Java tutorial
/* * Copyright 2018 the original author or authors. * * 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 org.springframework.cloud.stream.app.object.detection.processor; import java.awt.image.BufferedImage; import java.awt.image.DataBufferByte; import java.io.ByteArrayInputStream; import java.io.IOException; import java.nio.ByteBuffer; import java.util.HashMap; import java.util.Map; import javax.imageio.ImageIO; import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; import org.tensorflow.Tensor; import org.tensorflow.types.UInt8; import org.springframework.cloud.stream.app.tensorflow.processor.TensorflowInputConverter; /** * Converts byte array image into a input Tensor for the Object Detection API. The computed image tensors uses the * 'image_tensor' model placeholder. * * @author Christian Tzolov */ public class ObjectDetectionTensorflowInputConverter implements TensorflowInputConverter { private static final Log logger = LogFactory.getLog(ObjectDetectionTensorflowInputConverter.class); private static final long BATCH_SIZE = 1; private static final long CHANNELS = 3; public static final String IMAGE_TENSOR_FEED_NAME = "image_tensor"; @Override public Map<String, Object> convert(Object input, Map<String, Object> processorContext) { if (input instanceof byte[]) { try { Tensor inputImageTensor = makeImageTensor((byte[]) input); Map<String, Object> inputMap = new HashMap<>(); inputMap.put(IMAGE_TENSOR_FEED_NAME, inputImageTensor); return inputMap; } catch (IOException e) { throw new IllegalArgumentException("Incorrect image format", e); } } throw new IllegalArgumentException(String.format("Expected byte[] payload type, found: %s", input)); } private static Tensor<UInt8> makeImageTensor(byte[] imageBytes) throws IOException { ByteArrayInputStream is = new ByteArrayInputStream(imageBytes); BufferedImage img = ImageIO.read(is); if (img.getType() != BufferedImage.TYPE_3BYTE_BGR) { throw new IllegalArgumentException( String.format("Expected 3-byte BGR encoding in BufferedImage, found %d", img.getType())); } byte[] data = ((DataBufferByte) img.getData().getDataBuffer()).getData(); // ImageIO.read produces BGR-encoded images, while the model expects RGB. bgrToRgb(data); //Expand dimensions since the model expects images to have shape: [1, None, None, 3] long[] shape = new long[] { BATCH_SIZE, img.getHeight(), img.getWidth(), CHANNELS }; return Tensor.create(UInt8.class, shape, ByteBuffer.wrap(data)); } private static void bgrToRgb(byte[] data) { for (int i = 0; i < data.length; i += 3) { byte tmp = data[i]; data[i] = data[i + 2]; data[i + 2] = tmp; } } }