	bokeh = (Qbokeh >= lowerBound && Qbokeh <= upperBound) ? 1 : 0;
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
/**
 * Test
 */
@Test
public void testCircle() {
	final int imgWidthHeight = 200;

	final FImage circleImage = new FImage(imgWidthHeight, imgWidthHeight);
	final Circle c = new Circle(imgWidthHeight / 2 + 3, imgWidthHeight / 2 + 1, imgWidthHeight / 4);
	circleImage.drawShapeFilled(c, 1f);

	final CannyEdgeDetector det = new CannyEdgeDetector();
	final FImage edgeImage = circleImage.process(det);

	final HoughCircles circ = new HoughCircles(5, imgWidthHeight, 5, 360);
	edgeImage.analyseWith(circ);

	final List<WeightedCircle> best = circ.getBest(1);
	final WeightedCircle b = best.get(0);

	assertTrue(b.equals(c));
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void analyseImage(FImage image) {
	final FImage limg = image.process(laplacian);
	final FImage aimg = image.process(average);

	final SummaryStatistics stats = new SummaryStatistics();
	for (int r = 0; r < limg.height; r++) {
		for (int c = 0; c < limg.width; c++) {
			if (mask != null && mask.pixels[r][c] == 0)
				continue;

			if (aimg.pixels[r][c] != 0) {
				stats.addValue(Math.abs(limg.pixels[r][c] / aimg.pixels[r][c]));
			}
		}
	}

	sharpnessVariation = stats.getStandardDeviation();
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void processImage(FImage image) {
	final FImage contrast = image.process(new LocalContrastFilter(FilterSupport.createBlockSupport(sizeX, sizeY)));
	final FImage avg = image.process(new AverageBoxFilter(sizeX, sizeY));

	final float[][] cpix = contrast.pixels;
	final float[][] mpix = avg.pixels;
	final float[][] ipix = image.pixels;

	for (int y = 0; y < image.height; y++) {
		for (int x = 0; x < image.width; x++) {
			if (cpix[y][x] < threshold)
				ipix[y][x] = (mpix[y][x] >= 128) ? 1 : 0;
			else
				ipix[y][x] = (ipix[y][x] >= mpix[y][x]) ? 1 : 0;
		}
	}
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void processImage(FImage image) {
	for (int i=niter; i!=0; i--) {
		FImage newImage = image.process(hitAndMiss, true);
		
		int count = 0;
		for (int y=0; y<newImage.height; y++) {
			for (int x=0; x<newImage.width; x++) {
				if (newImage.pixels[y][x] == 1) {
					count++;
					image.pixels[y][x] = 0;
				}
			}
		}
		
		if (count == 0)
			break;
	}
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void analyseImage(FImage image) {
	final FImage limg = image.process(laplacian);
	final FImage aimg = image.process(average);

	double sum = 0;
	for (int r = 0; r < limg.height; r++) {
		for (int c = 0; c < limg.width; c++) {
			if (mask != null && mask.pixels[r][c] == 0)
				continue;

			if (aimg.pixels[r][c] != 0) {
				sum += Math.abs(limg.pixels[r][c] / aimg.pixels[r][c]);
			}
		}
	}

	sharpness = sum / (limg.height * limg.width);
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
/**
 * @throws IOException
 */
@Test
public void testFixedResize() throws IOException {
	final FImage image = ImageUtilities.readF(ResizeProcessorTest.class
			.getResourceAsStream("/org/openimaj/image/data/sinaface.jpg"));
	long start, end;
	start = System.currentTimeMillis();
	final FixedResizeProcessor frp = new FixedResizeProcessor(image, 500, 250);
	for (int i = 0; i < 10000; i++) {
		image.process(frp);
	}
	end = System.currentTimeMillis();
	System.out.println("Time taken (fixed): " + (end - start));

	final ResizeProcessor rp = new ResizeProcessor(500, 250);
	start = System.currentTimeMillis();
	for (int i = 0; i < 10000; i++) {
		image.process(rp);
	}
	end = System.currentTimeMillis();
	System.out.println("Time taken (normal): " + (end - start));
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void beforeUpdate(MBFImage frame) {
	// Rectangle extractionArea = new
	// Rectangle(100,100,IMAGE_WIDTH-200,IMAGE_HEIGHT-200);

	if (this.mode == DebugMode.DEBUG_DISPLAY)
		return;
	final FImage grey = frame.extractROI(extractionArea).flatten();
	if (!this.backgroundLearner.ready()) {
		grey.process(this.backgroundLearner);
		frame.fill(RGBColour.BLACK);
		frame.drawImage(new MBFImage(grey, grey, grey), (int) extractionArea.x, (int) extractionArea.y);
		return;
	}
	grey.addInplace(this.backgroundLearner.getBackground());
	grey.threshold(0.07f);
	// grey.processInplace(new OtsuThreshold());
	// if(grey.sum() > BIGGEST_POINT_AREA * 2 ){
	// this.backgroundLearner.relearn();
	// return;
	// }

	// List<Circle> filtered = getFilteredCircles(grey);
	final List<Touch> filtered = getFilteredTouchesFast(grey);
	if (filtered.size() != 0)
		this.fireTouchEvent(filtered);
	frame.fill(RGBColour.BLACK);
	frame.drawImage(new MBFImage(grey, grey, grey), (int) extractionArea.x, (int) extractionArea.y);
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
/**
 * @param image
 * @param tc
 */
public PyramidSet(FImage image, TrackingContext tc) {
	int nrows = image.height, ncols = image.width;
	FImage floatimg2 = image.process(new FGaussianConvolve(tc.computeSmoothSigma()));
	this.imgPyr = new Pyramid(ncols, nrows, (int) tc.subsampling, tc.nPyramidLevels);
	this.imgPyr.computePyramid(floatimg2, tc.pyramid_sigma_fact);
	this.gradx = new Pyramid(ncols, nrows, (int) tc.subsampling, tc.nPyramidLevels);
	this.grady = new Pyramid(ncols, nrows, (int) tc.subsampling, tc.nPyramidLevels);
	for (int i = 0 ; i < tc.nPyramidLevels ; i++)
		tc.computeGradients(imgPyr.img[i], tc.grad_sigma, gradx.img[i], grady.img[i]);
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void processImage(FImage image) {
	final FImage tmp = image.process(new FGaussianConvolve(sigma));

	final float[][] tpix = tmp.pixels;
	final float[][] ipix = image.pixels;
	for (int y = 0; y < image.height; y++)
		for (int x = 0; x < image.width; x++)
			tpix[y][x] = ipix[y][x] < (tpix[y][x] - offset) ? 0f : 1f;

	image.internalAssign(tmp);
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
protected void detect(FImage image, SWTTextDetector detector) {
	final StrokeWidthTransform swt = new StrokeWidthTransform(true, detector.options.canny);
	swt.setMaxStrokeWidth(detector.options.maxStrokeWidth);
	FImage swtImage = image.process(swt);
	detector.analyseImage(image, swtImage);

	swt.setDirection(false);
	swtImage = image.process(swt);
	detector.analyseImage(image, swtImage);
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public void processImage(FImage image) {
	FImage newImage = image.process(hitAndMiss, true);
	
	for (int y=0; y<newImage.height; y++) {
		for (int x=0; x<newImage.width; x++) {
			if (newImage.pixels[y][x] == 1) {
				image.pixels[y][x] = 1;
			}
		}
	}
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
/**
 * Not a good test yet, just trys to run the processor, no attempt is made
 * to check the processor
 * 
 * @throws IOException
 */
@Test
public void test90Degree() throws IOException {
	final FImage img = ImageUtilities.readF(TestOrientedPolygonExtractionProcessor.class
			.getResourceAsStream("/org/openimaj/image/data/bird.png"));
	final Rectangle r = new Rectangle(320, 100, 60, 170);
	final Polygon p = r.asPolygon();
	final Polygon prot = p.clone();
	final Point2d center = prot.calculateCentroid();
	prot.rotate(center, Math.PI / 3);

	final OrientedPolygonExtractionProcessor opep = new OrientedPolygonExtractionProcessor(prot, 0.f);
	img.process(opep);
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
public static void main(String[] args) throws IOException {
	final FImage img = ImageUtilities
			.readF(new File(
					"/Users/jon/Library/Containers/com.apple.mail/Data/Library/Mail Downloads/BD5C21CA-CC93-4C38-A96D-A44E961C5544/in-2.jpg"));

	// blur the image, with more blur in the horizontal direction than
	// vertical
	final FImage i1 = img.process(new AverageBoxFilter(40, 10));

	// numerical issues from the way the box filter is implemented might
	// mean that there are values slightly bigger than 1, so clip the values
	// to a maximum of 1.
	i1.clip(0f, 1f);

	// threshold the image to make it purely black and white
	i1.processInplace(new OtsuThreshold());

	// invert the image before input to the ConnectedComponentLabeler
	i1.inverse();

	// Apply connected component labelling to find all the "blobs"
	final ConnectedComponentLabeler ccl = new ConnectedComponentLabeler(ConnectMode.CONNECT_8);
	final List<ConnectedComponent> ccs = ccl.findComponents(i1);

	// values for the computed bounds of the "graphic"
	int left = i1.width;
	int right = 0;
	int top = i1.height;
	int bottom = 0;

	// loop through the "blobs" and filter them
	for (final ConnectedComponent cc : ccs) {
		final Rectangle bb = cc.calculateRegularBoundingBox();

		// ignore components that are near the top edge
		if (bb.y < 0.1 * i1.height)
			continue;

		// ignore components that are near the right edge
		if (bb.x + bb.width > 0.9 * i1.width)
			continue;

		// filter the other components based on their width and the relative
		// area of the blob to its bounding box (should be ~1 for a text
		// block)
		if (bb.width < 0.4 * i1.width || bb.calculateArea() / cc.calculateArea() > 2) {
			if (bb.x < left)
				left = (int) bb.x;
			if (bb.x + bb.width > right)
				right = (int) (bb.x + bb.width);
			if (bb.y < top)
				top = (int) bb.y;
			if (bb.y + bb.height > bottom)
				bottom = (int) (bb.y + bb.height);
			i1.drawShape(bb, 0.5f);
		}
	}

	// construct the final bounds rectangle (might want to extend/pad it)
	final Rectangle bounds = new Rectangle(left, top, right - left, bottom - top);
	DisplayUtilities.display(img.extractROI(bounds));
}
 

import org.openimaj.image.FImage; //导入方法依赖的package包/类
@Override
public List<ConnectedComponent> segment(FImage image) {
	final FImage timg = image.process(thresholder);

	return algorithm.findComponents(timg, 0, mode);
}