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/image-recognition-processor/src/main/java/org/springframework/cloud/stream/app/processor/image/recognition/ImageRecognitionProcessorConfiguration.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.image.recognition;
+
+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.image.recognition.ImageRecognition;
+import org.springframework.cloud.fn.image.recognition.ImageRecognitionAugmenter;
+import org.springframework.cloud.fn.image.recognition.RecognitionResponse;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.integration.support.MessageBuilder;
+import org.springframework.messaging.Message;
+
+/**
+ * @author Christian Tzolov
+ */
+@Configuration
+@EnableConfigurationProperties(ImageRecognitionProcessorProperties.class)
+public class ImageRecognitionProcessorConfiguration {
+
+	private static final Log logger = LogFactory.getLog(ImageRecognitionProcessorConfiguration.class);
+
+	/**
+	 * Name of the Message header containing the JSON encoded recognition response.
+	 */
+	public static final String RECOGNIZED_OBJECTS_HEADER = "recognized_objects";
+
+	@Bean
+	public Function<Message<byte[]>, Message<byte[]>> imageRecognitionFunction(ImageRecognitionProcessorProperties properties) {
+
+		return input -> {
+			// You can use file:, http: or classpath: to provide the path to the input image.
+			byte[] inputImage = input.getPayload();
+
+			try (ImageRecognition imageRecognition = createImageRecognitionFunction(properties)) {
+
+				List<RecognitionResponse> recognizedObjects =
+						ImageRecognition.toRecognitionResponse(imageRecognition.recognizeTopK(inputImage));
+
+				// Draw the predicted labels on top of the input image.
+				byte[] augmentedImage = new ImageRecognitionAugmenter().apply(inputImage, recognizedObjects);
+
+				String jsonRecognizedObjects = new JsonMapperFunction().apply(recognizedObjects);
+
+				Message<byte[]> outMessage = MessageBuilder
+						.withPayload(augmentedImage)
+						.setHeader(RECOGNIZED_OBJECTS_HEADER, jsonRecognizedObjects)
+						.build();
+
+				if (properties.isDebugOutput()) {
+					try {
+						logger.info("recognized objects = " + jsonRecognizedObjects);
+						IOUtils.write(augmentedImage, new FileOutputStream(properties.getDebugOutputPath()));
+					}
+					catch (IOException e) {
+						logger.warn("Cloud not produce debug output", e);
+					}
+				}
+
+				return outMessage;
+			}
+		};
+	}
+
+	private static ImageRecognition createImageRecognitionFunction(ImageRecognitionProcessorProperties properties) {
+		switch (properties.getModelType()) {
+		case inception:
+			return ImageRecognition.inception(
+					properties.getModel(),
+					properties.getNormalizedImageSize(),
+					properties.getResponseSize(),
+					properties.isCacheModel());
+		case mobilenetv1:
+			return ImageRecognition.mobileNetV1(
+					properties.getModel(),
+					properties.getNormalizedImageSize(),
+					properties.getResponseSize(),
+					properties.isCacheModel());
+		case mobilenetv2:
+			return ImageRecognition.mobileNetV2(
+					properties.getModel(),
+					properties.getNormalizedImageSize(),
+					properties.getResponseSize(),
+					properties.isCacheModel());
+		default:
+			throw new RuntimeException("Not supported Model Type: " + properties.getModelType());
+
+		}
+	}
+}

applications/processor/image-recognition-processor/src/main/java/org/springframework/cloud/stream/app/processor/image/recognition/ImageRecognitionProcessorProperties.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.image.recognition;
+
+import org.springframework.boot.context.properties.ConfigurationProperties;
+import org.springframework.validation.annotation.Validated;
+
+/**
+ * @author Christian Tzolov
+ */
+@ConfigurationProperties("image.recognition")
+@Validated
+public class ImageRecognitionProcessorProperties {
+
+	enum ModelType {
+		inception,
+		mobilenetv1,
+		mobilenetv2
+	}
+
+	/**
+	 * Supports three different pre-trained tensorflow image recognition models: Inception, MobileNetV1 and MobileNetV2
+	 *
+	 * 1. Inception graph uses "input" as input and "output" as output.
+	 * 2. MobileNetV2 pre-trained models: https://github.com/tensorflow/models/tree/master/research/slim/nets/mobilenet#pretrained-models
+	 * 	 - normalized image size is always square (e.g. H=W)
+	 * 	 - graph uses "input" as input and "MobilenetV2/Predictions/Reshape_1" as output.
+	 *  3. MobileNetV1 pre-trained models: https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md#pre-trained-models
+	 * 	 - graph uses "input" as input and "MobilenetV1/Predictions/Reshape_1" as output.
+	 */
+	private ModelType modelType = ModelType.mobilenetv2;
+
+	/**
+	 * pre-trained tensorflow image recognition model. Note that the model must match the selected model type!
+	 */
+	private String model = "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz#mobilenet_v2_1.4_224_frozen.pb";
+
+	/**
+	 * cache the pre-trained tensorflow model.
+	 */
+	private boolean cacheModel = true;
+
+	/**
+	 * Normalized image size.
+	 */
+	private int normalizedImageSize = 224;
+
+	/**
+	 * number of recognized images.
+	 */
+	private int responseSize = 5;
+
+	private boolean debugOutput = false;
+
+	private String debugOutputPath = "image-recognition-result.png";
+
+	public ModelType getModelType() {
+		return modelType;
+	}
+
+	public void setModelType(ModelType modelType) {
+		this.modelType = modelType;
+	}
+
+	public String getModel() {
+		return model;
+	}
+
+	public void setModel(String model) {
+		this.model = model;
+	}
+
+	public boolean isCacheModel() {
+		return cacheModel;
+	}
+
+	public void setCacheModel(boolean cacheModel) {
+		this.cacheModel = cacheModel;
+	}
+
+	public int getNormalizedImageSize() {
+		return normalizedImageSize;
+	}
+
+	public void setNormalizedImageSize(int normalizedImageSize) {
+		this.normalizedImageSize = normalizedImageSize;
+	}
+
+	public int getResponseSize() {
+		return responseSize;
+	}
+
+	public void setResponseSize(int responseSize) {
+		this.responseSize = responseSize;
+	}
+
+	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;
+	}
+}

applications/processor/image-recognition-processor/src/main/resources/META-INF/dataflow-configuration-metadata-whitelist.properties

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+configuration-properties.classes=\
+  org.springframework.cloud.stream.app.processor.image.recognition.ImageRecognitionProcessorProperties

applications/processor/image-recognition-processor/src/main/resources/application.yml

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+image:
+  recognition:
+      model: https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz#mobilenet_v2_1.4_224_frozen.pb
+      modelType: mobilenetv2
+      responseSize: 3
+      normalizedImageSize: 224
+      cacheModel: true
+spring:
+    cloud:
+        function:
+            definition: imageRecognitionFunction

applications/processor/image-recognition-processor/src/test/java/org/springframework/cloud/stream/app/processor/image/recognition/ImageRecognitionProcessorTests.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.image.recognition;
+
+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 ImageRecognitionProcessorTests {
+
+	@Test
+	public void testImageRecognitionProcessorMobileNetV2() throws IOException {
+		try (ConfigurableApplicationContext context = new SpringApplicationBuilder(
+				TestChannelBinderConfiguration.getCompleteConfiguration(ImageRecognitionProcessorTestApplication.class))
+				.web(WebApplicationType.NONE)
+				.run("--spring.cloud.function.definition=imageRecognitionFunction",
+						"--image.recognition.modelType=mobilenetv2",
+						"--image.recognition.responseSize=3",
+						"--image.recognition.debugOutput=true",
+						"--image.recognition.debugOutputPath=./target/image-recognition-mobilenetv2.png")) {
+
+			InputDestination processorInput = context.getBean(InputDestination.class);
+			OutputDestination processorOutput = context.getBean(OutputDestination.class);
+
+			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/giant_panda_in_beijing_zoo_1.jpg");
+			processorInput.send(new GenericMessage<>(inputImage));
+			Message<byte[]> sourceMessage = processorOutput.receive(10000);
+			String jsonRecognizedObjects = (String) sourceMessage.getHeaders().get(ImageRecognitionProcessorConfiguration.RECOGNIZED_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}]");
+		}
+	}
+
+	@Test
+	public void testImageRecognitionProcessorMobileNetV1() throws IOException {
+		try (ConfigurableApplicationContext context = new SpringApplicationBuilder(
+				TestChannelBinderConfiguration.getCompleteConfiguration(ImageRecognitionProcessorTestApplication.class))
+				.web(WebApplicationType.NONE)
+				.run("--image.recognition.model=https://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz#mobilenet_v1_1.0_224_frozen.pb",
+						"--image.recognition.modelType=mobilenetv1",
+						"--image.recognition.responseSize=3",
+						"--image.recognition.debugOutput=true",
+						"--image.recognition.debugOutputPath=./target/image-recognition-mobilenetv1.png")) {
+
+			InputDestination processorInput = context.getBean(InputDestination.class);
+			OutputDestination processorOutput = context.getBean(OutputDestination.class);
+
+			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/giant_panda_in_beijing_zoo_1.jpg");
+			processorInput.send(new GenericMessage<>(inputImage));
+			Message<byte[]> sourceMessage = processorOutput.receive(10000);
+			String jsonRecognizedObjects = (String) sourceMessage.getHeaders().get(ImageRecognitionProcessorConfiguration.RECOGNIZED_OBJECTS_HEADER);
+			assertThat(jsonRecognizedObjects)
+					.isEqualTo("[{\"label\":\"giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca\",\"probability\":0.984053909778595},{\"label\":\"ram, tup\",\"probability\":0.0019619385711848736},{\"label\":\"Staffordshire bullterrier, Staffordshire bull terrier\",\"probability\":0.0018697341438382864}]");
+		}
+	}
+
+	@Test
+	public void testImageRecognitionProcessorInception() throws IOException {
+		try (ConfigurableApplicationContext context = new SpringApplicationBuilder(
+				TestChannelBinderConfiguration.getCompleteConfiguration(ImageRecognitionProcessorTestApplication.class))
+				.web(WebApplicationType.NONE)
+				.run("--image.recognition.model=https://storage.googleapis.com/scdf-tensorflow-models/image-recognition/tensorflow_inception_graph.pb",
+						"--image.recognition.modelType=inception",
+						"--image.recognition.responseSize=3",
+						"--image.recognition.debugOutput=true",
+						"--image.recognition.debugOutputPath=./target/image-recognition-inception.png")) {
+
+			InputDestination processorInput = context.getBean(InputDestination.class);
+			OutputDestination processorOutput = context.getBean(OutputDestination.class);
+
+			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/giant_panda_in_beijing_zoo_1.jpg");
+			processorInput.send(new GenericMessage<>(inputImage));
+			Message<byte[]> sourceMessage = processorOutput.receive(10000);
+			String jsonRecognizedObjects = (String) sourceMessage.getHeaders().get(ImageRecognitionProcessorConfiguration.RECOGNIZED_OBJECTS_HEADER);
+			assertThat(jsonRecognizedObjects)
+					.isEqualTo("[{\"label\":\"giant panda\",\"probability\":0.9946685433387756},{\"label\":\"Arctic fox\",\"probability\":0.0036631159018725157},{\"label\":\"ice bear\",\"probability\":3.378273395355791E-4}]");
+		}
+	}
+
+	@SpringBootApplication
+	@Import({ ImageRecognitionProcessorConfiguration.class })
+	public static class ImageRecognitionProcessorTestApplication {
+	}
+
+}