Mercurial > hg > orthanc-java
view Samples/MammographyDeepLearning/src/main/java/ImageProcessing.java @ 33:10406d66d1c6
cppcheck
author | Sebastien Jodogne <s.jodogne@gmail.com> |
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date | Fri, 14 Jun 2024 11:14:02 +0200 |
parents | 43923934e934 |
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/** * SPDX-FileCopyrightText: 2023-2024 Sebastien Jodogne, UCLouvain, Belgium * SPDX-License-Identifier: GPL-3.0-or-later **/ /** * Java plugin for Orthanc * Copyright (C) 2023-2024 Sebastien Jodogne, UCLouvain, Belgium * * This program is free software: you can redistribute it and/or * modify it under the terms of the GNU General Public License as * published by the Free Software Foundation, either version 3 of the * License, or (at your option) any later version. * * This program is distributed in the hope that it will be useful, but * WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU * General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program. If not, see <http://www.gnu.org/licenses/>. **/ import ai.djl.ndarray.NDArray; import ai.djl.ndarray.NDManager; import ai.djl.ndarray.types.DataType; import ai.djl.ndarray.types.Shape; import java.awt.*; import java.awt.image.BufferedImage; import java.awt.image.DataBuffer; public class ImageProcessing { static BufferedImage resizeImage(BufferedImage originalImage, int targetWidth, int targetHeight) { BufferedImage resizedImage = new BufferedImage(targetWidth, targetHeight, originalImage.getType()); Graphics2D graphics2D = resizedImage.createGraphics(); graphics2D.setRenderingHint(RenderingHints.KEY_INTERPOLATION, RenderingHints.VALUE_INTERPOLATION_BILINEAR); graphics2D.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON); graphics2D.drawImage(originalImage, 0, 0, targetWidth, targetHeight, null); graphics2D.dispose(); return resizedImage; } static NDArray imageToTensor(NDManager manager, BufferedImage image) { if (image.getType() != image.TYPE_USHORT_GRAY /* 16 bpp */ && image.getType() != image.TYPE_BYTE_GRAY /* 8 bpp */) { throw new IllegalArgumentException(); } float pixels[] = new float[image.getHeight() * image.getWidth()]; DataBuffer db = image.getData().getDataBuffer(); int pos = 0; for (int y = 0; y < image.getHeight(); y++) { for (int x = 0; x < image.getWidth(); x++, pos++) { pixels[pos] = db.getElemFloat(pos); } } return manager.create(pixels, new Shape(1, image.getHeight(), image.getWidth())); } static NDArray standardize(NDArray image) { if (image.getDataType() != DataType.FLOAT32 || image.getShape().dimension() != 3 || (image.getShape().get(0) != 1 && image.getShape().get(0) != 3)) { throw new IllegalArgumentException(); } // Standardize the image to zero mean and 1 standard deviation NDArray doubleImage = image.toType(DataType.FLOAT64, false); NDArray squared = doubleImage.mul(doubleImage); double asum = doubleImage.sum().getDouble(); double asumOfSquares = squared.sum().getDouble(); double n = doubleImage.getShape().size(); double amean = asum / n; double astd = Math.sqrt((asumOfSquares - asum * asum / n) / n); return image.add(-amean).div(astd); } }