boofcv.examples.features.ExampleDenseOpticalFlow Maven / Gradle / Ivy

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/*
 * Copyright (c) 2011-2017, 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.examples.features;

import boofcv.abst.distort.FDistort;
import boofcv.abst.flow.DenseOpticalFlow;
import boofcv.factory.flow.FactoryDenseOpticalFlow;
import boofcv.gui.PanelGridPanel;
import boofcv.gui.feature.VisualizeOpticalFlow;
import boofcv.gui.image.AnimatePanel;
import boofcv.gui.image.ShowImages;
import boofcv.io.MediaManager;
import boofcv.io.UtilIO;
import boofcv.io.image.ConvertBufferedImage;
import boofcv.io.wrapper.DefaultMediaManager;
import boofcv.struct.flow.ImageFlow;
import boofcv.struct.image.GrayF32;

import java.awt.image.BufferedImage;

/**
 * Demonstration of how to compute the dense optical flow between two images.  Dense optical flow of an image
 * describes how each pixel moves from one image to the next.  The results is visualized in a color image.  The
 * color indicates the direction of motion and the intensity the magnitude.
 *
 * @author Peter Abeles
 */
public class ExampleDenseOpticalFlow {

	public static void main(String[] args) {
		MediaManager media = DefaultMediaManager.INSTANCE;

//		String fileName0 = UtilIO.pathExample("denseflow/dogdance07.png");
//		String fileName1 = UtilIO.pathExample("denseflow/dogdance08.png");

		String fileName0 = UtilIO.pathExample("denseflow/Urban2_07.png");
		String fileName1 = UtilIO.pathExample("denseflow/Urban2_08.png");

//		String fileName0 = UtilIO.pathExample("denseflow/Grove2_07.png");
//		String fileName1 = UtilIO.pathExample("denseflow/Grove2_09.png");

		DenseOpticalFlow denseFlow =
//				FactoryDenseOpticalFlow.flowKlt(null, 6, GrayF32.class, null);
//				FactoryDenseOpticalFlow.region(null,GrayF32.class);
//				FactoryDenseOpticalFlow.hornSchunck(20, 1000, GrayF32.class);
//				FactoryDenseOpticalFlow.hornSchunckPyramid(null,GrayF32.class);
				FactoryDenseOpticalFlow.broxWarping(null, GrayF32.class);

		BufferedImage buff0 = media.openImage(fileName0);
		BufferedImage buff1 = media.openImage(fileName1);

		GrayF32 full = new GrayF32(buff0.getWidth(),buff0.getHeight());

		// Dense optical flow is very computationally expensive.  Just process the image at 1/2 resolution
		GrayF32 previous = new GrayF32(full.width/2,full.height/2);
		GrayF32 current = previous.createSameShape();
		ImageFlow flow = new ImageFlow(previous.width,previous.height);

		ConvertBufferedImage.convertFrom(buff0,full);
		new FDistort(full, previous).scaleExt().apply();
		ConvertBufferedImage.convertFrom(buff1, full);
		new FDistort(full, current).scaleExt().apply();

		// compute dense motion
		denseFlow.process(previous, current, flow);

		// Visualize the results
		PanelGridPanel gui = new PanelGridPanel(1,2);

		BufferedImage converted0 = new BufferedImage(current.width,current.height,BufferedImage.TYPE_INT_RGB);
		BufferedImage converted1 = new BufferedImage(current.width,current.height,BufferedImage.TYPE_INT_RGB);
		BufferedImage visualized = new BufferedImage(current.width,current.height,BufferedImage.TYPE_INT_RGB);

		ConvertBufferedImage.convertTo(previous, converted0, true);
		ConvertBufferedImage.convertTo(current, converted1, true);
		VisualizeOpticalFlow.colorized(flow, 10, visualized);

		AnimatePanel animate = new AnimatePanel(150,converted0,converted1);
		gui.add(animate);
		gui.add(visualized);
		animate.start();

		ShowImages.showWindow(gui,"Dense Optical Flow",true);
	}
}