use of boofcv.struct.image.GrayF32 in project BoofCV by lessthanoptimal.
the class ShowImageDerivative method main.
public static void main(String[] args) {
ShowImageDerivative<GrayF32, GrayF32> app = new ShowImageDerivative<>(GrayF32.class, GrayF32.class);
// ShowImageDerivative<GrayU8, GrayS16> app
// = new ShowImageDerivative<GrayU8,GrayS16>(GrayU8.class,GrayS16.class);
List<PathLabel> 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")));
inputs.add(new PathLabel("xray", UtilIO.pathExample("xray01.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, "Image Derivative", true);
}
use of boofcv.struct.image.GrayF32 in project BoofCV by lessthanoptimal.
the class VisualizeAverageDownSample method main.
public static void main(String[] args) {
BufferedImage original = UtilImageIO.loadImage(UtilIO.pathExample("simple_objects.jpg"));
Planar<GrayF32> input = new Planar<>(GrayF32.class, original.getWidth(), original.getHeight(), 3);
ConvertBufferedImage.convertFromPlanar(original, input, true, GrayF32.class);
Planar<GrayF32> output = new Planar<>(GrayF32.class, original.getWidth() / 3, original.getHeight() / 3, 3);
Planar<GrayF32> output2 = new Planar<>(GrayF32.class, original.getWidth() / 3, original.getHeight() / 3, 3);
AverageDownSampleOps.down(input, output);
new FDistort(input, output2).scaleExt().apply();
BufferedImage outputFull = ConvertBufferedImage.convertTo_F32(output, null, true);
BufferedImage outputFull2 = ConvertBufferedImage.convertTo_F32(output2, null, true);
ShowImages.showWindow(original, "Original");
ShowImages.showWindow(outputFull, "3x small average");
ShowImages.showWindow(outputFull2, "3x small bilinear");
}
use of boofcv.struct.image.GrayF32 in project BoofCV by lessthanoptimal.
the class DenoiseAccuracyStudyApp method loadImage.
private void loadImage(String imagePath) {
BufferedImage in = UtilImageIO.loadImage(imagePath);
image = ConvertBufferedImage.convertFrom(in, (GrayF32) null);
}
use of boofcv.struct.image.GrayF32 in project BoofCV by lessthanoptimal.
the class VisualizeAssociationAlgorithmsApp method main.
public static void main(String[] args) {
Class imageType = GrayF32.class;
VisualizeAssociationAlgorithmsApp app = new VisualizeAssociationAlgorithmsApp(imageType);
List<PathLabel> inputs = new ArrayList<>();
inputs.add(new PathLabel("Cave", UtilIO.pathExample("stitch/cave_01.jpg"), UtilIO.pathExample("stitch/cave_02.jpg")));
inputs.add(new PathLabel("Kayak", UtilIO.pathExample("stitch/kayak_02.jpg"), UtilIO.pathExample("stitch/kayak_03.jpg")));
inputs.add(new PathLabel("Forest", UtilIO.pathExample("scale/rainforest_01.jpg"), UtilIO.pathExample("scale/rainforest_02.jpg")));
inputs.add(new PathLabel("Building", UtilIO.pathExample("stitch/apartment_building_01.jpg"), UtilIO.pathExample("stitch/apartment_building_02.jpg")));
inputs.add(new PathLabel("Trees Rotate", UtilIO.pathExample("stitch/trees_rotate_01.jpg"), UtilIO.pathExample("stitch/trees_rotate_03.jpg")));
app.setPreferredSize(new Dimension(1000, 500));
app.setSize(1000, 500);
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, "Associated Features", true);
}
use of boofcv.struct.image.GrayF32 in project BoofCV by lessthanoptimal.
the class VisualizeAssociationMatchesApp method main.
public static void main(String[] args) {
Class imageType = GrayF32.class;
Class derivType = GImageDerivativeOps.getDerivativeType(imageType);
VisualizeAssociationMatchesApp app = new VisualizeAssociationMatchesApp(imageType, derivType);
List<PathLabel> inputs = new ArrayList<>();
inputs.add(new PathLabel("Cave", UtilIO.pathExample("stitch/cave_01.jpg"), UtilIO.pathExample("stitch/cave_02.jpg")));
inputs.add(new PathLabel("Kayak", UtilIO.pathExample("stitch/kayak_02.jpg"), UtilIO.pathExample("stitch/kayak_03.jpg")));
inputs.add(new PathLabel("Forest", UtilIO.pathExample("scale/rainforest_01.jpg"), UtilIO.pathExample("scale/rainforest_02.jpg")));
inputs.add(new PathLabel("Building", UtilIO.pathExample("stitch/apartment_building_01.jpg"), UtilIO.pathExample("stitch/apartment_building_02.jpg")));
inputs.add(new PathLabel("Trees Rotate", UtilIO.pathExample("stitch/trees_rotate_01.jpg"), UtilIO.pathExample("stitch/trees_rotate_03.jpg")));
app.setPreferredSize(new Dimension(1000, 500));
app.setSize(1000, 500);
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, "Associated Features", true);
}
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