/*
 * Copyright (c) 2011-2016, Peter Abeles. All Rights Reserved.
 *
 * This file is part of BoofCV (http://boofcv.org).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package boofcv.demonstrations.feature.detect.intensity;

import boofcv.abst.feature.detect.intensity.*;
import boofcv.abst.filter.derivative.AnyImageDerivative;
import boofcv.alg.feature.detect.intensity.HessianBlobIntensity;
import boofcv.alg.filter.derivative.GradientThree;
import boofcv.alg.misc.ImageStatistics;
import boofcv.core.image.GeneralizedImageOps;
import boofcv.factory.feature.detect.intensity.FactoryIntensityPointAlg;
import boofcv.factory.filter.blur.FactoryBlurFilter;
import boofcv.gui.SelectAlgorithmAndInputPanel;
import boofcv.gui.image.ImagePanel;
import boofcv.gui.image.ShowImages;
import boofcv.gui.image.VisualizeImageData;
import boofcv.io.PathLabel;
import boofcv.io.UtilIO;
import boofcv.io.image.ConvertBufferedImage;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.GrayS16;
import boofcv.struct.image.GrayU8;
import boofcv.struct.image.ImageGray;

import javax.swing.*;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.util.ArrayList;

/**
 * Displays the intensity of detected features inside an image
 *
 * @author Peter Abeles
 */
public class IntensityPointFeatureApp
		extends SelectAlgorithmAndInputPanel
{
	// displays intensity image
	ImagePanel gui;

	// original input image
	BufferedImage input;
	// intensity image is rendered here
	BufferedImage temp;
	// converted input image
	T workImage;
	// type of image the input image is
	Class imageType;
	// computes image derivative
	AnyImageDerivative deriv;
	// if it has processed an image or not
	boolean processImage = false;

	public IntensityPointFeatureApp( Class imageType , Class derivType ) {
		super(1);
		this.imageType = imageType;

		boolean isInteger = !GeneralizedImageOps.isFloatingPoint(imageType);
		deriv = new AnyImageDerivative(GradientThree.getKernelX(isInteger),imageType,derivType);

		addAlgorithm(0, "Laplacian", new WrapperHessianBlobIntensity(HessianBlobIntensity.Type.TRACE,derivType));
		addAlgorithm(0, "Hessian Det", new WrapperHessianBlobIntensity(HessianBlobIntensity.Type.DETERMINANT,derivType));
		addAlgorithm(0, "Harris",new WrapperGradientCornerIntensity(FactoryIntensityPointAlg.harris(2, 0.4f, false, derivType)));
		addAlgorithm(0, "Harris Weighted",new WrapperGradientCornerIntensity(FactoryIntensityPointAlg.harris(2, 0.4f, true, derivType)));
		addAlgorithm(0, "Shi Tomasi",new WrapperGradientCornerIntensity( FactoryIntensityPointAlg.shiTomasi(2, false, derivType)));
		addAlgorithm(0, "Shi Tomasi Weighted",new WrapperGradientCornerIntensity( FactoryIntensityPointAlg.shiTomasi(2, true, derivType)));
		addAlgorithm(0, "FAST",new WrapperFastCornerIntensity(FactoryIntensityPointAlg.fast(5, 11, imageType)));
		addAlgorithm(0, "KitRos",new WrapperKitRosCornerIntensity(derivType));
		addAlgorithm(0, "Median",new WrapperMedianCornerIntensity(FactoryBlurFilter.median(imageType,2),imageType));

		gui = new ImagePanel();
		setMainGUI(gui);
	}

	@Override
	public void setActiveAlgorithm(int indexFamily, String name, Object cookie) {
		if( workImage == null )
			return;

		GeneralFeatureIntensity intensity = (GeneralFeatureIntensity)cookie;

		deriv.setInput(workImage);

		D derivX = deriv.getDerivative(true);
		D derivY = deriv.getDerivative(false);
		D derivXX = deriv.getDerivative(true,true);
		D derivYY = deriv.getDerivative(false,false);
		D derivXY = deriv.getDerivative(true,false);

		intensity.process(workImage,derivX,derivY,derivXX,derivYY,derivXY);

		GrayF32 featureImg = intensity.getIntensity();
		VisualizeImageData.colorizeSign(featureImg,temp, ImageStatistics.maxAbs(featureImg));
		gui.setBufferedImage(temp);
		gui.repaint();
		gui.requestFocusInWindow();
	}

	public void process( final BufferedImage input ) {
		setInputImage(input);
		this.input = input;
		workImage = ConvertBufferedImage.convertFromSingle(input, null, imageType);
		temp = new BufferedImage(workImage.width,workImage.height,BufferedImage.TYPE_INT_BGR);
		SwingUtilities.invokeLater(new Runnable() {
			public void run() {
				setPreferredSize(new Dimension(input.getWidth(),input.getHeight()));
				processImage = true;
			}});
		doRefreshAll();
	}

	@Override
	public void loadConfigurationFile(String fileName) {}

	@Override
	public void refreshAll(Object[] cookies) {
		setActiveAlgorithm(0,null,cookies[0]);
	}

	@Override
	public void changeInput(String name, int index) {
		BufferedImage image = media.openImage(inputRefs.get(index).getPath());

		if( image != null ) {
			process(image);
		}
	}

	@Override
	public boolean getHasProcessedImage() {
		return processImage;
	}

	public static void main( String args[] ) {
//		IntensityPointFeatureApp app =
//				new IntensityPointFeatureApp(GrayF32.class,GrayF32.class);

		IntensityPointFeatureApp app =
				new IntensityPointFeatureApp(GrayU8.class,GrayS16.class);

		java.util.List inputs = new ArrayList();

		inputs.add(new PathLabel("shapes", UtilIO.pathExample("shapes/shapes01.png")));
		inputs.add(new PathLabel("sunflowers",UtilIO.pathExample("sunflowers.jpg")));
		inputs.add(new PathLabel("beach",UtilIO.pathExample("scale/beach02.jpg")));

		app.setInputList(inputs);

		// wait for it to process one image so that the size isn't all screwed up
		while( !app.getHasProcessedImage() ) {
			Thread.yield();
		}

		ShowImages.showWindow(app,"Feature Intensity",true);
	}
}