Tensorflow functions and applications

* initial step
 * Tensorflow models functional model redesign

      -- Based on https://tzolov.github.io/mind-model-services
      -- Resolves #5

 * Add object detection processor README
 * Add image recognition processor README
 * Initial Tensorflow commonn README
 * Initial Tensorflow commonn README
 * Tensorflow common diagram
 * Tensorflow docs code
 * Tensorflow docs code snippets improve
 * Tensorflow docs code snippets improve
 * Tensorflow docs code snippets improve
 * Tensorflow docs code snippets improve
 * Add semantic segmentation function. add object detecteion function readme
 * oo images
 * Furether oo readme improvments
 * Final obj detection readme fixes
 * Add image recognition readme
 * Add image recognition readme 2
 * Semantic segmentation readme
 * Segmentation readme
 * Semantic segmentation readme 3
 * Fix image recognition and object detcion app starter dependecies

 * Add metadata for Tensorflow apps

applications/processor/object-detection-processor/src/main/java/org/springframework/cloud/stream/app/processor/object/detection/ObjectDetectionProcessorConfiguration.java

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+/*
+ * Copyright 2020-2020 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
+ *
+ *      https://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.processor.object.detection;
+
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.util.List;
+import java.util.function.Function;
+
+import org.apache.commons.io.IOUtils;
+import org.apache.commons.logging.Log;
+import org.apache.commons.logging.LogFactory;
+
+import org.springframework.boot.context.properties.EnableConfigurationProperties;
+import org.springframework.cloud.fn.common.tensorflow.deprecated.JsonMapperFunction;
+import org.springframework.cloud.fn.object.detection.ObjectDetectionImageAugmenter;
+import org.springframework.cloud.fn.object.detection.ObjectDetectionService;
+import org.springframework.cloud.fn.object.detection.domain.ObjectDetection;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.integration.support.MessageBuilder;
+import org.springframework.messaging.Message;
+import org.springframework.util.CollectionUtils;
+
+/**
+ * @author Christian Tzolov
+ */
+@Configuration
+@EnableConfigurationProperties(ObjectDetectionProcessorProperties.class)
+public class ObjectDetectionProcessorConfiguration {
+
+	private static final Log logger = LogFactory.getLog(ObjectDetectionProcessorConfiguration.class);
+
+	/**
+	 * Name of the Message header containing the JSON encoded detected objects.
+	 */
+	public static final String DETECTED_OBJECTS_HEADER = "detected_objects";
+
+	@Bean
+	public ObjectDetectionService objectDetectionService(ObjectDetectionProcessorProperties properties) {
+		return new ObjectDetectionService(properties.getModel(),
+				properties.getLabels(), properties.getConfidence(), properties.isWithMasks(),
+				properties.isCacheModel());
+	}
+
+	@Bean
+	public Function<Message<byte[]>, Message<byte[]>> objectDetection(
+			ObjectDetectionService objectDetectionService,
+			ObjectDetectionProcessorProperties properties) {
+
+		return input -> {
+			// You can use file:, http: or classpath: to provide the path to the input image.
+			byte[] inputImage = input.getPayload();
+
+			List<ObjectDetection> detectedObjects = objectDetectionService.detect(inputImage);
+
+			if (!CollectionUtils.isEmpty(detectedObjects) && properties.getResponseSize() < detectedObjects.size()) {
+				detectedObjects = detectedObjects.subList(0, properties.getResponseSize());
+			}
+
+			// Draw the predicted labels on top of the input image.
+			byte[] augmentedImage = new ObjectDetectionImageAugmenter().apply(inputImage, detectedObjects);
+
+			String jsonDetectedObjects = new JsonMapperFunction().apply(detectedObjects);
+
+			Message<byte[]> outMessage = MessageBuilder
+					.withPayload(augmentedImage)
+					.setHeader(DETECTED_OBJECTS_HEADER, jsonDetectedObjects)
+					.build();
+
+			if (properties.isDebugOutput()) {
+				try {
+					logger.info("detected objects = " + jsonDetectedObjects);
+					IOUtils.write(augmentedImage, new FileOutputStream(properties.getDebugOutputPath()));
+				}
+				catch (IOException e) {
+					logger.warn("Cloud not produce debug output", e);
+				}
+			}
+
+			return outMessage;
+
+		};
+	}
+
+}

applications/processor/object-detection-processor/src/main/java/org/springframework/cloud/stream/app/processor/object/detection/ObjectDetectionProcessorProperties.java

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+/*
+ * Copyright 2020-2020 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
+ *
+ *      https://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.processor.object.detection;
+
+import org.springframework.boot.context.properties.ConfigurationProperties;
+import org.springframework.validation.annotation.Validated;
+
+/**
+ * @author Christian Tzolov
+ */
+@ConfigurationProperties("object.detection")
+@Validated
+public class ObjectDetectionProcessorProperties {
+
+	/**
+	 * pre-trained tensorflow object detection model.
+	 */
+	private String model = "https://download.tensorflow.org/models/object_detection/ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz#frozen_inference_graph.pb";
+
+	/**
+	 * Labels URI.
+	 */
+	private String labels = "https://storage.googleapis.com/scdf-tensorflow-models/object-detection/mscoco_label_map.pbtxt";
+
+	private float confidence = 0.4f;
+
+	private boolean withMasks;
+
+	private boolean cacheModel = true;
+
+	private boolean debugOutput = false;
+
+	private String debugOutputPath = "object-detection-result.png";
+
+	private int responseSize = Integer.MAX_VALUE;
+
+	public boolean isDebugOutput() {
+		return debugOutput;
+	}
+
+	public void setDebugOutput(boolean debugOutput) {
+		this.debugOutput = debugOutput;
+	}
+
+	public String getDebugOutputPath() {
+		return debugOutputPath;
+	}
+
+	public void setDebugOutputPath(String debugOutputPath) {
+		this.debugOutputPath = debugOutputPath;
+	}
+
+	public String getModel() {
+		return model;
+	}
+
+	public void setModel(String model) {
+		this.model = model;
+	}
+
+	public String getLabels() {
+		return labels;
+	}
+
+	public void setLabels(String labels) {
+		this.labels = labels;
+	}
+
+	public float getConfidence() {
+		return confidence;
+	}
+
+	public void setConfidence(float confidence) {
+		this.confidence = confidence;
+	}
+
+	public boolean isWithMasks() {
+		return withMasks;
+	}
+
+	public void setWithMasks(boolean withMasks) {
+		this.withMasks = withMasks;
+	}
+
+	public boolean isCacheModel() {
+		return cacheModel;
+	}
+
+	public void setCacheModel(boolean cacheModel) {
+		this.cacheModel = cacheModel;
+	}
+
+	public int getResponseSize() {
+		return responseSize;
+	}
+
+	public void setResponseSize(int responseSize) {
+		this.responseSize = responseSize;
+	}
+}

applications/processor/object-detection-processor/src/main/resources/META-INF/dataflow-configuration-metadata-whitelist.properties

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+configuration-properties.classes=\
+  org.springframework.cloud.stream.app.processor.object.detection.ObjectDetectionProcessorProperties

applications/processor/object-detection-processor/src/test/java/org/springframework/cloud/stream/app/processor/object/detection/ObjectDetectionProcessorTests.java

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+/*
+ * Copyright 2020-2020 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
+ *
+ *      https://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.processor.object.detection;
+
+import java.io.IOException;
+
+import org.junit.jupiter.api.Test;
+
+import org.springframework.boot.WebApplicationType;
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+import org.springframework.boot.builder.SpringApplicationBuilder;
+import org.springframework.cloud.fn.common.tensorflow.deprecated.GraphicsUtils;
+import org.springframework.cloud.stream.binder.test.InputDestination;
+import org.springframework.cloud.stream.binder.test.OutputDestination;
+import org.springframework.cloud.stream.binder.test.TestChannelBinderConfiguration;
+import org.springframework.context.ConfigurableApplicationContext;
+import org.springframework.context.annotation.Import;
+import org.springframework.messaging.Message;
+import org.springframework.messaging.support.GenericMessage;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+/**
+ * @author Christian Tzolov
+ */
+public class ObjectDetectionProcessorTests {
+
+	@Test
+	public void testObjectDetectionProcessor() throws IOException {
+		try (ConfigurableApplicationContext context = new SpringApplicationBuilder(
+				TestChannelBinderConfiguration.getCompleteConfiguration(ObjectDetectionProcessorTestApplication.class))
+				.web(WebApplicationType.NONE)
+				.run("--spring.cloud.function.definition=objectDetection",
+						"--object.detection.model=https://download.tensorflow.org/models/object_detection/ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz#frozen_inference_graph.pb",
+						"--object.detection.labels=https://storage.googleapis.com/scdf-tensorflow-models/object-detection/mscoco_label_map.pbtxt",
+						"--object.detection.responseSize=10",
+						"--object.detection..debugOutput=true",
+						"--object.detection..debugOutputPath=./target/object-detection-1.png")) {
+
+			InputDestination processorInput = context.getBean(InputDestination.class);
+			OutputDestination processorOutput = context.getBean(OutputDestination.class);
+
+			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/pivotal.jpeg");
+			processorInput.send(new GenericMessage<>(inputImage));
+			Message<byte[]> sourceMessage = processorOutput.receive(10000);
+			String jsonRecognizedObjects = (String) sourceMessage.getHeaders().get(ObjectDetectionProcessorConfiguration.DETECTED_OBJECTS_HEADER);
+			assertThat(jsonRecognizedObjects).isNotEmpty();
+			//assertThat(jsonRecognizedObjects)
+			//		.isEqualTo("[{\"label\":\"giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca\",\"probability\":0.962329626083374}," +
+			//				"{\"label\":\"badger\",\"probability\":0.006058811210095882}," +
+			//				"{\"label\":\"ram, tup\",\"probability\":0.0010668420000001788}]");
+		}
+	}
+
+	//@Test
+	public void testObjectDetectionProcessoriNaturalistSpecies() throws IOException {
+		try (ConfigurableApplicationContext context = new SpringApplicationBuilder(
+				TestChannelBinderConfiguration.getCompleteConfiguration(ObjectDetectionProcessorTestApplication.class))
+				.web(WebApplicationType.NONE)
+				.run(
+						//"--spring.cloud.function.definition=objectDetection",
+						"--object.detection.model=http://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_fgvc_2018_07_19.tar.gz#frozen_inference_graph.pb",
+						"--object.detection.labels=https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/data/fgvc_2854_classes_label_map.pbtxt",
+						"--object.detection..debugOutput=true",
+						"--object.detection..debugOutputPath=./target/object-detection-2.png")) {
+
+			InputDestination processorInput = context.getBean(InputDestination.class);
+			OutputDestination processorOutput = context.getBean(OutputDestination.class);
+
+			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/animals2.jpg");
+			processorInput.send(new GenericMessage<>(inputImage));
+			Message<byte[]> sourceMessage = processorOutput.receive(10000);
+			String jsonRecognizedObjects = (String) sourceMessage.getHeaders().get(ObjectDetectionProcessorConfiguration.DETECTED_OBJECTS_HEADER);
+			//assertThat(jsonRecognizedObjects)
+			//		.isEqualTo("[{\"label\":\"giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca\",\"probability\":0.962329626083374}," +
+			//				"{\"label\":\"badger\",\"probability\":0.006058811210095882}," +
+			//				"{\"label\":\"ram, tup\",\"probability\":0.0010668420000001788}]");
+		}
+	}
+
+	@SpringBootApplication
+	@Import({ ObjectDetectionProcessorConfiguration.class })
+	public static class ObjectDetectionProcessorTestApplication {
+	}
+
+}