GH-7: Add checkstyle and javaformat plugins

Fixes: #7

* Run `./gradlew format`
* Updates from PR review suggestions

function/spring-aggregator-function/src/main/java/org/springframework/cloud/fn/aggregator/AggregatorFunctionConfiguration.java

@@ -63,17 +63,11 @@ public class AggregatorFunctionConfiguration {
 	private BeanFactory beanFactory;
 
 	@Bean
-	public Function<Flux<Message<?>>, Flux<Message<?>>> aggregatorFunction(
-		FluxMessageChannel inputChannel,
-		FluxMessageChannel outputChannel
-	) {
+	public Function<Flux<Message<?>>, Flux<Message<?>>> aggregatorFunction(FluxMessageChannel inputChannel,
+			FluxMessageChannel outputChannel) {
 		return input -> Flux.from(outputChannel)
-			.doOnRequest((request) ->
-					inputChannel.subscribeTo(
-							input.map((inputMessage) ->
-									MessageBuilder.fromMessage(inputMessage)
-											.removeHeader("kafka_consumer")
-											.build())));
+			.doOnRequest((request) -> inputChannel.subscribeTo(input.map((
+					inputMessage) -> MessageBuilder.fromMessage(inputMessage).removeHeader("kafka_consumer").build())));
 	}
 
 	@Bean
@@ -88,13 +82,10 @@ public class AggregatorFunctionConfiguration {
 
 	@Bean
 	@ServiceActivator(inputChannel = "inputChannel")
-	public AggregatorFactoryBean aggregator(
-		@Nullable CorrelationStrategy correlationStrategy,
-		@Nullable ReleaseStrategy releaseStrategy,
-		@Nullable MessageGroupProcessor messageGroupProcessor,
-		@Nullable MessageGroupStore messageStore,
-		@Qualifier("outputChannel") MessageChannel outputChannel,
-		@Nullable ComponentCustomizer<AggregatorFactoryBean> aggregatorCustomizer) {
+	public AggregatorFactoryBean aggregator(@Nullable CorrelationStrategy correlationStrategy,
+			@Nullable ReleaseStrategy releaseStrategy, @Nullable MessageGroupProcessor messageGroupProcessor,
+			@Nullable MessageGroupStore messageStore, @Qualifier("outputChannel") MessageChannel outputChannel,
+			@Nullable ComponentCustomizer<AggregatorFactoryBean> aggregatorCustomizer) {
 
 		AggregatorFactoryBean aggregator = new AggregatorFactoryBean();
 		aggregator.setExpireGroupsUponCompletion(true);
@@ -149,14 +140,10 @@ public class AggregatorFunctionConfiguration {
 		return new ExpressionEvaluatingMessageGroupProcessor(this.properties.getAggregation().getExpressionString());
 	}
 
-
 	@Configuration
 	@ConditionalOnMissingBean(MessageGroupStore.class)
-	@Import({
-		MessageStoreConfiguration.Mongo.class,
-		MessageStoreConfiguration.Redis.class,
-		MessageStoreConfiguration.Jdbc.class
-	})
+	@Import({ MessageStoreConfiguration.Mongo.class, MessageStoreConfiguration.Redis.class,
+			MessageStoreConfiguration.Jdbc.class })
 	protected static class MessageStoreAutoConfiguration {
 
 	}

function/spring-aggregator-function/src/main/java/org/springframework/cloud/fn/aggregator/AggregatorFunctionProperties.java

@@ -55,7 +55,8 @@ public class AggregatorFunctionProperties {
 	private String messageStoreType = MessageStoreType.SIMPLE;
 
 	/**
-	 * Persistence message store entity: table prefix in RDBMS, collection name in MongoDb, etc.
+	 * Persistence message store entity: table prefix in RDBMS, collection name in
+	 * MongoDb, etc.
 	 */
 	private String messageStoreEntity;
 

function/spring-aggregator-function/src/main/java/org/springframework/cloud/fn/aggregator/ExcludeStoresAutoConfigurationEnvironmentPostProcessor.java

@@ -32,8 +32,9 @@ import org.springframework.core.env.MutablePropertySources;
 import org.springframework.core.env.PropertiesPropertySource;
 
 /**
- * An {@link EnvironmentPostProcessor} to add {@code spring.autoconfigure.exclude} property
- * since we can't use {@code application.properties} from the library perspective.
+ * An {@link EnvironmentPostProcessor} to add {@code spring.autoconfigure.exclude}
+ * property since we can't use {@code application.properties} from the library
+ * perspective.
  *
  * @author Artem Bilan
  * @author Corneil du Plessis
@@ -45,16 +46,14 @@ public class ExcludeStoresAutoConfigurationEnvironmentPostProcessor implements E
 		MutablePropertySources propertySources = environment.getPropertySources();
 		Properties properties = new Properties();
 
-		properties.setProperty("spring.autoconfigure.exclude",
-				DataSourceAutoConfiguration.class.getName() + ", " +
-						DataSourceTransactionManagerAutoConfiguration.class.getName() + ", " +
-						MongoAutoConfiguration.class.getName() + ", " +
-						MongoDataAutoConfiguration.class.getName() + ", " +
-						MongoRepositoriesAutoConfiguration.class.getName() + ", " +
-						RedisAutoConfiguration.class.getName() + ", " +
-						RedisRepositoriesAutoConfiguration.class.getName());
+		properties.setProperty("spring.autoconfigure.exclude", DataSourceAutoConfiguration.class.getName() + ", "
+				+ DataSourceTransactionManagerAutoConfiguration.class.getName() + ", "
+				+ MongoAutoConfiguration.class.getName() + ", " + MongoDataAutoConfiguration.class.getName() + ", "
+				+ MongoRepositoriesAutoConfiguration.class.getName() + ", " + RedisAutoConfiguration.class.getName()
+				+ ", " + RedisRepositoriesAutoConfiguration.class.getName());
 
-		propertySources.addLast(new PropertiesPropertySource("aggregator.exclude.stores.auto-configuration", properties));
+		propertySources
+			.addLast(new PropertiesPropertySource("aggregator.exclude.stores.auto-configuration", properties));
 	}
 
 }

function/spring-aggregator-function/src/main/java/org/springframework/cloud/fn/aggregator/MessageStoreConfiguration.java

@@ -40,11 +40,10 @@ import org.springframework.integration.store.MessageGroupStore;
 import org.springframework.jdbc.core.JdbcTemplate;
 import org.springframework.util.StringUtils;
 
-
 /**
- * A helper class containing configuration classes for particular technologies
- * to expose an appropriate {@link org.springframework.integration.store.MessageStore} bean
- * via matched configuration properties.
+ * A helper class containing configuration classes for particular technologies to expose
+ * an appropriate {@link org.springframework.integration.store.MessageStore} bean via
+ * matched configuration properties.
  *
  * @author Artem Bilan
  * @author Corneil du Plessis
@@ -52,11 +51,9 @@ import org.springframework.util.StringUtils;
 class MessageStoreConfiguration {
 
 	@ConditionalOnClass(ConfigurableMongoDbMessageStore.class)
-	@ConditionalOnProperty(prefix = AggregatorFunctionProperties.PREFIX,
-			name = "message-store-type",
+	@ConditionalOnProperty(prefix = AggregatorFunctionProperties.PREFIX, name = "message-store-type",
 			havingValue = AggregatorFunctionProperties.MessageStoreType.MONGODB)
-	@Import({ MongoAutoConfiguration.class,
-			MongoDataAutoConfiguration.class })
+	@Import({ MongoAutoConfiguration.class, MongoDataAutoConfiguration.class })
 	static class Mongo {
 
 		@Bean
@@ -72,15 +69,14 @@ class MessageStoreConfiguration {
 		@Bean
 		@Primary
 		public MongoCustomConversions mongoDbCustomConversions() {
-			return new MongoCustomConversions(Arrays.asList(
-					new MessageToBinaryConverter(), new BinaryToMessageConverter()));
+			return new MongoCustomConversions(
+					Arrays.asList(new MessageToBinaryConverter(), new BinaryToMessageConverter()));
 		}
 
 	}
 
 	@ConditionalOnClass(RedisMessageStore.class)
-	@ConditionalOnProperty(prefix = AggregatorFunctionProperties.PREFIX,
-			name = "message-store-type",
+	@ConditionalOnProperty(prefix = AggregatorFunctionProperties.PREFIX, name = "message-store-type",
 			havingValue = AggregatorFunctionProperties.MessageStoreType.REDIS)
 	@Import(RedisAutoConfiguration.class)
 	static class Redis {
@@ -93,12 +89,9 @@ class MessageStoreConfiguration {
 	}
 
 	@ConditionalOnClass(JdbcMessageStore.class)
-	@ConditionalOnProperty(prefix = AggregatorFunctionProperties.PREFIX,
-			name = "message-store-type",
+	@ConditionalOnProperty(prefix = AggregatorFunctionProperties.PREFIX, name = "message-store-type",
 			havingValue = AggregatorFunctionProperties.MessageStoreType.JDBC)
-	@Import({
-			DataSourceAutoConfiguration.class,
-			DataSourceTransactionManagerAutoConfiguration.class })
+	@Import({ DataSourceAutoConfiguration.class, DataSourceTransactionManagerAutoConfiguration.class })
 	static class Jdbc {
 
 		@Bean

function/spring-aggregator-function/src/test/java/org/springframework/cloud/fn/aggregator/AbstractAggregatorFunctionTests.java

@@ -48,9 +48,11 @@ public abstract class AbstractAggregatorFunctionTests {
 
 	@SpringBootApplication
 	public static class AggregatorFunctionTestApplication {
+
 		public static void main(String[] args) {
 			SpringApplication.run(AggregatorFunctionTestApplication.class, args);
 		}
+
 	}
 
 }

function/spring-aggregator-function/src/test/java/org/springframework/cloud/fn/aggregator/CustomPropsAndMongoMessageStoreAggregatorTests.java

@@ -38,13 +38,10 @@ import static org.assertj.core.api.Assertions.assertThat;
 /**
  * @author Artem Bilan
  */
-@TestPropertySource(properties = {
-		"aggregator.correlation=T(Thread).currentThread().id",
+@TestPropertySource(properties = { "aggregator.correlation=T(Thread).currentThread().id",
 		"aggregator.release=!messages.?[payload == 'bar'].empty",
-		"aggregator.aggregation=#this.?[payload == 'foo'].![payload]",
-		"aggregator.messageStoreType=mongodb",
-		"aggregator.message-store-entity=aggregatorTest"
-})
+		"aggregator.aggregation=#this.?[payload == 'foo'].![payload]", "aggregator.messageStoreType=mongodb",
+		"aggregator.message-store-entity=aggregatorTest" })
 @AutoConfigureDataMongo
 public class CustomPropsAndMongoMessageStoreAggregatorTests extends AbstractAggregatorFunctionTests
 		implements MongoDbTestContainerSupport {
@@ -57,22 +54,19 @@ public class CustomPropsAndMongoMessageStoreAggregatorTests extends AbstractAggr
 
 	@Test
 	public void test() {
-		Flux<Message<?>> input =
-				Flux.just("foo", "bar")
-						.map(GenericMessage::new);
+		Flux<Message<?>> input = Flux.just("foo", "bar").map(GenericMessage::new);
 
 		Flux<Message<?>> output = this.aggregatorFunction.apply(input);
 
 		output.as(StepVerifier::create)
-				.assertNext((message) ->
-						assertThat(message)
-								.extracting(Message::getPayload)
-								.isInstanceOf(List.class)
-								.asList()
-								.hasSize(1)
-								.element(0).isEqualTo("foo"))
-				.thenCancel()
-				.verify(Duration.ofSeconds(10));
+			.assertNext((message) -> assertThat(message).extracting(Message::getPayload)
+				.isInstanceOf(List.class)
+				.asList()
+				.hasSize(1)
+				.element(0)
+				.isEqualTo("foo"))
+			.thenCancel()
+			.verify(Duration.ofSeconds(10));
 
 		assertThat(this.messageGroupStore).isInstanceOf(ConfigurableMongoDbMessageStore.class);
 		assertThat(TestUtils.getPropertyValue(this.messageGroupStore, "collectionName")).isEqualTo("aggregatorTest");

function/spring-aggregator-function/src/test/java/org/springframework/cloud/fn/aggregator/DefaultAggregatorTests.java

@@ -40,12 +40,13 @@ import static org.assertj.core.api.Assertions.assertThat;
 @Disabled("Fails on CI sporadically")
 @TestPropertySource(properties = "aggregator.message-store-type=simple")
 public class DefaultAggregatorTests extends AbstractAggregatorFunctionTests {
+
 	private static final Logger logger = LoggerFactory.getLogger(DefaultAggregatorTests.class);
 
 	@Test
 	public void test() {
-		Flux<Message<?>> input =
-			Flux.just(MessageBuilder.withPayload("2")
+		Flux<Message<?>> input = Flux.just(
+				MessageBuilder.withPayload("2")
 					.setHeader(IntegrationMessageHeaderAccessor.CORRELATION_ID, "my_correlation")
 					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_NUMBER, 2)
 					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_SIZE, 2)
@@ -57,20 +58,13 @@ public class DefaultAggregatorTests extends AbstractAggregatorFunctionTests {
 					.build());
 
 		Flux<Message<?>> output = this.aggregatorFunction.apply(input.log("DefaultAggregatorTests:input"));
-		output.log("DefaultAggregatorTests:output")
-			.as(StepVerifier::create)
-			.assertNext((message) -> {
-				assertThat(message)
-					.extracting(Message::getPayload)
-					.asList()
-					.hasSize(2)
-					.contains("1", "2");
-			})
-			.thenCancel()
-			.verify(Duration.ofSeconds(30));
+		output.log("DefaultAggregatorTests:output").as(StepVerifier::create).assertNext((message) -> {
+			assertThat(message).extracting(Message::getPayload).asList().hasSize(2).contains("1", "2");
+		}).thenCancel().verify(Duration.ofSeconds(30));
 
 		assertThat(this.messageGroupStore).isNull();
 		assertThat(this.aggregatingMessageHandler.getMessageStore()).isInstanceOf(SimpleMessageStore.class);
 
 	}
+
 }

function/spring-aggregator-function/src/test/java/org/springframework/cloud/fn/aggregator/JdbcMessageStoreAggregatorTests.java

@@ -40,30 +40,28 @@ public class JdbcMessageStoreAggregatorTests extends AbstractAggregatorFunctionT
 
 	@Test
 	public void test() {
-		Flux<Message<?>> input =
-				Flux.just(MessageBuilder.withPayload("2")
-								.setHeader(IntegrationMessageHeaderAccessor.CORRELATION_ID, "my_correlation")
-								.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_NUMBER, 2)
-								.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_SIZE, 2)
-								.build(),
-						MessageBuilder.withPayload("1")
-								.setHeader(IntegrationMessageHeaderAccessor.CORRELATION_ID, "my_correlation")
-								.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_NUMBER, 1)
-								.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_SIZE, 2)
-								.build());
+		Flux<Message<?>> input = Flux.just(
+				MessageBuilder.withPayload("2")
+					.setHeader(IntegrationMessageHeaderAccessor.CORRELATION_ID, "my_correlation")
+					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_NUMBER, 2)
+					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_SIZE, 2)
+					.build(),
+				MessageBuilder.withPayload("1")
+					.setHeader(IntegrationMessageHeaderAccessor.CORRELATION_ID, "my_correlation")
+					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_NUMBER, 1)
+					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_SIZE, 2)
+					.build());
 
 		Flux<Message<?>> output = this.aggregatorFunction.apply(input);
 
 		output.as(StepVerifier::create)
-				.assertNext((message) ->
-						assertThat(message)
-								.extracting(Message::getPayload)
-								.isInstanceOf(List.class)
-								.asList()
-								.hasSize(2)
-								.contains("1", "2"))
-				.thenCancel()
-				.verify(Duration.ofSeconds(10));
+			.assertNext((message) -> assertThat(message).extracting(Message::getPayload)
+				.isInstanceOf(List.class)
+				.asList()
+				.hasSize(2)
+				.contains("1", "2"))
+			.thenCancel()
+			.verify(Duration.ofSeconds(10));
 
 		assertThat(this.messageGroupStore).isInstanceOf(JdbcMessageStore.class);
 

function/spring-aggregator-function/src/test/java/org/springframework/cloud/fn/aggregator/RedisMessageStoreAggregatorTests.java

@@ -41,7 +41,8 @@ import static org.assertj.core.api.Assertions.assertThat;
  * @author Artem Bilan
  */
 @TestPropertySource(properties = "aggregator.message-store-type=redis")
-public class RedisMessageStoreAggregatorTests extends AbstractAggregatorFunctionTests implements RedisTestContainerSupport {
+public class RedisMessageStoreAggregatorTests extends AbstractAggregatorFunctionTests
+		implements RedisTestContainerSupport {
 
 	@DynamicPropertySource
 	static void redisProperties(DynamicPropertyRegistry registry) {
@@ -52,8 +53,8 @@ public class RedisMessageStoreAggregatorTests extends AbstractAggregatorFunction
 	public void test() {
 		InputStream fakeNonSerializableKafkaConsumer = new ByteArrayInputStream(new byte[0]);
 
-		Flux<Message<?>> input =
-			Flux.just(MessageBuilder.withPayload("2")
+		Flux<Message<?>> input = Flux.just(
+				MessageBuilder.withPayload("2")
 					.setHeader(IntegrationMessageHeaderAccessor.CORRELATION_ID, "my_correlation")
 					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_NUMBER, 2)
 					.setHeader(IntegrationMessageHeaderAccessor.SEQUENCE_SIZE, 2)
@@ -68,13 +69,11 @@ public class RedisMessageStoreAggregatorTests extends AbstractAggregatorFunction
 		Flux<Message<?>> output = this.aggregatorFunction.apply(input);
 
 		output.as(StepVerifier::create)
-			.assertNext((message) ->
-				assertThat(message)
-					.extracting(Message::getPayload)
-					.isInstanceOf(List.class)
-					.asList()
-					.hasSize(2)
-					.contains("1", "2"))
+			.assertNext((message) -> assertThat(message).extracting(Message::getPayload)
+				.isInstanceOf(List.class)
+				.asList()
+				.hasSize(2)
+				.contains("1", "2"))
 			.thenCancel()
 			.verify(Duration.ofSeconds(10));
 

function/spring-filter-function/src/main/java/org/springframework/cloud/fn/filter/FilterFunctionConfiguration.java

@@ -34,7 +34,7 @@ public class FilterFunctionConfiguration {
 
 	@Bean
 	public Function<Message<?>, Message<?>> filterFunction(
-		ExpressionEvaluatingTransformer filterExpressionEvaluatingTransformer) {
+			ExpressionEvaluatingTransformer filterExpressionEvaluatingTransformer) {
 
 		return message -> {
 			if ((Boolean) filterExpressionEvaluatingTransformer.transform(message).getPayload()) {
@@ -48,7 +48,7 @@ public class FilterFunctionConfiguration {
 
 	@Bean
 	public ExpressionEvaluatingTransformer filterExpressionEvaluatingTransformer(
-		FilterFunctionProperties filterFunctionProperties) {
+			FilterFunctionProperties filterFunctionProperties) {
 
 		return new ExpressionEvaluatingTransformer(filterFunctionProperties.getExpression());
 	}

function/spring-filter-function/src/test/java/org/springframework/cloud/fn/filter/FilterFunctionApplicationTests.java

@@ -21,11 +21,8 @@ import java.util.function.Function;
 import java.util.stream.Collectors;
 import java.util.stream.Stream;
 
-
 import org.junit.jupiter.api.Test;
 
-
-
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.beans.factory.annotation.Qualifier;
 import org.springframework.boot.autoconfigure.SpringBootApplication;
@@ -50,10 +47,9 @@ public class FilterFunctionApplicationTests {
 
 	@Test
 	public void testFilter() {
-		Stream<Message<?>> messages = List.of("hello", "hello world")
-			.stream()
-			.map(GenericMessage::new);
-		List<Message<?>> result = messages.filter(message -> this.filter.apply(message) != null).collect(Collectors.toList());
+		Stream<Message<?>> messages = List.of("hello", "hello world").stream().map(GenericMessage::new);
+		List<Message<?>> result = messages.filter(message -> this.filter.apply(message) != null)
+			.collect(Collectors.toList());
 		assertThat(result.size()).isEqualTo(1);
 		assertThat(result.get(0).getPayload()).isNotNull();
 		assertThat(result.get(0).getPayload()).isEqualTo("hello world");

function/spring-header-enricher-function/src/main/java/org/springframework/cloud/fn/header/enricher/HeaderEnricherFunctionConfiguration.java

@@ -58,8 +58,8 @@ public class HeaderEnricherFunctionConfiguration {
 		Enumeration<?> enumeration = props.propertyNames();
 		while (enumeration.hasMoreElements()) {
 			String propertyName = (String) enumeration.nextElement();
-			ExpressionEvaluatingHeaderValueMessageProcessor<?> headerValueMessageProcessor =
-					new ExpressionEvaluatingHeaderValueMessageProcessor<>(props.getProperty(propertyName), null);
+			ExpressionEvaluatingHeaderValueMessageProcessor<?> headerValueMessageProcessor = new ExpressionEvaluatingHeaderValueMessageProcessor<>(
+					props.getProperty(propertyName), null);
 			headerValueMessageProcessor.setBeanFactory(beanFactory);
 			headersToAdd.put(propertyName, headerValueMessageProcessor);
 		}

function/spring-header-enricher-function/src/main/java/org/springframework/cloud/fn/header/enricher/HeaderEnricherFunctionProperties.java

@@ -35,8 +35,8 @@ import org.springframework.validation.annotation.Validated;
 public class HeaderEnricherFunctionProperties {
 
 	/**
-	 * \n separated properties representing headers in which values are SpEL expressions, e.g
-	 * foo='bar' \n baz=payload.baz.
+	 * \n separated properties representing headers in which values are SpEL expressions,
+	 * e.g foo='bar' \n baz=payload.baz.
 	 */
 	private Properties headers;
 

function/spring-header-enricher-function/src/test/java/org/springframework/cloud/fn/header/enricher/HeaderEnricherFunctionApplicationTests.java

@@ -33,12 +33,10 @@ import static org.hamcrest.MatcherAssert.assertThat;
 import static org.hamcrest.Matchers.equalTo;
 
 /**
- *
  * @author Gary Russell
  * @author Soby Chacko
  */
-@SpringBootTest(properties = {
-		"header.enricher.headers=foo='bar' \\n baz='fiz' \\n buz=payload \\n jaz=@value",
+@SpringBootTest(properties = { "header.enricher.headers=foo='bar' \\n baz='fiz' \\n buz=payload \\n jaz=@value",
 		"header.enricher.overwrite = true" })
 @DirtiesContext
 public class HeaderEnricherFunctionApplicationTests {
@@ -48,8 +46,7 @@ public class HeaderEnricherFunctionApplicationTests {
 
 	@Test
 	public void testDefault() {
-		final Message<?> message = MessageBuilder.withPayload("hello")
-				.setHeader("baz", "qux").build();
+		final Message<?> message = MessageBuilder.withPayload("hello").setHeader("baz", "qux").build();
 		final Message<?> enriched = headerEnricherFunction.apply(message);
 
 		assertThat(enriched, HeaderMatcher.hasHeader("foo", equalTo("bar")));

function/spring-header-filter-function/src/main/java/org/springframework/cloud/fn/header/filter/HeaderFilterFunctionConfiguration.java

@@ -37,7 +37,9 @@ import org.springframework.util.StringUtils;
 @EnableConfigurationProperties(HeaderFilterFunctionProperties.class)
 @ConditionalOnExpression("'${header.filter.remove}'!='' or '${header.filter.delete-all}' != ''")
 public class HeaderFilterFunctionConfiguration {
+
 	private final HeaderFilterFunctionProperties properties;
+
 	public HeaderFilterFunctionConfiguration(HeaderFilterFunctionProperties properties) {
 		this.properties = properties;
 	}
@@ -46,7 +48,7 @@ public class HeaderFilterFunctionConfiguration {
 	public Function<Message<?>, Message<?>> headerFilterFunction() {
 		if (properties.isDeleteAll()) {
 			return (message) -> {
-				var  accessor = new IntegrationMessageHeaderAccessor(message);
+				var accessor = new IntegrationMessageHeaderAccessor(message);
 				var headers = new HashSet<>(message.getHeaders().keySet());
 				headers.removeIf(accessor::isReadOnly);
 				HeaderFilter filter = new HeaderFilter(headers.toArray(new String[0]));

function/spring-header-filter-function/src/main/java/org/springframework/cloud/fn/header/filter/HeaderFilterFunctionProperties.java

@@ -20,18 +20,20 @@ import org.springframework.boot.context.properties.ConfigurationProperties;
 
 /**
  * Properties for configuration of header-filter-function.
+ *
  * @author Corneil du Plessis
  */
 @ConfigurationProperties("header.filter")
 public class HeaderFilterFunctionProperties {
+
 	/**
 	 * Indicates the need to remove all headers.
 	 */
 	private boolean deleteAll = false;
 
 	/**
-	 * Remove all headers named. A comma, space separated list of header names.
-	 * The names may contain patterns.
+	 * Remove all headers named. A comma, space separated list of header names. The names
+	 * may contain patterns.
 	 */
 	private String remove;
 
@@ -50,4 +52,5 @@ public class HeaderFilterFunctionProperties {
 	public void setRemove(String remove) {
 		this.remove = remove;
 	}
+
 }

function/spring-header-filter-function/src/test/java/org/springframework/cloud/fn/header/filter/HeaderFilterFunctionApplicationDeleteAllTests.java

@@ -30,13 +30,10 @@ import org.springframework.messaging.support.MessageBuilder;
 
 import static org.assertj.core.api.Assertions.assertThat;
 
-@SpringBootTest(classes = {
-	HeaderFilterFunctionApplicationDeleteAllTests.HeaderFilterFunctionTestApplication.class,
-	HeaderFilterFunctionConfiguration.class
-},
-	properties = {"header.filter.delete-all=true"}
-)
+@SpringBootTest(classes = { HeaderFilterFunctionApplicationDeleteAllTests.HeaderFilterFunctionTestApplication.class,
+		HeaderFilterFunctionConfiguration.class }, properties = { "header.filter.delete-all=true" })
 public class HeaderFilterFunctionApplicationDeleteAllTests {
+
 	@Autowired
 	protected Function<Message<?>, Message<?>> headerFilter;
 
@@ -54,9 +51,11 @@ public class HeaderFilterFunctionApplicationDeleteAllTests {
 
 	@SpringBootApplication
 	static class HeaderFilterFunctionTestApplication {
+
 		public static void main(String[] args) throws Exception {
 			SpringApplication.main(args);
 		}
+
 	}
 
 }

function/spring-header-filter-function/src/test/java/org/springframework/cloud/fn/header/filter/HeaderFilterFunctionApplicationTests.java

@@ -29,13 +29,10 @@ import org.springframework.messaging.support.MessageBuilder;
 
 import static org.assertj.core.api.Assertions.assertThat;
 
-@SpringBootTest(classes = {
-	HeaderFilterFunctionApplicationTests.HeaderFilterFunctionTestApplication.class,
-	HeaderFilterFunctionConfiguration.class
-},
-	properties = {"header.filter.remove=foo,bar,pf-*"}
-)
+@SpringBootTest(classes = { HeaderFilterFunctionApplicationTests.HeaderFilterFunctionTestApplication.class,
+		HeaderFilterFunctionConfiguration.class }, properties = { "header.filter.remove=foo,bar,pf-*" })
 public class HeaderFilterFunctionApplicationTests {
+
 	@Autowired
 	protected Function<Message<?>, Message<?>> headerFilter;
 
@@ -93,9 +90,11 @@ public class HeaderFilterFunctionApplicationTests {
 
 	@SpringBootApplication
 	static class HeaderFilterFunctionTestApplication {
+
 		public static void main(String[] main) {
 
 		}
+
 	}
 
 }

function/spring-header-filter-function/src/test/java/org/springframework/cloud/fn/header/filter/HeaderUtils.java

@@ -25,6 +25,7 @@ import org.springframework.integration.IntegrationMessageHeaderAccessor;
 import org.springframework.messaging.Message;
 
 final public class HeaderUtils {
+
 	private HeaderUtils() {
 	}
 
@@ -35,4 +36,5 @@ final public class HeaderUtils {
 		headers.removeIf(accessor::isReadOnly);
 		return headers;
 	}
+
 }

function/spring-http-request-function/src/main/java/org/springframework/cloud/fn/http/request/HttpRequestFunctionConfiguration.java

@@ -33,7 +33,6 @@ import org.springframework.web.reactive.function.client.WebClient;
 import org.springframework.web.util.DefaultUriBuilderFactory;
 import org.springframework.web.util.UriBuilderFactory;
 
-
 /**
  * Configuration for a {@link Function} that makes HTTP requests to a resource and for
  * each request, returns a {@link ResponseEntity}.
@@ -47,7 +46,8 @@ import org.springframework.web.util.UriBuilderFactory;
 public class HttpRequestFunctionConfiguration {
 
 	@Bean
-	public HttpRequestFunction httpRequestFunction(WebClient.Builder webClientBuilder, HttpRequestFunctionProperties properties) {
+	public HttpRequestFunction httpRequestFunction(WebClient.Builder webClientBuilder,
+			HttpRequestFunctionProperties properties) {
 		return new HttpRequestFunction(webClientBuilder.build(), properties);
 	}
 
@@ -76,8 +76,7 @@ public class HttpRequestFunctionConfiguration {
 
 		@Override
 		public Object apply(Message<?> message) {
-			return this.webClient
-				.method(resolveHttpMethod(message))
+			return this.webClient.method(resolveHttpMethod(message))
 				.uri(uriBuilderFactory.uriString(resolveUrl(message)).build())
 				.bodyValue(resolveBody(message))
 				.headers(httpHeaders -> httpHeaders.addAll(resolveHeaders(message)))
@@ -98,7 +97,7 @@ public class HttpRequestFunctionConfiguration {
 
 		private Object resolveBody(Message<?> message) {
 			return properties.getBodyExpression() != null ? properties.getBodyExpression().getValue(message)
-				: message.getPayload();
+					: message.getPayload();
 		}
 
 		private HttpHeaders resolveHeaders(Message<?> message) {
@@ -107,8 +106,7 @@ public class HttpRequestFunctionConfiguration {
 				Map<?, ?> headersMap = properties.getHeadersExpression().getValue(message, Map.class);
 				for (Map.Entry<?, ?> header : headersMap.entrySet()) {
 					if (header.getKey() != null && header.getValue() != null) {
-						headers.add(header.getKey().toString(),
-							header.getValue().toString());
+						headers.add(header.getKey().toString(), header.getValue().toString());
 					}
 				}
 			}
@@ -123,5 +121,7 @@ public class HttpRequestFunctionConfiguration {
 		public HttpMethod convert(String source) {
 			return HttpMethod.valueOf(source);
 		}
+
 	}
+
 }

function/spring-http-request-function/src/test/java/org/springframework/cloud/fn/http/request/HttpRequestFunctionTestApplicationTests.java

@@ -43,25 +43,21 @@ import static org.assertj.core.api.Assertions.assertThat;
 import static org.assertj.core.api.Assertions.fail;
 
 public class HttpRequestFunctionTestApplicationTests {
+
 	private MockWebServer server = new MockWebServer();
 
 	private ApplicationContextRunner runner;
 
 	@BeforeEach
 	void setup() {
-		this.runner = new ApplicationContextRunner()
-				.withUserConfiguration(HttpRequestFunctionTestApplication.class)
-				.withPropertyValues(
-						"http.request.reply-expression=#root",
-						"http.request.url-expression='" + url() + "'");
+		this.runner = new ApplicationContextRunner().withUserConfiguration(HttpRequestFunctionTestApplication.class)
+			.withPropertyValues("http.request.reply-expression=#root", "http.request.url-expression='" + url() + "'");
 	}
 
 	@Test
 	void shouldReturnString() {
 
-		server.enqueue(new MockResponse()
-				.setResponseCode(HttpStatus.OK.value())
-				.setBody("hello"));
+		server.enqueue(new MockResponse().setResponseCode(HttpStatus.OK.value()).setBody("hello"));
 
 		runner.withPropertyValues("http.request.http-method-expression='POST'").run(context -> {
 			HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
@@ -78,26 +74,27 @@ public class HttpRequestFunctionTestApplicationTests {
 		server.setDispatcher(new Dispatcher() {
 			@Override
 			public MockResponse dispatch(RecordedRequest recordedRequest) {
-				return new MockResponse().setHeader(HttpHeaders.CONTENT_TYPE,
-						recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
+				return new MockResponse()
+					.setHeader(HttpHeaders.CONTENT_TYPE, recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
 					.setBody(recordedRequest.getBody())
 					.setResponseCode(HttpStatus.CREATED.value());
 			}
 		});
 
-		runner.withPropertyValues("http.request.http-method-expression='POST'",
-			"http.request.headers-expression={'Content-Type':'application/json'}").run(context -> {
-			HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
-			String json = "{\"hello\":\"world\"}";
-			Message<?> message = MessageBuilder.withPayload(json)
-				.build();
-			ResponseEntity r = (ResponseEntity) httpRequestFunction.apply(message);
-			assertThat(r.getBody()).isEqualTo(json);
-			assertThat(r.getStatusCode().is2xxSuccessful()).isTrue();
-			assertThat(r.getHeaders().getContentType()).isEqualTo(MediaType.APPLICATION_JSON);
-			RecordedRequest request = server.takeRequest(100, TimeUnit.MILLISECONDS);
-			assertThat(request.getMethod()).isEqualTo("POST");
-		});
+		runner
+			.withPropertyValues("http.request.http-method-expression='POST'",
+					"http.request.headers-expression={'Content-Type':'application/json'}")
+			.run(context -> {
+				HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
+				String json = "{\"hello\":\"world\"}";
+				Message<?> message = MessageBuilder.withPayload(json).build();
+				ResponseEntity r = (ResponseEntity) httpRequestFunction.apply(message);
+				assertThat(r.getBody()).isEqualTo(json);
+				assertThat(r.getStatusCode().is2xxSuccessful()).isTrue();
+				assertThat(r.getHeaders().getContentType()).isEqualTo(MediaType.APPLICATION_JSON);
+				RecordedRequest request = server.takeRequest(100, TimeUnit.MILLISECONDS);
+				assertThat(request.getMethod()).isEqualTo("POST");
+			});
 	}
 
 	@Test
@@ -106,26 +103,27 @@ public class HttpRequestFunctionTestApplicationTests {
 		server.setDispatcher(new Dispatcher() {
 			@Override
 			public MockResponse dispatch(RecordedRequest recordedRequest) {
-				return new MockResponse().setHeader(HttpHeaders.CONTENT_TYPE,
-						recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
+				return new MockResponse()
+					.setHeader(HttpHeaders.CONTENT_TYPE, recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
 					.setBody(recordedRequest.getBody())
 					.setResponseCode(HttpStatus.CREATED.value());
 			}
 		});
 
-		runner.withPropertyValues("http.request.http-method-expression='POST'",
-			"http.request.expected-response-type=" + Map.class.getName()).run(context -> {
-			HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
-			Map<String, String> json = Collections.singletonMap("hello", "world");
-			Message<?> message = MessageBuilder.withPayload(json)
-				.build();
-			ResponseEntity r = (ResponseEntity) httpRequestFunction.apply(message);
-			assertThat(r.getBody()).isEqualTo(json);
-			assertThat(r.getStatusCode().is2xxSuccessful()).isTrue();
-			assertThat(r.getHeaders().getContentType()).isEqualTo(MediaType.APPLICATION_JSON);
-			RecordedRequest request = server.takeRequest(100, TimeUnit.MILLISECONDS);
-			assertThat(request.getMethod()).isEqualTo("POST");
-		});
+		runner
+			.withPropertyValues("http.request.http-method-expression='POST'",
+					"http.request.expected-response-type=" + Map.class.getName())
+			.run(context -> {
+				HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
+				Map<String, String> json = Collections.singletonMap("hello", "world");
+				Message<?> message = MessageBuilder.withPayload(json).build();
+				ResponseEntity r = (ResponseEntity) httpRequestFunction.apply(message);
+				assertThat(r.getBody()).isEqualTo(json);
+				assertThat(r.getStatusCode().is2xxSuccessful()).isTrue();
+				assertThat(r.getHeaders().getContentType()).isEqualTo(MediaType.APPLICATION_JSON);
+				RecordedRequest request = server.takeRequest(100, TimeUnit.MILLISECONDS);
+				assertThat(request.getMethod()).isEqualTo("POST");
+			});
 	}
 
 	@Test
@@ -133,24 +131,25 @@ public class HttpRequestFunctionTestApplicationTests {
 		server.setDispatcher(new Dispatcher() {
 			@Override
 			public MockResponse dispatch(RecordedRequest recordedRequest) {
-				return new MockResponse().setHeader(HttpHeaders.CONTENT_TYPE,
-						recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
-						.setBody(recordedRequest.getBody())
-						.setResponseCode(HttpStatus.ACCEPTED.value());
+				return new MockResponse()
+					.setHeader(HttpHeaders.CONTENT_TYPE, recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
+					.setBody(recordedRequest.getBody())
+					.setResponseCode(HttpStatus.ACCEPTED.value());
 			}
 		});
 
-		runner.withPropertyValues("http.request.http-method-expression='DELETE'",
-			"http.request.expected-response-type=" + Void.class.getName()).run(context -> {
-			HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
-			Message<?> message = MessageBuilder.withPayload("")
-				.build();
-			ResponseEntity r = (ResponseEntity) httpRequestFunction.apply(message);
-			assertThat(r.getBody()).isNull();
-			assertThat(r.getStatusCode().is2xxSuccessful()).isTrue();
-			RecordedRequest request = server.takeRequest(100, TimeUnit.MILLISECONDS);
-			assertThat(request.getMethod()).isEqualTo("DELETE");
-		});
+		runner
+			.withPropertyValues("http.request.http-method-expression='DELETE'",
+					"http.request.expected-response-type=" + Void.class.getName())
+			.run(context -> {
+				HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
+				Message<?> message = MessageBuilder.withPayload("").build();
+				ResponseEntity r = (ResponseEntity) httpRequestFunction.apply(message);
+				assertThat(r.getBody()).isNull();
+				assertThat(r.getStatusCode().is2xxSuccessful()).isTrue();
+				RecordedRequest request = server.takeRequest(100, TimeUnit.MILLISECONDS);
+				assertThat(request.getMethod()).isEqualTo("DELETE");
+			});
 	}
 
 	@Test
@@ -173,17 +172,15 @@ public class HttpRequestFunctionTestApplicationTests {
 		server.setDispatcher(new Dispatcher() {
 			@Override
 			public MockResponse dispatch(RecordedRequest recordedRequest) {
-				return new MockResponse().setHeader(HttpHeaders.CONTENT_TYPE,
-						recordedRequest.getHeader(HttpHeaders.ACCEPT))
-						.setBody(recordedRequest.getBody())
-						.setResponseCode(HttpStatus.OK.value());
+				return new MockResponse()
+					.setHeader(HttpHeaders.CONTENT_TYPE, recordedRequest.getHeader(HttpHeaders.ACCEPT))
+					.setBody(recordedRequest.getBody())
+					.setResponseCode(HttpStatus.OK.value());
 			}
 		});
 
-		runner.withPropertyValues(
-				"http.request.url-expression=headers['url']",
-				"http.request.http-method-expression=headers['method']",
-				"http.request.body-expression=headers['body']",
+		runner.withPropertyValues("http.request.url-expression=headers['url']",
+				"http.request.http-method-expression=headers['method']", "http.request.body-expression=headers['body']",
 				"http.request.headers-expression={Accept:'application/json'}")
 			.run(context -> {
 				Message<?> message = MessageBuilder.withPayload("")
@@ -196,8 +193,7 @@ public class HttpRequestFunctionTestApplicationTests {
 				ResponseEntity responseEntity = (ResponseEntity) httpRequestFunction.apply(message);
 				assertThat(responseEntity.getStatusCode()).isEqualTo(HttpStatus.OK);
 				assertThat(responseEntity.getBody()).isEqualTo(message.getHeaders().get("body"));
-				assertThat(responseEntity.getHeaders().getContentType())
-					.isEqualTo(MediaType.APPLICATION_JSON);
+				assertThat(responseEntity.getHeaders().getContentType()).isEqualTo(MediaType.APPLICATION_JSON);
 			});
 	}
 
@@ -206,25 +202,23 @@ public class HttpRequestFunctionTestApplicationTests {
 		server.setDispatcher(new Dispatcher() {
 			@Override
 			public MockResponse dispatch(RecordedRequest recordedRequest) {
-				return new MockResponse().setHeader(HttpHeaders.CONTENT_TYPE,
-						recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
-						.setBody(recordedRequest.getBody())
-						.setResponseCode(HttpStatus.OK.value());
+				return new MockResponse()
+					.setHeader(HttpHeaders.CONTENT_TYPE, recordedRequest.getHeader(HttpHeaders.CONTENT_TYPE))
+					.setBody(recordedRequest.getBody())
+					.setResponseCode(HttpStatus.OK.value());
 			}
 		});
-		runner.withPropertyValues(
-				"http.request..http-method-expression='POST'",
-				"http.request.headers-expression={'Content-Type':'application/octet-stream'}",
-				"http.request.expected-response-type=byte[]")
+		runner
+			.withPropertyValues("http.request..http-method-expression='POST'",
+					"http.request.headers-expression={'Content-Type':'application/octet-stream'}",
+					"http.request.expected-response-type=byte[]")
 			.run(context -> {
-				Message<?> message = MessageBuilder.withPayload("hello")
-					.build();
+				Message<?> message = MessageBuilder.withPayload("hello").build();
 				HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
 				ResponseEntity responseEntity = (ResponseEntity) httpRequestFunction.apply(message);
 				assertThat(responseEntity.getStatusCode()).isEqualTo(HttpStatus.OK);
 				assertThat(responseEntity.getBody()).isEqualTo("hello".getBytes());
-				assertThat(responseEntity.getHeaders().getContentType())
-					.isEqualTo(MediaType.APPLICATION_OCTET_STREAM);
+				assertThat(responseEntity.getHeaders().getContentType()).isEqualTo(MediaType.APPLICATION_OCTET_STREAM);
 			});
 	}
 
@@ -233,17 +227,14 @@ public class HttpRequestFunctionTestApplicationTests {
 		server.setDispatcher(new Dispatcher() {
 			@Override
 			public MockResponse dispatch(RecordedRequest recordedRequest) {
-				return new MockResponse()
-						.setBody(recordedRequest.getBody())
-						.setHeader("method", recordedRequest.getMethod())
-						.setResponseCode(HttpStatus.OK.value());
+				return new MockResponse().setBody(recordedRequest.getBody())
+					.setHeader("method", recordedRequest.getMethod())
+					.setResponseCode(HttpStatus.OK.value());
 			}
 		});
-		runner.withPropertyValues(
-				"http.request.http-method-expression=#jsonPath(payload,'$.myMethod')")
+		runner.withPropertyValues("http.request.http-method-expression=#jsonPath(payload,'$.myMethod')")
 			.run(context -> {
-				Message<?> message = MessageBuilder
-					.withPayload("{\"name\":\"Fred\",\"age\":41, \"myMethod\":\"POST\"}")
+				Message<?> message = MessageBuilder.withPayload("{\"name\":\"Fred\",\"age\":41, \"myMethod\":\"POST\"}")
 					.build();
 				HttpRequestFunction httpRequestFunction = context.getBean(HttpRequestFunction.class);
 				ResponseEntity responseEntity = (ResponseEntity) httpRequestFunction.apply(message);
@@ -258,5 +249,7 @@ public class HttpRequestFunctionTestApplicationTests {
 
 	@SpringBootApplication
 	static class HttpRequestFunctionTestApplication {
+
 	}
+
 }

function/spring-image-recognition-function/src/main/java/org/springframework/cloud/fn/image/recognition/ImageRecognition.java

@@ -46,23 +46,29 @@ import org.springframework.util.StreamUtils;
 public class ImageRecognition implements AutoCloseable {
 
 	private final List<String> labels;
+
 	private final GraphRunner imageNormalization;
+
 	private final GraphRunner imageRecognition;
+
 	private final GraphRunner maxProbability;
+
 	private final GraphRunner topKProbabilities;
 
 	/**
-	 * Instead of creating the {@link ImageRecognition} service explicitly via the constructor,
-	 * you should consider the convenience factory methods below. E.g.
-	 *
-	 *  {@link #inception(String, int, int, boolean)}
-	 *  {@link #mobileNetV1(String, int, int, boolean)}
-	 *  {@link #mobileNetV2(String, int, int, boolean)}
+	 * Instead of creating the {@link ImageRecognition} service explicitly via the
+	 * constructor, you should consider the convenience factory methods below. E.g.
 	 *
+	 * {@link #inception(String, int, int, boolean)}
+	 * {@link #mobileNetV1(String, int, int, boolean)}
+	 * {@link #mobileNetV2(String, int, int, boolean)}
 	 * @param modelUri location of the pre-trained model to use.
-	 * @param labelsUri location of the list fromMemory pre-trained categories used by the model.
-	 * @param imageRecognitionGraphInputName name of the Model's input node to send the input image to.
-	 * @param imageRecognitionGraphOutputName name of the Model's output node to retrieve the predictions from.
+	 * @param labelsUri location of the list fromMemory pre-trained categories used by the
+	 * model.
+	 * @param imageRecognitionGraphInputName name of the Model's input node to send the
+	 * input image to.
+	 * @param imageRecognitionGraphOutputName name of the Model's output node to retrieve
+	 * the predictions from.
 	 * @param imageHeight normalized image height.
 	 * @param imageWidth normalized image width.
 	 * @param mean mean value to normalize the input image.
@@ -71,62 +77,66 @@ public class ImageRecognition implements AutoCloseable {
 	 * @param cacheModel if true the pre-trained model is cached on the local file system.
 	 */
 	public ImageRecognition(String modelUri, String labelsUri, int imageHeight, int imageWidth, float mean, float scale,
-			String imageRecognitionGraphInputName, String imageRecognitionGraphOutputName, int responseSize, boolean cacheModel) {
+			String imageRecognitionGraphInputName, String imageRecognitionGraphOutputName, int responseSize,
+			boolean cacheModel) {
 
 		this.labels = labels(labelsUri);
 
 		/**
-		 * Normalizes the raw input image into format expected by the pre-trained Inception/MobileNetV1/MobileNetV2 models.
-		 * Typically the model is trained fromMemory images scaled to certain size. Usually it is 224x224 pixels, but can be
-		 * also 192x192, 160x160, 128128, 92x92. Use the (imageHeight, imageWidth) to set the desired size.
-		 * The colors, represented as R, G, B in 1-byte each were converted to float using (Value - Mean)/Scale.
+		 * Normalizes the raw input image into format expected by the pre-trained
+		 * Inception/MobileNetV1/MobileNetV2 models. Typically the model is trained
+		 * fromMemory images scaled to certain size. Usually it is 224x224 pixels, but can
+		 * be also 192x192, 160x160, 128128, 92x92. Use the (imageHeight, imageWidth) to
+		 * set the desired size. The colors, represented as R, G, B in 1-byte each were
+		 * converted to float using (Value - Mean)/Scale.
 		 *
-		 *  imageHeight normalized image height.
-		 *  imageWidth normalized image width.
-		 *  mean mean value to normalize the input image.
-		 *  scale scale to normalize the input image.
+		 * imageHeight normalized image height. imageWidth normalized image width. mean
+		 * mean value to normalize the input image. scale scale to normalize the input
+		 * image.
 		 */
-		this.imageNormalization = new GraphRunner("raw_image", "normalized_image")
-				.withGraphDefinition(tf -> {
-					Placeholder<String> input = tf.withName("raw_image").placeholder(String.class);
-					final Operand<Float> decodedImage =
-							tf.dtypes.cast(tf.image.decodeJpeg(input, DecodeJpeg.channels(3L)), Float.class);
-					final Operand<Float> resizedImage = tf.image.resizeBilinear(
-							tf.expandDims(decodedImage, tf.constant(0)),
-							tf.constant(new int[] { imageHeight, imageWidth }));
-					tf.withName("normalized_image").math.div(tf.math.sub(resizedImage, tf.constant(mean)), tf.constant(scale));
-				});
+		this.imageNormalization = new GraphRunner("raw_image", "normalized_image").withGraphDefinition(tf -> {
+			Placeholder<String> input = tf.withName("raw_image").placeholder(String.class);
+			final Operand<Float> decodedImage = tf.dtypes.cast(tf.image.decodeJpeg(input, DecodeJpeg.channels(3L)),
+					Float.class);
+			final Operand<Float> resizedImage = tf.image.resizeBilinear(tf.expandDims(decodedImage, tf.constant(0)),
+					tf.constant(new int[] { imageHeight, imageWidth }));
+			tf.withName("normalized_image").math.div(tf.math.sub(resizedImage, tf.constant(mean)), tf.constant(scale));
+		});
 
 		this.imageRecognition = new GraphRunner(imageRecognitionGraphInputName, imageRecognitionGraphOutputName)
-				.withGraphDefinition(new ProtoBufGraphDefinition(toResource(modelUri), cacheModel));
+			.withGraphDefinition(new ProtoBufGraphDefinition(toResource(modelUri), cacheModel));
 
-		this.maxProbability = new GraphRunner(Arrays.asList("recognition_result"), Arrays.asList("category", "probability"))
-				.withGraphDefinition(tf -> {
-					Placeholder<Float> input = tf.withName("recognition_result").placeholder(Float.class);
-					tf.withName("category").math.argMax(input, tf.constant(1));
-					tf.withName("probability").max(input, tf.constant(1));
-				});
+		this.maxProbability = new GraphRunner(Arrays.asList("recognition_result"),
+				Arrays.asList("category", "probability"))
+			.withGraphDefinition(tf -> {
+				Placeholder<Float> input = tf.withName("recognition_result").placeholder(Float.class);
+				tf.withName("category").math.argMax(input, tf.constant(1));
+				tf.withName("probability").max(input, tf.constant(1));
+			});
 
-		this.topKProbabilities = new GraphRunner("recognition_result", "topK")
-				.withGraphDefinition(tf -> {
-					Placeholder<Float> input = tf.withName("recognition_result").placeholder(Float.class);
-					tf.withName("topK").nn.topK(input, tf.constant(responseSize), TopK.sorted(true));
-				});
+		this.topKProbabilities = new GraphRunner("recognition_result", "topK").withGraphDefinition(tf -> {
+			Placeholder<Float> input = tf.withName("recognition_result").placeholder(Float.class);
+			tf.withName("topK").nn.topK(input, tf.constant(responseSize), TopK.sorted(true));
+		});
 	}
 
 	/**
-	 * Takes an byte encoded image and returns the most probable category recognized in the image along fromMemory its probability.
+	 * Takes an byte encoded image and returns the most probable category recognized in
+	 * the image along fromMemory its probability.
 	 * @param inputImage Byte array encoded image to recognize.
-	 * @return Returns a single map entry containing the names of the recognized categories as key and the confidence as value.
+	 * @return Returns a single map entry containing the names of the recognized
+	 * categories as key and the confidence as value.
 	 */
 	public Map<String, Double> recognizeMax(byte[] inputImage) {
 
 		try (Tensor inputTensor = Tensor.create(inputImage); GraphRunnerMemory memorize = new GraphRunnerMemory()) {
 
 			Map<String, Tensor<?>> max = this.imageNormalization.andThen(memorize)
-					.andThen(this.imageRecognition).andThen(memorize)
-					.andThen(this.maxProbability).andThen(memorize)
-					.apply(Collections.singletonMap("raw_image", inputTensor));
+				.andThen(this.imageRecognition)
+				.andThen(memorize)
+				.andThen(this.maxProbability)
+				.andThen(memorize)
+				.apply(Collections.singletonMap("raw_image", inputTensor));
 
 			long[] category = new long[1];
 			max.get("category").copyTo(category);
@@ -138,26 +148,28 @@ public class ImageRecognition implements AutoCloseable {
 	}
 
 	/**
-	 * Takes an byte encoded input image and returns the top K most probable categories recognized in the image
-	 * along fromMemory their probabilities.
-	 *
+	 * Takes an byte encoded input image and returns the top K most probable categories
+	 * recognized in the image along fromMemory their probabilities.
 	 * @param inputImage Byte array encoded image to recognize.
-	 * @return Returns a list of key-value pairs. Every key-value pair represents a single category recognized.
-	 * The key stands for the name(s) of the category while the value states the confidence that there is an
-	 * object of this category. The entries in the Map are ordered from the higher to the lower confidences.
+	 * @return Returns a list of key-value pairs. Every key-value pair represents a single
+	 * category recognized. The key stands for the name(s) of the category while the value
+	 * states the confidence that there is an object of this category. The entries in the
+	 * Map are ordered from the higher to the lower confidences.
 	 */
 	public Map<String, Double> recognizeTopK(byte[] inputImage) {
 
 		try (Tensor inputTensor = Tensor.create(inputImage); GraphRunnerMemory memorize = new GraphRunnerMemory()) {
 
-			Map<String, Tensor<?>> topKResults =
-					this.imageNormalization.andThen(memorize)
-							.andThen(this.imageRecognition).andThen(memorize)
-							.andThen(this.topKProbabilities).andThen(memorize)
-							.apply(Collections.singletonMap("raw_image", inputTensor));
+			Map<String, Tensor<?>> topKResults = this.imageNormalization.andThen(memorize)
+				.andThen(this.imageRecognition)
+				.andThen(memorize)
+				.andThen(this.topKProbabilities)
+				.andThen(memorize)
+				.apply(Collections.singletonMap("raw_image", inputTensor));
 
 			Tensor recognizedImagesTensor = memorize.getTensorMap().get(this.imageRecognition.getSingleFetchName());
-			float[][] results = new float[(int) recognizedImagesTensor.shape()[0]][(int) recognizedImagesTensor.shape()[1]];
+			float[][] results = new float[(int) recognizedImagesTensor.shape()[0]][(int) recognizedImagesTensor
+				.shape()[1]];
 			recognizedImagesTensor.copyTo(results);
 
 			Tensor<Float> topKTensor = topKResults.get("topK").expect(Float.class);
@@ -204,12 +216,10 @@ public class ImageRecognition implements AutoCloseable {
 	 * The Inception graph uses "input" as input and "output" as output.
 	 *
 	 */
-	public static ImageRecognition inception(String inceptionModelUri,
-			int normalizedImageSize, int responseSize, boolean cacheModel) {
-		return new ImageRecognition(inceptionModelUri, "classpath:/labels/inception_labels.txt",
-				normalizedImageSize, normalizedImageSize, 117f, 1f,
-				"input", "output",
-				responseSize, cacheModel);
+	public static ImageRecognition inception(String inceptionModelUri, int normalizedImageSize, int responseSize,
+			boolean cacheModel) {
+		return new ImageRecognition(inceptionModelUri, "classpath:/labels/inception_labels.txt", normalizedImageSize,
+				normalizedImageSize, 117f, 1f, "input", "output", responseSize, cacheModel);
 	}
 
 	/**
@@ -218,48 +228,50 @@ public class ImageRecognition implements AutoCloseable {
 	 *
 	 * The normalized image size is always square (e.g. H=W)
 	 *
-	 * The MobileNetV2 graph uses "input" as input and "MobilenetV2/Predictions/Reshape_1" as output.
-	 *
+	 * The MobileNetV2 graph uses "input" as input and "MobilenetV2/Predictions/Reshape_1"
+	 * as output.
 	 * @param mobileNetV2ModelUri model uri
-	 * @param normalizedImageSize Depends on the pre-trained model used. Usually 224px is used.
+	 * @param normalizedImageSize Depends on the pre-trained model used. Usually 224px is
+	 * used.
 	 * @param responseSize Number of responses fot topK requests.
 	 * @param cacheModel cache model
-	 * @return ImageRecognition instance configured fromMemory a MobileNetV2 pre-trained model.
+	 * @return ImageRecognition instance configured fromMemory a MobileNetV2 pre-trained
+	 * model.
 	 */
-	public static ImageRecognition mobileNetV2(String mobileNetV2ModelUri,
-			int normalizedImageSize, int responseSize, boolean cacheModel) {
-		return new ImageRecognition(mobileNetV2ModelUri, "classpath:/labels/mobilenet_labels.txt",
-				normalizedImageSize, normalizedImageSize, 0f, 127f,
-				"input", "MobilenetV2/Predictions/Reshape_1",
-				responseSize, cacheModel);
+	public static ImageRecognition mobileNetV2(String mobileNetV2ModelUri, int normalizedImageSize, int responseSize,
+			boolean cacheModel) {
+		return new ImageRecognition(mobileNetV2ModelUri, "classpath:/labels/mobilenet_labels.txt", normalizedImageSize,
+				normalizedImageSize, 0f, 127f, "input", "MobilenetV2/Predictions/Reshape_1", responseSize, cacheModel);
 	}
 
 	/**
 	 * Convenience for MobileNetV1 pre-trained models:
 	 * https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet_v1.md#pre-trained-models
 	 *
-	 * The MobileNetV1 graph uses "input" as input and "MobilenetV1/Predictions/Reshape_1" as output.
+	 * The MobileNetV1 graph uses "input" as input and "MobilenetV1/Predictions/Reshape_1"
+	 * as output.
 	 *
 	 */
-	public static ImageRecognition mobileNetV1(String mobileNetV1ModelUri,
-			int normalizedImageSize, int responseSize, boolean cacheModel) {
-		return new ImageRecognition(mobileNetV1ModelUri, "classpath:/labels/mobilenet_labels.txt",
-				normalizedImageSize, normalizedImageSize,
-				0f, 127f,
-				"input", "MobilenetV1/Predictions/Reshape_1",
-				responseSize, cacheModel);
+	public static ImageRecognition mobileNetV1(String mobileNetV1ModelUri, int normalizedImageSize, int responseSize,
+			boolean cacheModel) {
+		return new ImageRecognition(mobileNetV1ModelUri, "classpath:/labels/mobilenet_labels.txt", normalizedImageSize,
+				normalizedImageSize, 0f, 127f, "input", "MobilenetV1/Predictions/Reshape_1", responseSize, cacheModel);
 	}
 
 	/**
 	 * Convert image recognition results into {@link RecognitionResponse} domain list.
-	 * @param recognitionMap map containing the category mames and its probability. Returned by the
-	 * {@link ImageRecognition#recognizeMax(byte[])} and the ImageRecognition{@link #recognizeTopK(byte[])} methods
-	 * @return List of {@link RecognitionResponse} objects representing the name-to-probability pairs in the input map.
+	 * @param recognitionMap map containing the category mames and its probability.
+	 * Returned by the {@link ImageRecognition#recognizeMax(byte[])} and the
+	 * ImageRecognition{@link #recognizeTopK(byte[])} methods
+	 * @return List of {@link RecognitionResponse} objects representing the
+	 * name-to-probability pairs in the input map.
 	 */
 	public static List<RecognitionResponse> toRecognitionResponse(Map<String, Double> recognitionMap) {
-		return recognitionMap.entrySet().stream()
-				.map(nameProbabilityPair -> new RecognitionResponse(nameProbabilityPair.getKey(), nameProbabilityPair.getValue()))
-				.collect(Collectors.toList());
+		return recognitionMap.entrySet()
+			.stream()
+			.map(nameProbabilityPair -> new RecognitionResponse(nameProbabilityPair.getKey(),
+					nameProbabilityPair.getValue()))
+			.collect(Collectors.toList());
 	}
 
 	@Override
@@ -269,4 +281,5 @@ public class ImageRecognition implements AutoCloseable {
 		this.maxProbability.close();
 		this.topKProbabilities.close();
 	}
+
 }

function/spring-image-recognition-function/src/main/java/org/springframework/cloud/fn/image/recognition/ImageRecognitionAugmenter.java

@@ -33,7 +33,6 @@ import javax.imageio.ImageIO;
 import org.apache.commons.logging.Log;
 import org.apache.commons.logging.LogFactory;
 
-
 /**
  * Ability to to augment the input image fromMemory the recognized labels.
  *
@@ -47,6 +46,7 @@ public class ImageRecognitionAugmenter implements BiFunction<byte[], List<Recogn
 	public static final String IMAGE_FORMAT = "jpg";
 
 	private final Color textColor = Color.BLACK;
+
 	private final Color bgColor = new Color(167, 252, 0);
 
 	public ImageRecognitionAugmenter() {
@@ -54,7 +54,6 @@ public class ImageRecognitionAugmenter implements BiFunction<byte[], List<Recogn
 
 	/**
 	 * Augment the input image by adding the recognized classes.
-	 *
 	 * @param imageBytes input image as byte array
 	 * @param result computed recognition labels
 	 * @return the image augmented fromMemory recognized labels.

function/spring-image-recognition-function/src/main/java/org/springframework/cloud/fn/image/recognition/RecognitionResponse.java

@@ -20,7 +20,9 @@ package org.springframework.cloud.fn.image.recognition;
  * @author Christian Tzolov
  */
 public class RecognitionResponse {
+
 	private String label;
+
 	private Double probability;
 
 	public RecognitionResponse() {
@@ -51,4 +53,5 @@ public class RecognitionResponse {
 	public String toString() {
 		return "{label='" + label + ", probability=" + probability + '}';
 	}
+
 }

function/spring-image-recognition-function/src/main/java/org/springframework/cloud/fn/image/recognition/util/ImageNetReadableNamesWriter.java

@@ -36,22 +36,20 @@ import org.springframework.util.StreamUtils;
 /**
  * Create a text file mapping label id to human readable string.
  *
- * Produces a text file where every line represents single category. The line number represents the category id, while
- * the line text is human-readable names for the categories fromMemory this imagenet id.
+ * Produces a text file where every line represents single category. The line number
+ * represents the category id, while the line text is human-readable names for the
+ * categories fromMemory this imagenet id.
  *
- * Based on https://github.com/tensorflow/models/blob/master/research/slim/datasets/imagenet.py#L66
+ * Based on
+ * https://github.com/tensorflow/models/blob/master/research/slim/datasets/imagenet.py#L66
  *
- *   We retrieve a synset file, which contains a list of valid synset labels used
- *   by ILSVRC competition. There is one synset one per line, eg.
- *           #   n01440764
- *           #   n01443537
- *   We also retrieve a synset_to_human_file, which contains a mapping from synsets
- *   to human-readable names for every synset in Imagenet. These are stored in a
- *   tsv format, as follows:
- *           #   n02119247    black fox
- *           #   n02119359    silver fox
- *   We assign each synset (in alphabetical order) an integer, starting from 1
- *   (since 0 is reserved for the background class)
+ * We retrieve a synset file, which contains a list of valid synset labels used by ILSVRC
+ * competition. There is one synset one per line, eg. # n01440764 # n01443537 We also
+ * retrieve a synset_to_human_file, which contains a mapping from synsets to
+ * human-readable names for every synset in Imagenet. These are stored in a tsv format, as
+ * follows: # n02119247 black fox # n02119359 silver fox We assign each synset (in
+ * alphabetical order) an integer, starting from 1 (since 0 is reserved for the background
+ * class)
  *
  * @author Christian Tzolov
  */
@@ -62,8 +60,10 @@ public final class ImageNetReadableNamesWriter {
 
 	/** BASE_URL. */
 	public final static String BASE_URL = "https://raw.githubusercontent.com/tensorflow/models/master/research/inception/inception/data/";
+
 	/** SYNSET_URI. */
 	public final static String SYNSET_URI = BASE_URL + "imagenet_lsvrc_2015_synsets.txt";
+
 	/** SYNSET_TO_HUMAN_URI. */
 	public final static String SYNSET_TO_HUMAN_URI = BASE_URL + "imagenet_metadata.txt";
 
@@ -71,19 +71,24 @@ public final class ImageNetReadableNamesWriter {
 		Charset utf8 = Charset.forName("UTF-8");
 
 		try (InputStream synsetIs = toResource(SYNSET_URI).getInputStream();
-			InputStream synsetToHumanIs = toResource(SYNSET_TO_HUMAN_URI).getInputStream()) {
+				InputStream synsetToHumanIs = toResource(SYNSET_TO_HUMAN_URI).getInputStream()) {
 
-			List<String> synsetList = Arrays.asList(StreamUtils.copyToString(synsetIs, utf8)
-					.split("\n")).stream().map(l -> l.trim()).collect(Collectors.toList());
+			List<String> synsetList = Arrays.asList(StreamUtils.copyToString(synsetIs, utf8).split("\n"))
+				.stream()
+				.map(l -> l.trim())
+				.collect(Collectors.toList());
 			Assert.notNull(synsetList, "Failed to initialize the labels list");
-			Assert.isTrue(synsetList.size() == 1000, "Labels list is expected to be of " +
-					"size 1000 but was:" + synsetList.size());
+			Assert.isTrue(synsetList.size() == 1000,
+					"Labels list is expected to be of " + "size 1000 but was:" + synsetList.size());
 
-			Map<String, String> synsetToHuman = Arrays.asList(StreamUtils.copyToString(synsetToHumanIs, utf8)
-					.split("\n")).stream().map(s2h -> s2h.split("\t")).collect(Collectors.toMap(s -> s[0], s -> s[1]));
+			Map<String, String> synsetToHuman = Arrays
+				.asList(StreamUtils.copyToString(synsetToHumanIs, utf8).split("\n"))
+				.stream()
+				.map(s2h -> s2h.split("\t"))
+				.collect(Collectors.toMap(s -> s[0], s -> s[1]));
 			Assert.notNull(synsetToHuman, "Failed to initialize the synsetToHuman");
-			Assert.isTrue(synsetToHuman.size() == 21842, "synsetToHuman is expected to be of " +
-					"size 21842 but was:" + synsetToHuman.size());
+			Assert.isTrue(synsetToHuman.size() == 21842,
+					"synsetToHuman is expected to be of " + "size 21842 but was:" + synsetToHuman.size());
 
 			List<String> l = synsetList.stream().map(id -> synsetToHuman.get(id)).collect(Collectors.toList());
 
@@ -102,4 +107,5 @@ public final class ImageNetReadableNamesWriter {
 	public static Resource toResource(String uri) {
 		return new DefaultResourceLoader().getResource(uri);
 	}
+
 }

function/spring-image-recognition-function/src/test/java/org/springframework/cloud/fn/image/recognition/ImageRecognitionExample.java

@@ -42,62 +42,51 @@ public final class ImageRecognitionExample {
 		// MmobileNetV2 models
 		// https://github.com/tensorflow/models/tree/master/research/slim/nets/mobilenet#pretrained-models
 		String mobilenet_v2_modelUri = "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_1.4_224.tgz#mobilenet_v2_1.4_224_frozen.pb";
-		//String mobilenet_v2_modelUri = "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_0.35_96.tgz#mobilenet_v2_0.35_96_frozen.pb";
-		try (ImageRecognition imageRecognition = ImageRecognition.mobileNetV2(
-				mobilenet_v2_modelUri,
-				224,
-				5,
-				true)) {
+		// String mobilenet_v2_modelUri =
+		// "https://storage.googleapis.com/mobilenet_v2/checkpoints/mobilenet_v2_0.35_96.tgz#mobilenet_v2_0.35_96_frozen.pb";
+		try (ImageRecognition imageRecognition = ImageRecognition.mobileNetV2(mobilenet_v2_modelUri, 224, 5, true)) {
 
-			List<RecognitionResponse> recognizedObjects =
-					ImageRecognition.toRecognitionResponse(imageRecognition.recognizeTopK(inputImage));
+			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);
-			IOUtils.write(augmentedImage, new FileOutputStream("./image-recognition/target/image-augmented-mobilnetV2.jpg"));
-
+			IOUtils.write(augmentedImage,
+					new FileOutputStream("./image-recognition/target/image-augmented-mobilnetV2.jpg"));
 
 			String jsonRecognizedObjects = new JsonMapperFunction().apply(recognizedObjects);
 			System.out.println("mobilnetV2 result:" + jsonRecognizedObjects);
 		}
 
-
 		String mobilenet_v1_modelUri = "https://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz#mobilenet_v1_1.0_224_frozen.pb";
-		try (ImageRecognition recognitionService = ImageRecognition.mobileNetV1(
-				mobilenet_v1_modelUri,
-				224,
-				5,
-				true)) {
+		try (ImageRecognition recognitionService = ImageRecognition.mobileNetV1(mobilenet_v1_modelUri, 224, 5, true)) {
 
-			List<RecognitionResponse> recognizedObjects =
-					ImageRecognition.toRecognitionResponse(recognitionService.recognizeTopK(inputImage));
+			List<RecognitionResponse> recognizedObjects = ImageRecognition
+				.toRecognitionResponse(recognitionService.recognizeTopK(inputImage));
 
 			// Draw the predicted labels on top of the input image.
 			byte[] augmentedImage = new ImageRecognitionAugmenter().apply(inputImage, recognizedObjects);
-			IOUtils.write(augmentedImage, new FileOutputStream("./image-recognition/target/image-augmented-mobilnetV1.jpg"));
-
+			IOUtils.write(augmentedImage,
+					new FileOutputStream("./image-recognition/target/image-augmented-mobilnetV1.jpg"));
 
 			String jsonRecognizedObjects = new JsonMapperFunction().apply(recognizedObjects);
 			System.out.println("mobilnetV1 result:" + jsonRecognizedObjects);
 		}
 
 		String inception_modelUri = "https://storage.googleapis.com/scdf-tensorflow-models/image-recognition/tensorflow_inception_graph.pb";
-		try (ImageRecognition recognitionService = ImageRecognition.inception(
-				inception_modelUri,
-				224,
-				5,
-				true)) {
+		try (ImageRecognition recognitionService = ImageRecognition.inception(inception_modelUri, 224, 5, true)) {
 
-			List<RecognitionResponse> recognizedObjects =
-					ImageRecognition.toRecognitionResponse(recognitionService.recognizeTopK(inputImage));
+			List<RecognitionResponse> recognizedObjects = ImageRecognition
+				.toRecognitionResponse(recognitionService.recognizeTopK(inputImage));
 
 			// Draw the predicted labels on top of the input image.
 			byte[] augmentedImage = new ImageRecognitionAugmenter().apply(inputImage, recognizedObjects);
-			IOUtils.write(augmentedImage, new FileOutputStream("./image-recognition/target/image-augmented-inception.jpg"));
-
+			IOUtils.write(augmentedImage,
+					new FileOutputStream("./image-recognition/target/image-augmented-inception.jpg"));
 
 			String jsonRecognizedObjects = new JsonMapperFunction().apply(recognizedObjects);
 			System.out.println("inception result:" + jsonRecognizedObjects);
 		}
 	}
+
 }

function/spring-image-recognition-function/src/test/java/org/springframework/cloud/fn/image/recognition/ImageRecognitionExample2.java

@@ -45,8 +45,11 @@ public final class ImageRecognitionExample2 {
 		System.out.println(inceptions.recognizeTopK(inputImage));
 		System.out.println(ImageRecognition.toRecognitionResponse(inceptions.recognizeTopK(inputImage)));
 
-		IOUtils.write(augmenter.apply(inputImage, ImageRecognition.toRecognitionResponse(inceptions.recognizeTopK(inputImage))),
-				new FileOutputStream("./functions/function/image-recognition-function/target/image-augmented-inceptions.jpg"));
+		IOUtils.write(
+				augmenter.apply(inputImage,
+						ImageRecognition.toRecognitionResponse(inceptions.recognizeTopK(inputImage))),
+				new FileOutputStream(
+						"./functions/function/image-recognition-function/target/image-augmented-inceptions.jpg"));
 		inceptions.close();
 
 		ImageRecognition mobileNetV2 = ImageRecognition.mobileNetV2(
@@ -54,8 +57,11 @@ public final class ImageRecognitionExample2 {
 				224, 10, true);
 		System.out.println(mobileNetV2.recognizeMax(inputImage));
 		System.out.println(mobileNetV2.recognizeTopK(inputImage));
-		IOUtils.write(augmenter.apply(inputImage, ImageRecognition.toRecognitionResponse(mobileNetV2.recognizeTopK(inputImage))),
-				new FileOutputStream("./functions/function/image-recognition-function/target/image-augmented-mobilnetV2.jpg"));
+		IOUtils.write(
+				augmenter.apply(inputImage,
+						ImageRecognition.toRecognitionResponse(mobileNetV2.recognizeTopK(inputImage))),
+				new FileOutputStream(
+						"./functions/function/image-recognition-function/target/image-augmented-mobilnetV2.jpg"));
 		mobileNetV2.close();
 
 		ImageRecognition mobileNetV1 = ImageRecognition.mobileNetV1(
@@ -63,8 +69,12 @@ public final class ImageRecognitionExample2 {
 				224, 10, true);
 		System.out.println(mobileNetV1.recognizeMax(inputImage));
 		System.out.println(mobileNetV1.recognizeTopK(inputImage));
-		IOUtils.write(augmenter.apply(inputImage, ImageRecognition.toRecognitionResponse(mobileNetV1.recognizeTopK(inputImage))),
-				new FileOutputStream("./functions/function/image-recognition-function/target/image-augmented-mobilnetV1.jpg"));
+		IOUtils.write(
+				augmenter.apply(inputImage,
+						ImageRecognition.toRecognitionResponse(mobileNetV1.recognizeTopK(inputImage))),
+				new FileOutputStream(
+						"./functions/function/image-recognition-function/target/image-augmented-mobilnetV1.jpg"));
 		mobileNetV1.close();
 	}
+
 }

function/spring-image-recognition-function/src/test/java/org/springframework/cloud/fn/image/recognition/SavedModelTest.java

@@ -18,7 +18,6 @@ package org.springframework.cloud.fn.image.recognition;
 
 import java.util.Map;
 
-
 import com.google.protobuf.InvalidProtocolBufferException;
 import org.tensorflow.SavedModelBundle;
 import org.tensorflow.framework.MetaGraphDef;
@@ -40,11 +39,13 @@ public final class SavedModelTest {
 	 *
 	 */
 	public static void main(String[] args) throws InvalidProtocolBufferException {
-		SavedModelBundle savedModelBundle =
-				SavedModelBundle.load("/Users/ctzolov/Downloads/ssd_mobilenet_v1_coco_2017_11_17/saved_model", "serve");
-				//SavedModelBundle.load("/Users/ctzolov/Downloads/aiy_vision_classifier_plants_V1_1/", "serve");
-		//SavedModelBundle savedModelBundle =
-		//		SavedModelBundle.load("/Users/ctzolov/Downloads/mnasnet-a1/saved_model", "serve");
+		SavedModelBundle savedModelBundle = SavedModelBundle
+			.load("/Users/ctzolov/Downloads/ssd_mobilenet_v1_coco_2017_11_17/saved_model", "serve");
+		// SavedModelBundle.load("/Users/ctzolov/Downloads/aiy_vision_classifier_plants_V1_1/",
+		// "serve");
+		// SavedModelBundle savedModelBundle =
+		// SavedModelBundle.load("/Users/ctzolov/Downloads/mnasnet-a1/saved_model",
+		// "serve");
 
 		MetaGraphDef meta = MetaGraphDef.parseFrom(savedModelBundle.metaGraphDef());
 
@@ -54,10 +55,11 @@ public final class SavedModelTest {
 
 		savedModelBundle.session();
 
-		//Iterator<Operation> itr = savedModelBundle.graph().operations();
+		// Iterator<Operation> itr = savedModelBundle.graph().operations();
 		//
-		//while (itr.hasNext()) {
-		//	System.out.println("Operation: " + itr.next());
-		//}
+		// while (itr.hasNext()) {
+		// System.out.println("Operation: " + itr.next());
+		// }
 	}
+
 }

function/spring-object-detection-function/src/main/java/org/springframework/cloud/fn/object/detection/ObjectDetectionImageAugmenter.java

@@ -33,8 +33,8 @@ import org.springframework.cloud.fn.object.detection.domain.ObjectDetection;
 import org.springframework.util.CollectionUtils;
 
 /**
- * Augment the input image fromMemory detected object bounding boxes and categories.
- * For mask models and withMask set to true it draws the instance segmentation image as well.
+ * Augment the input image fromMemory detected object bounding boxes and categories. For
+ * mask models and withMask set to true it draws the instance segmentation image as well.
  *
  * @author Christian Tzolov
  */
@@ -48,6 +48,7 @@ public class ObjectDetectionImageAugmenter implements BiFunction<byte[], List<Ob
 	private String imageFormat = DEFAULT_IMAGE_FORMAT;
 
 	private final boolean withMask;
+
 	private boolean agnosticColors = false;
 
 	public ObjectDetectionImageAugmenter() {
@@ -99,8 +100,7 @@ public class ObjectDetectionImageAugmenter implements BiFunction<byte[], List<Ob
 						float[][] mask = od.getMask();
 						if (mask != null) {
 							Color maskColor = this.agnosticColors ? null : GraphicsUtils.getClassColor(cid);
-							BufferedImage maskImage = GraphicsUtils.createMaskImage(
-									mask, x2 - x1, y2 - y1, maskColor);
+							BufferedImage maskImage = GraphicsUtils.createMaskImage(mask, x2 - x1, y2 - y1, maskColor);
 							GraphicsUtils.overlayImages(bufferedImage, maskImage, x1, y1);
 						}
 					}
@@ -116,4 +116,5 @@ public class ObjectDetectionImageAugmenter implements BiFunction<byte[], List<Ob
 		// Null mend that QR image is found and not output message will be send.
 		return imageBytes;
 	}
+
 }

function/spring-object-detection-function/src/main/java/org/springframework/cloud/fn/object/detection/ObjectDetectionInputAdapter.java

@@ -41,8 +41,10 @@ public class ObjectDetectionInputAdapter implements Function<byte[], Map<String,
 
 	/** Make checkstyle happy. **/
 	public static final String RAW_IMAGE = "raw_image";
+
 	/** Make checkstyle happy. **/
 	public static final String NORMALIZED_IMAGE = "normalized_image";
+
 	/** Make checkstyle happy. **/
 	public static final long CHANNELS = 3;
 
@@ -50,14 +52,14 @@ public class ObjectDetectionInputAdapter implements Function<byte[], Map<String,
 
 	public ObjectDetectionInputAdapter() {
 
-		this.imageLoaderGraph = new GraphRunner(RAW_IMAGE, NORMALIZED_IMAGE)
-				.withGraphDefinition(tf -> {
-					Placeholder<String> rawImage = tf.withName(RAW_IMAGE).placeholder(String.class);
-					Operand<UInt8> decodedImage = tf.dtypes.cast(
-							tf.image.decodeJpeg(rawImage, DecodeJpeg.channels(CHANNELS)), UInt8.class);
-					// Expand dimensions since the model expects images to have shape: [1, H, W, 3]
-					tf.withName(NORMALIZED_IMAGE).expandDims(decodedImage, tf.constant(0));
-				});
+		this.imageLoaderGraph = new GraphRunner(RAW_IMAGE, NORMALIZED_IMAGE).withGraphDefinition(tf -> {
+			Placeholder<String> rawImage = tf.withName(RAW_IMAGE).placeholder(String.class);
+			Operand<UInt8> decodedImage = tf.dtypes.cast(tf.image.decodeJpeg(rawImage, DecodeJpeg.channels(CHANNELS)),
+					UInt8.class);
+			// Expand dimensions since the model expects images to have shape: [1, H, W,
+			// 3]
+			tf.withName(NORMALIZED_IMAGE).expandDims(decodedImage, tf.constant(0));
+		});
 	}
 
 	@Override
@@ -73,4 +75,5 @@ public class ObjectDetectionInputAdapter implements Function<byte[], Map<String,
 			this.imageLoaderGraph.close();
 		}
 	}
+
 }

function/spring-object-detection-function/src/main/java/org/springframework/cloud/fn/object/detection/ObjectDetectionInputConverter.java

@@ -35,8 +35,8 @@ import org.tensorflow.types.UInt8;
 import org.springframework.cloud.fn.common.tensorflow.deprecated.GraphicsUtils;
 
 /**
- * Converts byte array image into a input Tensor for the Object Detection API. The computed image tensors uses the
- * 'image_tensor' model placeholder.
+ * 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
  */
@@ -95,4 +95,5 @@ public class ObjectDetectionInputConverter implements Function<byte[][], Map<Str
 			data[i + 2] = tmp;
 		}
 	}
+
 }

function/spring-object-detection-function/src/main/java/org/springframework/cloud/fn/object/detection/ObjectDetectionOutputConverter.java

@@ -37,21 +37,22 @@ import org.springframework.util.StreamUtils;
 import org.springframework.util.StringUtils;
 
 /**
- * Converts the Tensorflow Object Detection result into {@link ObjectDetection} list.
- * The pre-trained Object Detection models (http://bit.ly/2osxMAY) produce 3 tensor outputs:
- *  (1) detection_classes - containing the ids of detected objects, (2) detection_scores - confidence probabilities of the
- *  detected object and (3) detection_boxes - the object bounding boxes withing the images.
+ * Converts the Tensorflow Object Detection result into {@link ObjectDetection} list. The
+ * pre-trained Object Detection models (http://bit.ly/2osxMAY) produce 3 tensor outputs:
+ * (1) detection_classes - containing the ids of detected objects, (2) detection_scores -
+ * confidence probabilities of the detected object and (3) detection_boxes - the object
+ * bounding boxes withing the images.
  *
- *  The MASK based models provide to 2 additional tensors: (4) num_detections and (5) detection_masks.
+ * The MASK based models provide to 2 additional tensors: (4) num_detections and (5)
+ * detection_masks.
  *
- * All outputs tensors are float arrays, having:
- * - 1 as the first dimension
- * - maxObjects as the second dimension
- * While boxesT will have 4 as the third dimension (2 sets of (x, y) coordinates).
- * This can be verified by looking at scoresT.shape() etc.
+ * All outputs tensors are float arrays, having: - 1 as the first dimension - maxObjects
+ * as the second dimension While boxesT will have 4 as the third dimension (2 sets of (x,
+ * y) coordinates). This can be verified by looking at scoresT.shape() etc.
  *
- * The format detected classes (e.g. labels) names is defined by the 'string_int_labels_map.proto'. The input list
- * is available at: https://github.com/tensorflow/models/tree/master/research/object_detection/data
+ * The format detected classes (e.g. labels) names is defined by the
+ * 'string_int_labels_map.proto'. The input list is available at:
+ * https://github.com/tensorflow/models/tree/master/research/object_detection/data
  *
  * @author Christian Tzolov
  */
@@ -61,17 +62,23 @@ public class ObjectDetectionOutputConverter implements Function<Map<String, Tens
 
 	/** DETECTION_CLASSES. */
 	public static final String DETECTION_CLASSES = "detection_classes";
+
 	/** DETECTION_SCORES. */
 	public static final String DETECTION_SCORES = "detection_scores";
+
 	/** DETECTION_BOXES. */
 	public static final String DETECTION_BOXES = "detection_boxes";
+
 	/** DETECTION_MASKS. */
 	public static final String DETECTION_MASKS = "detection_masks";
+
 	/** NUM_DETECTIONS. */
 	public static final String NUM_DETECTIONS = "num_detections";
 
 	private final String[] labels;
+
 	private float confidence;
+
 	private List<String> modelFetch;
 
 	public ObjectDetectionOutputConverter(Resource labelsResource, float confidence, List<String> modelFetch) {
@@ -96,15 +103,16 @@ public class ObjectDetectionOutputConverter implements Function<Map<String, Tens
 	private static String[] loadLabels(Resource labelsResource) throws Exception {
 		try (InputStream is = labelsResource.getInputStream()) {
 			String text = StreamUtils.copyToString(is, Charset.forName("UTF-8"));
-			StringIntLabelMapOuterClass.StringIntLabelMap.Builder builder =
-					StringIntLabelMapOuterClass.StringIntLabelMap.newBuilder();
+			StringIntLabelMapOuterClass.StringIntLabelMap.Builder builder = StringIntLabelMapOuterClass.StringIntLabelMap
+				.newBuilder();
 			TextFormat.merge(text, builder);
 			StringIntLabelMapOuterClass.StringIntLabelMap proto = builder.build();
 
-			int maxLabelId = proto.getItemList().stream()
-					.map(StringIntLabelMapOuterClass.StringIntLabelMapItem::getId)
-					.max(Comparator.comparing(i -> i))
-					.orElse(-1);
+			int maxLabelId = proto.getItemList()
+				.stream()
+				.map(StringIntLabelMapOuterClass.StringIntLabelMapItem::getId)
+				.max(Comparator.comparing(i -> i))
+				.orElse(-1);
 
 			String[] labelIdToNameMap = new String[maxLabelId + 1];
 			for (StringIntLabelMapOuterClass.StringIntLabelMapItem item : proto.getItemList()) {
@@ -112,7 +120,8 @@ public class ObjectDetectionOutputConverter implements Function<Map<String, Tens
 					labelIdToNameMap[item.getId()] = item.getDisplayName();
 				}
 				else {
-					// Common practice is to set the name to a MID or Synsets Id. Synset is a set of synonyms that
+					// Common practice is to set the name to a MID or Synsets Id. Synset
+					// is a set of synonyms that
 					// share a common meaning: https://en.wikipedia.org/wiki/WordNet
 					labelIdToNameMap[item.getId()] = item.getName();
 				}
@@ -125,13 +134,13 @@ public class ObjectDetectionOutputConverter implements Function<Map<String, Tens
 	public List<List<ObjectDetection>> apply(Map<String, Tensor<?>> tensorMap) {
 
 		try (Tensor<Float> scoresTensor = tensorMap.get(DETECTION_SCORES).expect(Float.class);
-			Tensor<Float> classesTensor = tensorMap.get(DETECTION_CLASSES).expect(Float.class);
-			Tensor<Float> boxesTensor = tensorMap.get(DETECTION_BOXES).expect(Float.class)
-		) {
+				Tensor<Float> classesTensor = tensorMap.get(DETECTION_CLASSES).expect(Float.class);
+				Tensor<Float> boxesTensor = tensorMap.get(DETECTION_BOXES).expect(Float.class)) {
 			// All these tensors have:
 			// - 1 as the first dimension
 			// - maxObjects as the second dimension
-			// While boxesT will have 4 as the third dimension (2 sets of (x, y) coordinates).
+			// While boxesT will have 4 as the third dimension (2 sets of (x, y)
+			// coordinates).
 			// This can be verified by looking at scoresT.shape() etc.
 			int batchSize = (int) scoresTensor.shape()[0];
 			int maxObjects = (int) scoresTensor.shape()[1];
@@ -143,10 +152,10 @@ public class ObjectDetectionOutputConverter implements Function<Map<String, Tens
 
 			for (int batchIndex = 0; batchIndex < batchSize; batchIndex++) {
 
-
 				List<ObjectDetection> objectDetections = new ArrayList<>();
 
-				// Collect only the objects whose scores are at above the configured confidence threshold.
+				// Collect only the objects whose scores are at above the configured
+				// confidence threshold.
 				for (int i = 0; i < scores[batchIndex].length; ++i) {
 					if (scores[batchIndex][i] >= confidence) {
 						String category = labels[(int) classes[batchIndex][i]];
@@ -169,7 +178,8 @@ public class ObjectDetectionOutputConverter implements Function<Map<String, Tens
 
 							if (masksTensor != null) {
 								long[] shape = masksTensor.shape();
-								float[][][][] masks = masksTensor.copyTo(new float[(int) shape[0]][(int) shape[1]][(int) shape[2]][(int) shape[3]]);
+								float[][][][] masks = masksTensor
+									.copyTo(new float[(int) shape[0]][(int) shape[1]][(int) shape[2]][(int) shape[3]]);
 								od.setMask(masks[batchIndex][i]);
 								logger.debug(String.format("Num detections: %s, Masks: %s", nd, masks));
 							}
@@ -184,4 +194,5 @@ public class ObjectDetectionOutputConverter implements Function<Map<String, Tens
 			return batchObjectDetections;
 		}
 	}
+
 }

function/spring-object-detection-function/src/main/java/org/springframework/cloud/fn/object/detection/ObjectDetectionService.java

@@ -29,66 +29,79 @@ import org.springframework.core.io.DefaultResourceLoader;
 import org.springframework.util.StreamUtils;
 
 /**
- * Convenience class that leverages the the {@link ObjectDetectionInputConverter}, {@link ObjectDetectionOutputConverter} and {@link TensorFlowService}
- * in combination fromMemory the Tensorflow Object Detection API (https://github.com/tensorflow/models/tree/master/research/object_detection)
- * models for detection objects in input images.
+ * Convenience class that leverages the the {@link ObjectDetectionInputConverter},
+ * {@link ObjectDetectionOutputConverter} and {@link TensorFlowService} in combination
+ * fromMemory the Tensorflow Object Detection API
+ * (https://github.com/tensorflow/models/tree/master/research/object_detection) models for
+ * detection objects in input images.
  *
- * All pre-trained models (https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md) and labels are supported.
+ * All pre-trained models
+ * (https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md)
+ * and labels are supported.
  *
- * You can download pre-trained models directly from the zoo: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
- * Just use the URI notation: (zoo model tar.gz url)#(name of the frozen model file name). To speedup the bootstrap
- * performance you should consider downloading the models locally and use the file:/"path to my model" URI instead!
+ * You can download pre-trained models directly from the zoo:
+ * https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
+ * Just use the URI notation: (zoo model tar.gz url)#(name of the frozen model file name).
+ * To speedup the bootstrap performance you should consider downloading the models locally
+ * and use the file:/"path to my model" URI instead!
  *
- * The object category labels for the pre-trained models are available at: https://github.com/tensorflow/models/tree/master/research/object_detection/data
- * Use the labels applicable for the model. Also, for performance reasons you may consider to download the labels
- * and load them from file: instead.
+ * The object category labels for the pre-trained models are available at:
+ * https://github.com/tensorflow/models/tree/master/research/object_detection/data Use the
+ * labels applicable for the model. Also, for performance reasons you may consider to
+ * download the labels and load them from file: instead.
  *
  * @author Christian Tzolov
  */
 public class ObjectDetectionService {
 
 	/** Default list of fetch names for Box models. */
-	public static List<String> FETCH_NAMES = Arrays.asList(
-			ObjectDetectionOutputConverter.DETECTION_SCORES, ObjectDetectionOutputConverter.DETECTION_CLASSES,
-			ObjectDetectionOutputConverter.DETECTION_BOXES, ObjectDetectionOutputConverter.NUM_DETECTIONS);
-
-	/** Default list of fetch names for mask supporting models. */
-	public static List<String> FETCH_NAMES_WITH_MASKS = Arrays.asList(
-			ObjectDetectionOutputConverter.DETECTION_SCORES, ObjectDetectionOutputConverter.DETECTION_CLASSES,
-			ObjectDetectionOutputConverter.DETECTION_BOXES, ObjectDetectionOutputConverter.DETECTION_MASKS,
+	public static List<String> FETCH_NAMES = Arrays.asList(ObjectDetectionOutputConverter.DETECTION_SCORES,
+			ObjectDetectionOutputConverter.DETECTION_CLASSES, ObjectDetectionOutputConverter.DETECTION_BOXES,
 			ObjectDetectionOutputConverter.NUM_DETECTIONS);
 
+	/** Default list of fetch names for mask supporting models. */
+	public static List<String> FETCH_NAMES_WITH_MASKS = Arrays.asList(ObjectDetectionOutputConverter.DETECTION_SCORES,
+			ObjectDetectionOutputConverter.DETECTION_CLASSES, ObjectDetectionOutputConverter.DETECTION_BOXES,
+			ObjectDetectionOutputConverter.DETECTION_MASKS, ObjectDetectionOutputConverter.NUM_DETECTIONS);
+
 	private final ObjectDetectionInputConverter inputConverter;
+
 	private final ObjectDetectionOutputConverter outputConverter;
+
 	private final TensorFlowService tensorFlowService;
 
 	public ObjectDetectionService() {
 		this("https://download.tensorflow.org/models/object_detection/ssdlite_mobilenet_v2_coco_2018_05_09.tar.gz#frozen_inference_graph.pb",
-				"https://storage.googleapis.com/scdf-tensorflow-models/object-detection/mscoco_label_map.pbtxt",
-				0.4f, false, true);
+				"https://storage.googleapis.com/scdf-tensorflow-models/object-detection/mscoco_label_map.pbtxt", 0.4f,
+				false, true);
 	}
 
 	/**
 	 * Convenience constructor that would initialize all necessary internal components.
 	 * @param modelUri URI of the pre-trained, frozen Tensorflow model.
 	 * @param labelsUri URI of the pre-trained category labels.
-	 * @param confidence Confidence threshold. Only objects detected wth confidence above this threshold will be returned.
-	 * @param withMasks If a Mask model is selected then you can use this flag to extract the instance segmentation masks as well.
+	 * @param confidence Confidence threshold. Only objects detected wth confidence above
+	 * this threshold will be returned.
+	 * @param withMasks If a Mask model is selected then you can use this flag to extract
+	 * the instance segmentation masks as well.
 	 */
-	public ObjectDetectionService(String modelUri, String labelsUri,
-			float confidence, boolean withMasks, boolean cacheModel) {
+	public ObjectDetectionService(String modelUri, String labelsUri, float confidence, boolean withMasks,
+			boolean cacheModel) {
 		this.inputConverter = new ObjectDetectionInputConverter();
 		List<String> fetchNames = withMasks ? FETCH_NAMES_WITH_MASKS : FETCH_NAMES;
-		this.outputConverter = new ObjectDetectionOutputConverter(
-				new DefaultResourceLoader().getResource(labelsUri), confidence, fetchNames);
-		this.tensorFlowService = new TensorFlowService(
-				new DefaultResourceLoader().getResource(modelUri), fetchNames, cacheModel);
+		this.outputConverter = new ObjectDetectionOutputConverter(new DefaultResourceLoader().getResource(labelsUri),
+				confidence, fetchNames);
+		this.tensorFlowService = new TensorFlowService(new DefaultResourceLoader().getResource(modelUri), fetchNames,
+				cacheModel);
 	}
 
 	/**
-	 * Generic constructor thea allow the converter to be pre-configured before passed to the service.
-	 * @param inputConverter Converter from byte array to object detection input image tensor
-	 * @param outputConverter Covets the object detection output tensors into {@link ObjectDetection } list
+	 * Generic constructor thea allow the converter to be pre-configured before passed to
+	 * the service.
+	 * @param inputConverter Converter from byte array to object detection input image
+	 * tensor
+	 * @param outputConverter Covets the object detection output tensors into
+	 * {@link ObjectDetection } list
 	 * @param tensorFlowService Java tensorflow runner instance
 	 */
 	public ObjectDetectionService(ObjectDetectionInputConverter inputConverter,
@@ -100,9 +113,9 @@ public class ObjectDetectionService {
 
 	/**
 	 * Detects objects in a single input image identified by its URI.
-	 *
 	 * @param imageUri input image's URI
-	 * @return Returns a list of {@link ObjectDetection} domain objects representing detected objects
+	 * @return Returns a list of {@link ObjectDetection} domain objects representing
+	 * detected objects
 	 */
 	public List<ObjectDetection> detect(String imageUri) {
 		try (InputStream is = new DefaultResourceLoader().getResource(imageUri).getInputStream()) {
@@ -116,10 +129,11 @@ public class ObjectDetectionService {
 
 	/**
 	 * Detects objects in a single {@link BufferedImage}.
-	 *
 	 * @param image Input image to detect objects from.
-	 * @param format Image format (e.g. jpg, png ...) to use when converting the buffer into byte array.
-	 * @return Returns a list of {@link ObjectDetection} domain objects representing detected objects in the input image
+	 * @param format Image format (e.g. jpg, png ...) to use when converting the buffer
+	 * into byte array.
+	 * @return Returns a list of {@link ObjectDetection} domain objects representing
+	 * detected objects in the input image
 	 */
 	public List<ObjectDetection> detect(BufferedImage image, String format) {
 		return this.detect(GraphicsUtils.toImageByteArray(image, format));
@@ -127,21 +141,27 @@ public class ObjectDetectionService {
 
 	/**
 	 * Detects objects from a single input image encoded as byte array.
-	 *
 	 * @param image Input image encoded as byte array
-	 * @return Returns a list of {@link ObjectDetection} domain objects representing detected objects in the input image
+	 * @return Returns a list of {@link ObjectDetection} domain objects representing
+	 * detected objects in the input image
 	 */
 	public List<ObjectDetection> detect(byte[] image) {
-		return this.inputConverter.andThen(this.tensorFlowService).andThen(this.outputConverter).apply(new byte[][] { image }).get(0);
+		return this.inputConverter.andThen(this.tensorFlowService)
+			.andThen(this.outputConverter)
+			.apply(new byte[][] { image })
+			.get(0);
 	}
 
 	/**
 	 * Uses detects objects from a batch of input images encoded as byte array.
-	 *
-	 * @param batchedImages Batch of input images encoded as byte arrays. First dimension is the batch size and second the image bytes.
-	 * @return Returns list of lists. For every input image in the batch a list of {@link ObjectDetection} domain objects representing detected objects in the input image.
+	 * @param batchedImages Batch of input images encoded as byte arrays. First dimension
+	 * is the batch size and second the image bytes.
+	 * @return Returns list of lists. For every input image in the batch a list of
+	 * {@link ObjectDetection} domain objects representing detected objects in the input
+	 * image.
 	 */
 	public List<List<ObjectDetection>> detect(byte[][] batchedImages) {
 		return this.inputConverter.andThen(this.tensorFlowService).andThen(this.outputConverter).apply(batchedImages);
 	}
+
 }

function/spring-object-detection-function/src/main/java/org/springframework/cloud/fn/object/detection/ObjectDetectionService2.java

@@ -40,35 +40,34 @@ import org.springframework.core.io.DefaultResourceLoader;
 public class ObjectDetectionService2 implements AutoCloseable {
 
 	/** Default Box models fetch names. */
-	public static List<String> FETCH_NAMES = Arrays.asList(
-			ObjectDetectionOutputConverter.DETECTION_SCORES, ObjectDetectionOutputConverter.DETECTION_CLASSES,
-			ObjectDetectionOutputConverter.DETECTION_BOXES, ObjectDetectionOutputConverter.NUM_DETECTIONS);
-
-	/** Default Models models fetch names. */
-	public static List<String> FETCH_NAMES_WITH_MASKS = Arrays.asList(
-			ObjectDetectionOutputConverter.DETECTION_SCORES, ObjectDetectionOutputConverter.DETECTION_CLASSES,
-			ObjectDetectionOutputConverter.DETECTION_BOXES, ObjectDetectionOutputConverter.DETECTION_MASKS,
+	public static List<String> FETCH_NAMES = Arrays.asList(ObjectDetectionOutputConverter.DETECTION_SCORES,
+			ObjectDetectionOutputConverter.DETECTION_CLASSES, ObjectDetectionOutputConverter.DETECTION_BOXES,
 			ObjectDetectionOutputConverter.NUM_DETECTIONS);
 
-	private final GraphRunner imageNormalization;
-	private final GraphRunner objectDetection;
-	private final ObjectDetectionOutputConverter outputConverter;
+	/** Default Models models fetch names. */
+	public static List<String> FETCH_NAMES_WITH_MASKS = Arrays.asList(ObjectDetectionOutputConverter.DETECTION_SCORES,
+			ObjectDetectionOutputConverter.DETECTION_CLASSES, ObjectDetectionOutputConverter.DETECTION_BOXES,
+			ObjectDetectionOutputConverter.DETECTION_MASKS, ObjectDetectionOutputConverter.NUM_DETECTIONS);
 
+	private final GraphRunner imageNormalization;
+
+	private final GraphRunner objectDetection;
+
+	private final ObjectDetectionOutputConverter outputConverter;
 
 	public ObjectDetectionService2(String modelUri, ObjectDetectionOutputConverter outputConverter) {
 
-		this.imageNormalization = new GraphRunner("raw_image", "normalized_image")
-				.withGraphDefinition(tf -> {
-					Placeholder<String> rawImage = tf.withName("raw_image").placeholder(String.class);
-					Operand<UInt8> decodedImage = tf.dtypes.cast(
-							tf.image.decodeJpeg(rawImage, DecodeJpeg.channels(3L)), UInt8.class);
-					// Expand dimensions since the model expects images to have shape: [1, H, W, 3]
-					tf.withName("normalized_image").expandDims(decodedImage, tf.constant(0));
-				});
+		this.imageNormalization = new GraphRunner("raw_image", "normalized_image").withGraphDefinition(tf -> {
+			Placeholder<String> rawImage = tf.withName("raw_image").placeholder(String.class);
+			Operand<UInt8> decodedImage = tf.dtypes.cast(tf.image.decodeJpeg(rawImage, DecodeJpeg.channels(3L)),
+					UInt8.class);
+			// Expand dimensions since the model expects images to have shape: [1, H, W,
+			// 3]
+			tf.withName("normalized_image").expandDims(decodedImage, tf.constant(0));
+		});
 
 		this.objectDetection = new GraphRunner(Arrays.asList("image_tensor"), FETCH_NAMES)
-				.withGraphDefinition(new ProtoBufGraphDefinition(
-						new DefaultResourceLoader().getResource(modelUri), true));
+			.withGraphDefinition(new ProtoBufGraphDefinition(new DefaultResourceLoader().getResource(modelUri), true));
 
 		this.outputConverter = outputConverter;
 	}
@@ -77,9 +76,10 @@ public class ObjectDetectionService2 implements AutoCloseable {
 		try (Tensor inputTensor = Tensor.create(image); GraphRunnerMemory memorize = new GraphRunnerMemory()) {
 
 			List<List<ObjectDetection>> out = this.imageNormalization.andThen(memorize)
-					.andThen(this.objectDetection).andThen(memorize)
-					.andThen(outputConverter)
-					.apply(Collections.singletonMap("raw_image", inputTensor));
+				.andThen(this.objectDetection)
+				.andThen(memorize)
+				.andThen(outputConverter)
+				.apply(Collections.singletonMap("raw_image", inputTensor));
 
 			return out.get(0);
 
@@ -90,7 +90,7 @@ public class ObjectDetectionService2 implements AutoCloseable {
 	public void close() {
 		this.imageNormalization.close();
 		this.objectDetection.close();
-		//this.outputConverter.close();
+		// this.outputConverter.close();
 	}
 
 	public static void main(String[] args) throws IOException {
@@ -100,7 +100,8 @@ public class ObjectDetectionService2 implements AutoCloseable {
 		ObjectDetectionOutputConverter outputAdapter = new ObjectDetectionOutputConverter(
 				new DefaultResourceLoader().getResource(labelUri), 0.4f, FETCH_NAMES);
 
-		//byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/object-detection.jpg");
+		// byte[] inputImage =
+		// GraphicsUtils.loadAsByteArray("classpath:/images/object-detection.jpg");
 		byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/wild-animals-15.jpg");
 
 		try (ObjectDetectionService2 objectDetectionService2 = new ObjectDetectionService2(modelUri, outputAdapter)) {
@@ -110,4 +111,5 @@ public class ObjectDetectionService2 implements AutoCloseable {
 			System.out.println(boza);
 		}
 	}
+
 }

function/spring-object-detection-function/src/main/java/org/springframework/cloud/fn/object/detection/domain/ObjectDetection.java

@@ -28,12 +28,19 @@ import com.fasterxml.jackson.annotation.JsonInclude;
 public class ObjectDetection {
 
 	private String name;
+
 	private float confidence;
+
 	private float x1;
+
 	private float y1;
+
 	private float x2;
+
 	private float y2;
+
 	private float[][] mask;
+
 	private int cid;
 
 	public String getName() {
@@ -102,15 +109,8 @@ public class ObjectDetection {
 
 	@Override
 	public String toString() {
-		return "ObjectDetection{" +
-				"name='" + name + '\'' +
-				", confidence=" + confidence +
-				", x1=" + x1 +
-				", y1=" + y1 +
-				", x2=" + x2 +
-				", y2=" + y2 +
-				", mask=" + Arrays.toString(mask) +
-				", cid=" + cid +
-				'}';
+		return "ObjectDetection{" + "name='" + name + '\'' + ", confidence=" + confidence + ", x1=" + x1 + ", y1=" + y1
+				+ ", x2=" + x2 + ", y2=" + y2 + ", mask=" + Arrays.toString(mask) + ", cid=" + cid + '}';
 	}
+
 }

function/spring-object-detection-function/src/test/java/org/springframework/cloud/fn/object/detection/examples/ExampleInstanceSegmentation.java

@@ -32,15 +32,15 @@ import org.springframework.core.io.DefaultResourceLoader;
 import org.springframework.core.io.ResourceLoader;
 
 /**
- * 4 of the pre-trained model in the model zoo (https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md)
+ * 4 of the pre-trained model in the model zoo
+ * (https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md)
  * can also compute the masks of the detected objects, providing instance segmentation.
  * <p>
  * Here are the models that can be used for instance segmentation.
  * <p>
- * mask_rcnn_inception_resnet_v2_atrous_coco	771	36	Masks
- * mask_rcnn_inception_v2_coco					79	25	Masks
- * mask_rcnn_resnet101_atrous_coco				470	33	Masks
- * mask_rcnn_resnet50_atrous_coco				343	29	Masks
+ * mask_rcnn_inception_resnet_v2_atrous_coco 771 36 Masks mask_rcnn_inception_v2_coco 79
+ * 25 Masks mask_rcnn_resnet101_atrous_coco 470 33 Masks mask_rcnn_resnet50_atrous_coco
+ * 343 29 Masks
  *
  * @author Christian Tzolov
  */
@@ -50,44 +50,53 @@ public class ExampleInstanceSegmentation {
 
 		ResourceLoader resourceLoader = new DefaultResourceLoader();
 
-		// You can download pre-trained models directly from the zoo: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
-		// Just use the notation <zoo model tar.gz url>#<name of the frozen model file name>
-		// For performance reasons you may consider downloading the model locally and use the file:/<path to my model> URI instead!
+		// You can download pre-trained models directly from the zoo:
+		// https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
+		// Just use the notation <zoo model tar.gz url>#<name of the frozen model file
+		// name>
+		// For performance reasons you may consider downloading the model locally and use
+		// the file:/<path to my model> URI instead!
 		String model = "https://download.tensorflow.org/models/object_detection/mask_rcnn_inception_resnet_v2_atrous_coco_2018_01_28.tar.gz#frozen_inference_graph.pb";
 
 		// All labels for the pre-trained models are available at:
 		// https://github.com/tensorflow/models/tree/master/research/object_detection/data
 		// Use the labels applicable for the model.
-		// Also, for performance reasons you may consider to download the labels and load them from file: instead.
+		// Also, for performance reasons you may consider to download the labels and load
+		// them from file: instead.
 		String labels = "https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/data/mscoco_label_map.pbtxt";
 
-		// You can cache the TF model on the local file system to improve the bootstrap performance on consecutive runs!
+		// You can cache the TF model on the local file system to improve the bootstrap
+		// performance on consecutive runs!
 		boolean CACHE_TF_MODEL = true;
 
-		// For the pre-trained models fromMemory mask you can set the INSTANCE_SEGMENTATION to enable object instance segmentation as well
+		// For the pre-trained models fromMemory mask you can set the
+		// INSTANCE_SEGMENTATION to enable object instance segmentation as well
 		boolean INSTANCE_SEGMENTATION = true;
 
 		// Only object fromMemory confidence above the threshold are returned
 		float CONFIDENCE_THRESHOLD = 0.4f;
 
-		ObjectDetectionService detectionService =
-			new ObjectDetectionService(model, labels, CONFIDENCE_THRESHOLD, INSTANCE_SEGMENTATION, CACHE_TF_MODEL);
+		ObjectDetectionService detectionService = new ObjectDetectionService(model, labels, CONFIDENCE_THRESHOLD,
+				INSTANCE_SEGMENTATION, CACHE_TF_MODEL);
 
 		// You can use file:, http: or classpath: to provide the path to the input image.
 		byte[] image = GraphicsUtils.loadAsByteArray("classpath:/images/object-detection.jpg");
 
-		// Returns a list ObjectDetection domain classes to allow programmatic accesses to the detected objects's metadata
+		// Returns a list ObjectDetection domain classes to allow programmatic accesses to
+		// the detected objects's metadata
 		List<ObjectDetection> detectedObjects = detectionService.detect(image);
 
 		// Get JSON representation of the detected objects
 		String jsonObjectDetections = new JsonMapperFunction().apply(detectedObjects);
 		System.out.println(jsonObjectDetections);
 
-		// Draw the detected object metadata on top of the original image and store the result
+		// Draw the detected object metadata on top of the original image and store the
+		// result
 		byte[] annotatedImage = new ObjectDetectionImageAugmenter(INSTANCE_SEGMENTATION).apply(image, detectedObjects);
 		File projectDir = new File("functions/function/object-detection-function");
 		File output = new File(projectDir, "target/object-detection-segmentation-augmented.jpg");
 		IOUtils.write(annotatedImage, new FileOutputStream(output));
 		System.out.println("Created:" + output.getPath());
 	}
+
 }

function/spring-object-detection-function/src/test/java/org/springframework/cloud/fn/object/detection/examples/ExampleObjectDetection.java

@@ -37,31 +37,40 @@ public class ExampleObjectDetection {
 
 	public static void main(String[] args) throws IOException {
 
-		// You can download pre-trained models directly from the zoo: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
-		// Just use the notation <zoo model tar.gz url>#<name of the frozen model file name>
-		// For performance reasons you may consider downloading the model locally and use the file:/<path to my model> URI instead!
+		// You can download pre-trained models directly from the zoo:
+		// https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
+		// Just use the notation <zoo model tar.gz url>#<name of the frozen model file
+		// name>
+		// For performance reasons you may consider downloading the model locally and use
+		// the file:/<path to my model> URI instead!
 		String model = "https://download.tensorflow.org/models/object_detection/faster_rcnn_nas_coco_2018_01_28.tar.gz#frozen_inference_graph.pb";
-		//Resource model = resourceLoader.getResource("https://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_fgvc_2018_07_19.tar.gz#frozen_inference_graph.pb");
-		//Resource model = resourceLoader.getResource("https://download.tensorflow.org/models/object_detection/faster_rcnn_resnet50_fgvc_2018_07_19.tar.gz#frozen_inference_graph.pb");
+		// Resource model =
+		// resourceLoader.getResource("https://download.tensorflow.org/models/object_detection/faster_rcnn_resnet101_fgvc_2018_07_19.tar.gz#frozen_inference_graph.pb");
+		// Resource model =
+		// resourceLoader.getResource("https://download.tensorflow.org/models/object_detection/faster_rcnn_resnet50_fgvc_2018_07_19.tar.gz#frozen_inference_graph.pb");
 
 		// All labels for the pre-trained models are available at:
 		// https://github.com/tensorflow/models/tree/master/research/object_detection/data
 		// Use the labels applicable for the model.
-		// Also, for performance reasons you may consider to download the labels and load them from file: instead.
+		// Also, for performance reasons you may consider to download the labels and load
+		// them from file: instead.
 		String labels = "https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/data/mscoco_label_map.pbtxt";
-		//Resource labels = resourceLoader.getResource("https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/data/fgvc_2854_classes_label_map.pbtxt");
+		// Resource labels =
+		// resourceLoader.getResource("https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/data/fgvc_2854_classes_label_map.pbtxt");
 
-		// You can cache the TF model on the local file system to improve the bootstrap performance on consecutive runs!
+		// You can cache the TF model on the local file system to improve the bootstrap
+		// performance on consecutive runs!
 		boolean CACHE_TF_MODEL = true;
 
-		// For the pre-trained models fromMemory mask you can set the INSTANCE_SEGMENTATION to enable object instance segmentation as well
+		// For the pre-trained models fromMemory mask you can set the
+		// INSTANCE_SEGMENTATION to enable object instance segmentation as well
 		boolean NO_INSTANCE_SEGMENTATION = false;
 
 		// Only object fromMemory confidence above the threshold are returned
 		float CONFIDENCE_THRESHOLD = 0.4f;
 
-		ObjectDetectionService detectionService =
-				new ObjectDetectionService(model, labels, CONFIDENCE_THRESHOLD, NO_INSTANCE_SEGMENTATION, CACHE_TF_MODEL);
+		ObjectDetectionService detectionService = new ObjectDetectionService(model, labels, CONFIDENCE_THRESHOLD,
+				NO_INSTANCE_SEGMENTATION, CACHE_TF_MODEL);
 
 		// You can use file:, http: or classpath: to provide the path to the input image.
 		String inputImageUri = "classpath:/images/object-detection.jpg";
@@ -69,16 +78,21 @@ public class ExampleObjectDetection {
 
 			byte[] image = StreamUtils.copyToByteArray(is);
 
-			// Returns a list ObjectDetection domain classes to allow programmatic accesses to the detected objects's metadata
+			// Returns a list ObjectDetection domain classes to allow programmatic
+			// accesses to the detected objects's metadata
 			List<ObjectDetection> detectedObjects = detectionService.detect(image);
 
 			// Get JSON representation of the detected objects
 			String jsonObjectDetections = new JsonMapperFunction().apply(detectedObjects);
 			System.out.println(jsonObjectDetections);
 
-			// Draw the detected object metadata on top of the original image and store the result
-			byte[] annotatedImage = new ObjectDetectionImageAugmenter(NO_INSTANCE_SEGMENTATION).apply(image, detectedObjects);
-			IOUtils.write(annotatedImage, new FileOutputStream("./object-detection-function/target/object-detection-augmented.jpg"));
+			// Draw the detected object metadata on top of the original image and store
+			// the result
+			byte[] annotatedImage = new ObjectDetectionImageAugmenter(NO_INSTANCE_SEGMENTATION).apply(image,
+					detectedObjects);
+			IOUtils.write(annotatedImage,
+					new FileOutputStream("./object-detection-function/target/object-detection-augmented.jpg"));
 		}
 	}
+
 }

function/spring-object-detection-function/src/test/java/org/springframework/cloud/fn/object/detection/examples/SimpleExample.java

@@ -16,7 +16,6 @@
 
 package org.springframework.cloud.fn.object.detection.examples;
 
-
 import java.util.List;
 
 import org.springframework.cloud.fn.object.detection.ObjectDetectionService;
@@ -28,15 +27,30 @@ import org.springframework.cloud.fn.object.detection.domain.ObjectDetection;
 public class SimpleExample {
 
 	public static void main(String[] args) {
-		// Select a pre-trained model from the model zoo: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
-		// Just use the notation <model zoo url>#<name of the frozen model file in the zoo's tar.gz>
+		// Select a pre-trained model from the model zoo:
+		// https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md
+		// Just use the notation <model zoo url>#<name of the frozen model file in the
+		// zoo's tar.gz>
 		String model = "https://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_ppn_shared_box_predictor_300x300_coco14_sync_2018_07_03.tar.gz#frozen_inference_graph.pb";
 
-		// All labels for the pre-trained models are available at: https://github.com/tensorflow/models/tree/master/research/object_detection/data
+		// All labels for the pre-trained models are available at:
+		// https://github.com/tensorflow/models/tree/master/research/object_detection/data
 		String labels = "https://raw.githubusercontent.com/tensorflow/models/master/research/object_detection/data/mscoco_label_map.pbtxt";
 
-		ObjectDetectionService detectionService = new ObjectDetectionService(model, labels,
-				0.4f, // Only object fromMemory confidence above the threshold are returned. Confidence range is [0, 1].
+		ObjectDetectionService detectionService = new ObjectDetectionService(model, labels, 0.4f, // Only
+																									// object
+																									// fromMemory
+																									// confidence
+																									// above
+																									// the
+																									// threshold
+																									// are
+																									// returned.
+																									// Confidence
+																									// range
+																									// is
+																									// [0,
+																									// 1].
 				false, // No instance segmentation
 				true); // cache the TF model locally
 
@@ -44,4 +58,5 @@ public class SimpleExample {
 		List<ObjectDetection> detectedObjects = detectionService.detect("classpath:/images/object-detection.jpg");
 		detectedObjects.stream().map(o -> o.toString()).forEach(System.out::println);
 	}
+
 }

function/spring-payload-converter-function/src/main/java/functions/ByteArrayTextToString.java

@@ -24,7 +24,6 @@ import org.springframework.messaging.support.MessageBuilder;
 import org.springframework.util.MimeTypeUtils;
 
 /**
- *
  * @author Christian Tzolov
  */
 public class ByteArrayTextToString implements Function<Message<?>, Message<?>> {
@@ -35,17 +34,17 @@ public class ByteArrayTextToString implements Function<Message<?>, Message<?>> {
 		if (message.getPayload() instanceof byte[]) {
 			final MessageHeaders headers = message.getHeaders();
 			String contentType = headers.containsKey(MessageHeaders.CONTENT_TYPE)
-					? headers.get(MessageHeaders.CONTENT_TYPE).toString()
-					: MimeTypeUtils.APPLICATION_JSON_VALUE;
+					? headers.get(MessageHeaders.CONTENT_TYPE).toString() : MimeTypeUtils.APPLICATION_JSON_VALUE;
 
-			if (contentType.contains("text") || contentType.contains("json") || contentType.contains("x-spring-tuple")) {
+			if (contentType.contains("text") || contentType.contains("json")
+					|| contentType.contains("x-spring-tuple")) {
 				message = MessageBuilder.withPayload(new String(((byte[]) message.getPayload())))
-						.copyHeaders(message.getHeaders())
-						.build();
+					.copyHeaders(message.getHeaders())
+					.build();
 			}
 		}
 
 		return message;
 	}
-}
 
+}

function/spring-payload-converter-function/src/main/java/functions/JsonBytesToMap.java

@@ -29,12 +29,11 @@ import org.springframework.messaging.support.MessageBuilder;
 import org.springframework.util.MimeTypeUtils;
 
 /**
- * The {@link Function} to deserialize {@code byte[]} payload into a Map
- * if {@link MessageHeaders#CONTENT_TYPE} header is JSON.
- * Otherwise, the message is returned as is.
+ * The {@link Function} to deserialize {@code byte[]} payload into a Map if
+ * {@link MessageHeaders#CONTENT_TYPE} header is JSON. Otherwise, the message is returned
+ * as is.
  *
  * @author Artem Bilan
- *
  * @since 4.0
  */
 public class JsonBytesToMap implements Function<Message<?>, Message<?>> {
@@ -51,15 +50,13 @@ public class JsonBytesToMap implements Function<Message<?>, Message<?>> {
 	public Message<?> apply(Message<?> message) {
 		if (message.getPayload() instanceof byte[] payload) {
 			MessageHeaders headers = message.getHeaders();
-			String contentType =
-					headers.containsKey(MessageHeaders.CONTENT_TYPE)
-							? headers.get(MessageHeaders.CONTENT_TYPE).toString()
-							: MimeTypeUtils.APPLICATION_JSON_VALUE;
+			String contentType = headers.containsKey(MessageHeaders.CONTENT_TYPE)
+					? headers.get(MessageHeaders.CONTENT_TYPE).toString() : MimeTypeUtils.APPLICATION_JSON_VALUE;
 
 			if (contentType.contains("json")) {
 				message = MessageBuilder.withPayload(payloadToMapIfCan(payload))
-						.copyHeaders(message.getHeaders())
-						.build();
+					.copyHeaders(message.getHeaders())
+					.build();
 			}
 		}
 

function/spring-payload-converter-function/src/test/java/functions/ByteArrayTextToStringTests.java

@@ -32,6 +32,7 @@ import static org.assertj.core.api.Assertions.assertThat;
 public class ByteArrayTextToStringTests {
 
 	private static final String MESSAGE = "hello world";
+
 	private static Function<Message<?>, Message<?>> converter;
 
 	@BeforeAll

function/spring-semantic-segmentation-function/src/main/java/org/springframework/cloud/fn/semantic/segmentation/NativeImageUtils.java

@@ -43,11 +43,10 @@ public final class NativeImageUtils {
 	 * https://github.com/tensorflow/tensorflow/blob/r1.13/tensorflow/python/ops/image_ops_impl.py#L1536
 	 */
 	public static <T> Operand<T> grayscaleToRgb(Ops tf, Operand<T> images) {
-		ExpandDims<Integer> rank_1 = tf.expandDims(
-				tf.math.sub(tf.rank(images), tf.constant(1)),
-				tf.constant(0));
+		ExpandDims<Integer> rank_1 = tf.expandDims(tf.math.sub(tf.rank(images), tf.constant(1)), tf.constant(0));
 		// Create once 1D vector of the shape defined by the rank_1.
-		// E.g. for rank [2] will produce matrix [1, 1]. For [3] rank will produce a cube [1, 1, 1]
+		// E.g. for rank [2] will produce matrix [1, 1]. For [3] rank will produce a cube
+		// [1, 1, 1]
 		Add<Integer> ones = tf.math.add(tf.zeros(rank_1, Integer.class), tf.constant(1));
 		// Convert scalar 3 into 1D array [3]
 		ExpandDims<Integer> channelsAs1D = tf.expandDims(tf.constant(3), tf.constant(0));
@@ -59,49 +58,57 @@ public final class NativeImageUtils {
 	public static Operand<Float> normalizeMask(Ops tf, Operand<Float> mask, float newValue) {
 		// generate array representing the axis indexes.
 		// For example of tensor of rank K the axisRange is {0, 1, 2 ...K}
-		Range<Integer> axisRange = tf.range(tf.constant(0),  // from
+		Range<Integer> axisRange = tf.range(tf.constant(0), // from
 				tf.dtypes.cast(tf.rank(mask), Integer.class), // to
 				tf.constant(1)); // step
 
 		ReduceMax<Float> max = tf.reduceMax(mask, axisRange);
-		//Mul<Float> input2Float1 = tf.math.mul(tf.math.div(input2Float, max), tf.constant(1f));
+		// Mul<Float> input2Float1 = tf.math.mul(tf.math.div(input2Float, max),
+		// tf.constant(1f));
 		Mul<Float> normalizedMask = tf.math.mul(tf.math.div(mask, max), tf.constant(newValue));
 
 		return normalizedMask;
 	}
 
 	/**
-	 * Alpha Blending .
-	 * https://en.wikipedia.org/wiki/Alpha_compositing#Alpha_blending
+	 * Alpha Blending . https://en.wikipedia.org/wiki/Alpha_compositing#Alpha_blending
 	 */
-	public static Operand<Float> alphaBlending(Ops tf, Operand<Float> srcRgb, Operand<Float> dstRgb, Operand<Float> srcAlpha) {
+	public static Operand<Float> alphaBlending(Ops tf, Operand<Float> srcRgb, Operand<Float> dstRgb,
+			Operand<Float> srcAlpha) {
 		Sub<Float> alpha = tf.math.sub(tf.onesLike(srcRgb), srcAlpha);
 		Mul<Float> src = tf.math.mul(srcRgb, alpha);
 		Mul<Float> dst = tf.math.mul(dstRgb, tf.math.sub(tf.constant(1.0f), alpha));
 		Add<Float> out = tf.math.add(dst, src);
 
-		//Mul<Float> out = tf.math.mul(srcRgbNormalized, dstRgb);
-		//Squeeze<Float> squeeze = tf.withName("squeeze").squeeze(out, Squeeze.axis(Arrays.asList(0L)));
+		// Mul<Float> out = tf.math.mul(srcRgbNormalized, dstRgb);
+		// Squeeze<Float> squeeze = tf.withName("squeeze").squeeze(out,
+		// Squeeze.axis(Arrays.asList(0L)));
 
 		return out;
 	}
 
 	/**
-	 * The mask can contain label values larger than the list of colors provided in the color map.
-	 * To avoid out-of-index errors we will "normalize" the label values in the mask to MOD max-color-table-value.
+	 * The mask can contain label values larger than the list of colors provided in the
+	 * color map. To avoid out-of-index errors we will "normalize" the label values in the
+	 * mask to MOD max-color-table-value.
 	 * @param tf - tensorflow
-	 * @param colorTable Color map of shape [n, 3]. n is the count of label entries and 3 is the RGB color assigned
-	 *                   to that label.
+	 * @param colorTable Color map of shape [n, 3]. n is the count of label entries and 3
+	 * is the RGB color assigned to that label.
 	 * @param mask Mask of shape [h, w] containing label vales.
 	 * @return Mask of shape [h, w] fromMemory values normalized between [0, n]
 	 */
 	public static Operand<Long> normalizeMaskLabels(Ops tf, Operand<Integer> colorTable, Operand<Long> mask) {
-		// The mask can contain label values larger than the list of colors provided in the color map.
-		// To avoid out-of-index errors we will "normalize" the label values in the mask to MOD max-color-table-value.
+		// The mask can contain label values larger than the list of colors provided in
+		// the color map.
+		// To avoid out-of-index errors we will "normalize" the label values in the mask
+		// to MOD max-color-table-value.
 		Sub<Long> colorTableShape = tf.math.sub(tf.shape(colorTable, Long.class), tf.constant(1L));
-		// Color tables have shape [N, 3], where N is the count of label entries. Therefore the max label id is (N - 1).
+		// Color tables have shape [N, 3], where N is the count of label entries.
+		// Therefore the max label id is (N - 1).
 		Gather<Long> colorTableSize = tf.gather(colorTableShape, tf.constant(new int[] { 0 }), tf.constant(0));
-		// Normalize the label values in the mask so they don't exceed the max value in the color map.
+		// Normalize the label values in the mask so they don't exceed the max value in
+		// the color map.
 		return tf.math.mod(mask, colorTableSize);
 	}
+
 }

function/spring-semantic-segmentation-function/src/main/java/org/springframework/cloud/fn/semantic/segmentation/SegmentationColorMap.java

@@ -25,16 +25,17 @@ import org.springframework.core.io.DefaultResourceLoader;
 
 /**
  *
- * Visualizes the segmentation results via specified color map.
- * Color maps helping to visualize the semantic segmentation results for the different datasets.
+ * Visualizes the segmentation results via specified color map. Color maps helping to
+ * visualize the semantic segmentation results for the different datasets.
  *
- * Supported colormaps are:
- * - ADE20K (http://groups.csail.mit.edu/vision/datasets/ADE20K/).
- * - Cityscapes dataset (https://www.cityscapes-dataset.com).
- * - Mapillary Vistas (https://research.mapillary.com).
- * - PASCAL VOC 2012 (http://host.robots.ox.ac.uk/pascal/VOC/).
+ * Supported colormaps are: - ADE20K
+ * (http://groups.csail.mit.edu/vision/datasets/ADE20K/). - Cityscapes dataset
+ * (https://www.cityscapes-dataset.com). - Mapillary Vistas
+ * (https://research.mapillary.com). - PASCAL VOC 2012
+ * (http://host.robots.ox.ac.uk/pascal/VOC/).
  *
- * Based on: https://github.com/tensorflow/models/blob/master/research/deeplab/utils/get_dataset_colormap.py
+ * Based on:
+ * https://github.com/tensorflow/models/blob/master/research/deeplab/utils/get_dataset_colormap.py
  *
  * @author Christian Tzolov
  */
@@ -45,238 +46,51 @@ public final class SegmentationColorMap {
 	}
 
 	/** MAPILLARY_COLORMAP . */
-	public static final int[][] MAPILLARY_COLORMAP = new int[][] {
-			{ 165, 42, 42 },
-			{ 0, 192, 0 },
-			{ 196, 196, 196 },
-			{ 190, 153, 153 },
-			{ 180, 165, 180 },
-			{ 102, 102, 156 },
-			{ 102, 102, 156 },
-			{ 128, 64, 255 },
-			{ 140, 140, 200 },
-			{ 170, 170, 170 },
-			{ 250, 170, 160 },
-			{ 96, 96, 96 },
-			{ 230, 150, 140 },
-			{ 128, 64, 128 },
-			{ 110, 110, 110 },
-			{ 244, 35, 232 },
-			{ 150, 100, 100 },
-			{ 70, 70, 70 },
-			{ 150, 120, 90 },
-			{ 220, 20, 60 },
-			{ 255, 0, 0 },
-			{ 255, 0, 0 },
-			{ 255, 0, 0 },
-			{ 200, 128, 128 },
-			{ 255, 255, 255 },
-			{ 64, 170, 64 },
-			{ 128, 64, 64 },
-			{ 70, 130, 180 },
-			{ 255, 255, 255 },
-			{ 152, 251, 152 },
-			{ 107, 142, 35 },
-			{ 0, 170, 30 },
-			{ 255, 255, 128 },
-			{ 250, 0, 30 },
-			{ 0, 0, 0 },
-			{ 220, 220, 220 },
-			{ 170, 170, 170 },
-			{ 222, 40, 40 },
-			{ 100, 170, 30 },
-			{ 40, 40, 40 },
-			{ 33, 33, 33 },
-			{ 170, 170, 170 },
-			{ 0, 0, 142 },
-			{ 170, 170, 170 },
-			{ 210, 170, 100 },
-			{ 153, 153, 153 },
-			{ 128, 128, 128 },
-			{ 0, 0, 142 },
-			{ 250, 170, 30 },
-			{ 192, 192, 192 },
-			{ 220, 220, 0 },
-			{ 180, 165, 180 },
-			{ 119, 11, 32 },
-			{ 0, 0, 142 },
-			{ 0, 60, 100 },
-			{ 0, 0, 142 },
-			{ 0, 0, 90 },
-			{ 0, 0, 230 },
-			{ 0, 80, 100 },
-			{ 128, 64, 64 },
-			{ 0, 0, 110 },
-			{ 0, 0, 70 },
-			{ 0, 0, 192 },
-			{ 32, 32, 32 },
-			{ 0, 0, 0 },
-			{ 0, 0, 0 },
-	};
+	public static final int[][] MAPILLARY_COLORMAP = new int[][] { { 165, 42, 42 }, { 0, 192, 0 }, { 196, 196, 196 },
+			{ 190, 153, 153 }, { 180, 165, 180 }, { 102, 102, 156 }, { 102, 102, 156 }, { 128, 64, 255 },
+			{ 140, 140, 200 }, { 170, 170, 170 }, { 250, 170, 160 }, { 96, 96, 96 }, { 230, 150, 140 },
+			{ 128, 64, 128 }, { 110, 110, 110 }, { 244, 35, 232 }, { 150, 100, 100 }, { 70, 70, 70 }, { 150, 120, 90 },
+			{ 220, 20, 60 }, { 255, 0, 0 }, { 255, 0, 0 }, { 255, 0, 0 }, { 200, 128, 128 }, { 255, 255, 255 },
+			{ 64, 170, 64 }, { 128, 64, 64 }, { 70, 130, 180 }, { 255, 255, 255 }, { 152, 251, 152 }, { 107, 142, 35 },
+			{ 0, 170, 30 }, { 255, 255, 128 }, { 250, 0, 30 }, { 0, 0, 0 }, { 220, 220, 220 }, { 170, 170, 170 },
+			{ 222, 40, 40 }, { 100, 170, 30 }, { 40, 40, 40 }, { 33, 33, 33 }, { 170, 170, 170 }, { 0, 0, 142 },
+			{ 170, 170, 170 }, { 210, 170, 100 }, { 153, 153, 153 }, { 128, 128, 128 }, { 0, 0, 142 }, { 250, 170, 30 },
+			{ 192, 192, 192 }, { 220, 220, 0 }, { 180, 165, 180 }, { 119, 11, 32 }, { 0, 0, 142 }, { 0, 60, 100 },
+			{ 0, 0, 142 }, { 0, 0, 90 }, { 0, 0, 230 }, { 0, 80, 100 }, { 128, 64, 64 }, { 0, 0, 110 }, { 0, 0, 70 },
+			{ 0, 0, 192 }, { 32, 32, 32 }, { 0, 0, 0 }, { 0, 0, 0 }, };
 
 	/**
 	 * Label colormap used in ADE20K segmentation benchmark.
 	 */
-	public static final int[][] ADE20K_COLORMAP = new int[][] {
-			{ 0, 0, 0 },
-			{ 120, 120, 120 },
-			{ 180, 120, 120 },
-			{ 6, 230, 230 },
-			{ 80, 50, 50 },
-			{ 4, 200, 3 },
-			{ 120, 120, 80 },
-			{ 140, 140, 140 },
-			{ 204, 5, 255 },
-			{ 230, 230, 230 },
-			{ 4, 250, 7 },
-			{ 224, 5, 255 },
-			{ 235, 255, 7 },
-			{ 150, 5, 61 },
-			{ 120, 120, 70 },
-			{ 8, 255, 51 },
-			{ 255, 6, 82 },
-			{ 143, 255, 140 },
-			{ 204, 255, 4 },
-			{ 255, 51, 7 },
-			{ 204, 70, 3 },
-			{ 0, 102, 200 },
-			{ 61, 230, 250 },
-			{ 255, 6, 51 },
-			{ 11, 102, 255 },
-			{ 255, 7, 71 },
-			{ 255, 9, 224 },
-			{ 9, 7, 230 },
-			{ 220, 220, 220 },
-			{ 255, 9, 92 },
-			{ 112, 9, 255 },
-			{ 8, 255, 214 },
-			{ 7, 255, 224 },
-			{ 255, 184, 6 },
-			{ 10, 255, 71 },
-			{ 255, 41, 10 },
-			{ 7, 255, 255 },
-			{ 224, 255, 8 },
-			{ 102, 8, 255 },
-			{ 255, 61, 6 },
-			{ 255, 194, 7 },
-			{ 255, 122, 8 },
-			{ 0, 255, 20 },
-			{ 255, 8, 41 },
-			{ 255, 5, 153 },
-			{ 6, 51, 255 },
-			{ 235, 12, 255 },
-			{ 160, 150, 20 },
-			{ 0, 163, 255 },
-			{ 140, 140, 140 },
-			{ 250, 10, 15 },
-			{ 20, 255, 0 },
-			{ 31, 255, 0 },
-			{ 255, 31, 0 },
-			{ 255, 224, 0 },
-			{ 153, 255, 0 },
-			{ 0, 0, 255 },
-			{ 255, 71, 0 },
-			{ 0, 235, 255 },
-			{ 0, 173, 255 },
-			{ 31, 0, 255 },
-			{ 11, 200, 200 },
-			{ 255, 82, 0 },
-			{ 0, 255, 245 },
-			{ 0, 61, 255 },
-			{ 0, 255, 112 },
-			{ 0, 255, 133 },
-			{ 255, 0, 0 },
-			{ 255, 163, 0 },
-			{ 255, 102, 0 },
-			{ 194, 255, 0 },
-			{ 0, 143, 255 },
-			{ 51, 255, 0 },
-			{ 0, 82, 255 },
-			{ 0, 255, 41 },
-			{ 0, 255, 173 },
-			{ 10, 0, 255 },
-			{ 173, 255, 0 },
-			{ 0, 255, 153 },
-			{ 255, 92, 0 },
-			{ 255, 0, 255 },
-			{ 255, 0, 245 },
-			{ 255, 0, 102 },
-			{ 255, 173, 0 },
-			{ 255, 0, 20 },
-			{ 255, 184, 184 },
-			{ 0, 31, 255 },
-			{ 0, 255, 61 },
-			{ 0, 71, 255 },
-			{ 255, 0, 204 },
-			{ 0, 255, 194 },
-			{ 0, 255, 82 },
-			{ 0, 10, 255 },
-			{ 0, 112, 255 },
-			{ 51, 0, 255 },
-			{ 0, 194, 255 },
-			{ 0, 122, 255 },
-			{ 0, 255, 163 },
-			{ 255, 153, 0 },
-			{ 0, 255, 10 },
-			{ 255, 112, 0 },
-			{ 143, 255, 0 },
-			{ 82, 0, 255 },
-			{ 163, 255, 0 },
-			{ 255, 235, 0 },
-			{ 8, 184, 170 },
-			{ 133, 0, 255 },
-			{ 0, 255, 92 },
-			{ 184, 0, 255 },
-			{ 255, 0, 31 },
-			{ 0, 184, 255 },
-			{ 0, 214, 255 },
-			{ 255, 0, 112 },
-			{ 92, 255, 0 },
-			{ 0, 224, 255 },
-			{ 112, 224, 255 },
-			{ 70, 184, 160 },
-			{ 163, 0, 255 },
-			{ 153, 0, 255 },
-			{ 71, 255, 0 },
-			{ 255, 0, 163 },
-			{ 255, 204, 0 },
-			{ 255, 0, 143 },
-			{ 0, 255, 235 },
-			{ 133, 255, 0 },
-			{ 255, 0, 235 },
-			{ 245, 0, 255 },
-			{ 255, 0, 122 },
-			{ 255, 245, 0 },
-			{ 10, 190, 212 },
-			{ 214, 255, 0 },
-			{ 0, 204, 255 },
-			{ 20, 0, 255 },
-			{ 255, 255, 0 },
-			{ 0, 153, 255 },
-			{ 0, 41, 255 },
-			{ 0, 255, 204 },
-			{ 41, 0, 255 },
-			{ 41, 255, 0 },
-			{ 173, 0, 255 },
-			{ 0, 245, 255 },
-			{ 71, 0, 255 },
-			{ 122, 0, 255 },
-			{ 0, 255, 184 },
-			{ 0, 92, 255 },
-			{ 184, 255, 0 },
-			{ 0, 133, 255 },
-			{ 255, 214, 0 },
-			{ 25, 194, 194 },
-			{ 102, 255, 0 },
-			{ 92, 0, 255 },
-	};
+	public static final int[][] ADE20K_COLORMAP = new int[][] { { 0, 0, 0 }, { 120, 120, 120 }, { 180, 120, 120 },
+			{ 6, 230, 230 }, { 80, 50, 50 }, { 4, 200, 3 }, { 120, 120, 80 }, { 140, 140, 140 }, { 204, 5, 255 },
+			{ 230, 230, 230 }, { 4, 250, 7 }, { 224, 5, 255 }, { 235, 255, 7 }, { 150, 5, 61 }, { 120, 120, 70 },
+			{ 8, 255, 51 }, { 255, 6, 82 }, { 143, 255, 140 }, { 204, 255, 4 }, { 255, 51, 7 }, { 204, 70, 3 },
+			{ 0, 102, 200 }, { 61, 230, 250 }, { 255, 6, 51 }, { 11, 102, 255 }, { 255, 7, 71 }, { 255, 9, 224 },
+			{ 9, 7, 230 }, { 220, 220, 220 }, { 255, 9, 92 }, { 112, 9, 255 }, { 8, 255, 214 }, { 7, 255, 224 },
+			{ 255, 184, 6 }, { 10, 255, 71 }, { 255, 41, 10 }, { 7, 255, 255 }, { 224, 255, 8 }, { 102, 8, 255 },
+			{ 255, 61, 6 }, { 255, 194, 7 }, { 255, 122, 8 }, { 0, 255, 20 }, { 255, 8, 41 }, { 255, 5, 153 },
+			{ 6, 51, 255 }, { 235, 12, 255 }, { 160, 150, 20 }, { 0, 163, 255 }, { 140, 140, 140 }, { 250, 10, 15 },
+			{ 20, 255, 0 }, { 31, 255, 0 }, { 255, 31, 0 }, { 255, 224, 0 }, { 153, 255, 0 }, { 0, 0, 255 },
+			{ 255, 71, 0 }, { 0, 235, 255 }, { 0, 173, 255 }, { 31, 0, 255 }, { 11, 200, 200 }, { 255, 82, 0 },
+			{ 0, 255, 245 }, { 0, 61, 255 }, { 0, 255, 112 }, { 0, 255, 133 }, { 255, 0, 0 }, { 255, 163, 0 },
+			{ 255, 102, 0 }, { 194, 255, 0 }, { 0, 143, 255 }, { 51, 255, 0 }, { 0, 82, 255 }, { 0, 255, 41 },
+			{ 0, 255, 173 }, { 10, 0, 255 }, { 173, 255, 0 }, { 0, 255, 153 }, { 255, 92, 0 }, { 255, 0, 255 },
+			{ 255, 0, 245 }, { 255, 0, 102 }, { 255, 173, 0 }, { 255, 0, 20 }, { 255, 184, 184 }, { 0, 31, 255 },
+			{ 0, 255, 61 }, { 0, 71, 255 }, { 255, 0, 204 }, { 0, 255, 194 }, { 0, 255, 82 }, { 0, 10, 255 },
+			{ 0, 112, 255 }, { 51, 0, 255 }, { 0, 194, 255 }, { 0, 122, 255 }, { 0, 255, 163 }, { 255, 153, 0 },
+			{ 0, 255, 10 }, { 255, 112, 0 }, { 143, 255, 0 }, { 82, 0, 255 }, { 163, 255, 0 }, { 255, 235, 0 },
+			{ 8, 184, 170 }, { 133, 0, 255 }, { 0, 255, 92 }, { 184, 0, 255 }, { 255, 0, 31 }, { 0, 184, 255 },
+			{ 0, 214, 255 }, { 255, 0, 112 }, { 92, 255, 0 }, { 0, 224, 255 }, { 112, 224, 255 }, { 70, 184, 160 },
+			{ 163, 0, 255 }, { 153, 0, 255 }, { 71, 255, 0 }, { 255, 0, 163 }, { 255, 204, 0 }, { 255, 0, 143 },
+			{ 0, 255, 235 }, { 133, 255, 0 }, { 255, 0, 235 }, { 245, 0, 255 }, { 255, 0, 122 }, { 255, 245, 0 },
+			{ 10, 190, 212 }, { 214, 255, 0 }, { 0, 204, 255 }, { 20, 0, 255 }, { 255, 255, 0 }, { 0, 153, 255 },
+			{ 0, 41, 255 }, { 0, 255, 204 }, { 41, 0, 255 }, { 41, 255, 0 }, { 173, 0, 255 }, { 0, 245, 255 },
+			{ 71, 0, 255 }, { 122, 0, 255 }, { 0, 255, 184 }, { 0, 92, 255 }, { 184, 255, 0 }, { 0, 133, 255 },
+			{ 255, 214, 0 }, { 25, 194, 194 }, { 102, 255, 0 }, { 92, 0, 255 }, };
 
 	/** BLACK_WHITE_COLORMAP . */
-	public static int[][] BLACK_WHITE_COLORMAP = new int[][] {
-			{ 0, 0, 0 },
-			{ 127, 127, 127 },
-			{ 255, 255, 255 },
-	};
+	public static int[][] BLACK_WHITE_COLORMAP = new int[][] { { 0, 0, 0 }, { 127, 127, 127 }, { 255, 255, 255 }, };
 
 	/** CITYMAP_COLORMAP . */
 	public static final int[][] CITYMAP_COLORMAP = new int[255][3];
@@ -284,27 +98,10 @@ public final class SegmentationColorMap {
 	static {
 
 		// Initialize citymap
-		int[][] _CITYMAP_COLORMAP = new int[][] {
-				{ 128, 64, 128 },
-				{ 244, 35, 232 },
-				{ 70, 70, 70 },
-				{ 102, 102, 156 },
-				{ 190, 153, 153 },
-				{ 153, 153, 153 },
-				{ 250, 170, 30 },
-				{ 220, 220, 0 },
-				{ 107, 142, 35 },
-				{ 152, 251, 152 },
-				{ 70, 130, 180 },
-				{ 220, 20, 60 },
-				{ 255, 0, 0 },
-				{ 0, 0, 142 },
-				{ 0, 0, 70 },
-				{ 0, 60, 100 },
-				{ 0, 80, 100 },
-				{ 0, 0, 230 },
-				{ 119, 11, 32 }
-		};
+		int[][] _CITYMAP_COLORMAP = new int[][] { { 128, 64, 128 }, { 244, 35, 232 }, { 70, 70, 70 }, { 102, 102, 156 },
+				{ 190, 153, 153 }, { 153, 153, 153 }, { 250, 170, 30 }, { 220, 220, 0 }, { 107, 142, 35 },
+				{ 152, 251, 152 }, { 70, 130, 180 }, { 220, 20, 60 }, { 255, 0, 0 }, { 0, 0, 142 }, { 0, 0, 70 },
+				{ 0, 60, 100 }, { 0, 80, 100 }, { 0, 0, 230 }, { 119, 11, 32 } };
 
 		for (int i = 0; i < _CITYMAP_COLORMAP.length; i++) {
 			System.arraycopy(_CITYMAP_COLORMAP[i], 0, CITYMAP_COLORMAP[i], 0, _CITYMAP_COLORMAP[i].length);
@@ -323,8 +120,11 @@ public final class SegmentationColorMap {
 	}
 
 	public static class ColorMap {
+
 		private String name;
+
 		private String info;
+
 		private int[][] colormap;
 
 		public String getName() {
@@ -353,11 +153,10 @@ public final class SegmentationColorMap {
 
 		@Override
 		public String toString() {
-			return "ColorMap{" +
-					"name='" + name + '\'' +
-					"info='" + info + '\'' +
-					", colormap=" + Arrays.deepToString(colormap) +
-					'}';
+			return "ColorMap{" + "name='" + name + '\'' + "info='" + info + '\'' + ", colormap="
+					+ Arrays.deepToString(colormap) + '}';
 		}
+
 	}
+
 }

function/spring-semantic-segmentation-function/src/main/java/org/springframework/cloud/fn/semantic/segmentation/SemanticSegmentation.java

@@ -54,12 +54,19 @@ import org.springframework.core.io.DefaultResourceLoader;
 public class SemanticSegmentation implements AutoCloseable {
 
 	private static final long CHANNELS = 3;
+
 	private static final float REQUIRED_INPUT_IMAGE_SIZE = 513f;
+
 	private final GraphRunner imageNormalization;
+
 	private final GraphRunner semanticSegmentation;
+
 	private final GraphRunner maskImageEncoding;
+
 	private final GraphRunner alphaBlending;
+
 	private final Tensor<Integer> colorMapTensor;
+
 	private final Tensor<Float> maskTransparencyTensor;
 
 	@Override
@@ -75,95 +82,134 @@ public class SemanticSegmentation implements AutoCloseable {
 
 	public SemanticSegmentation(String modelUrl, int[][] colorMap, long[] labelFilter, float maskTransparency) {
 
-		this.imageNormalization = new GraphRunner("input_image", "resized_image")
-				.withGraphDefinition(tf -> {
-					Placeholder<String> input = tf.withName("input_image").placeholder(String.class);
-					ExtractJpegShape<Integer> imageShapeAndChannel = tf.image.extractJpegShape(input);
-					Gather<Integer> imageShape = tf.gather(imageShapeAndChannel, tf.constant(new int[] { 0, 1 }), tf.constant(0));
+		this.imageNormalization = new GraphRunner("input_image", "resized_image").withGraphDefinition(tf -> {
+			Placeholder<String> input = tf.withName("input_image").placeholder(String.class);
+			ExtractJpegShape<Integer> imageShapeAndChannel = tf.image.extractJpegShape(input);
+			Gather<Integer> imageShape = tf.gather(imageShapeAndChannel, tf.constant(new int[] { 0, 1 }),
+					tf.constant(0));
 
-					Cast<Float> maxSize = tf.dtypes.cast(tf.max(imageShape, tf.constant(0)), Float.class);
-					Div<Float> scale = tf.math.div(tf.constant(REQUIRED_INPUT_IMAGE_SIZE), maxSize);
-					Cast<Integer> newSize = tf.dtypes.cast(tf.math.mul(scale, tf.dtypes.cast(imageShape, Float.class)), Integer.class);
+			Cast<Float> maxSize = tf.dtypes.cast(tf.max(imageShape, tf.constant(0)), Float.class);
+			Div<Float> scale = tf.math.div(tf.constant(REQUIRED_INPUT_IMAGE_SIZE), maxSize);
+			Cast<Integer> newSize = tf.dtypes.cast(tf.math.mul(scale, tf.dtypes.cast(imageShape, Float.class)),
+					Integer.class);
 
-					final Operand<Float> decodedImage =
-							tf.dtypes.cast(tf.image.decodeJpeg(input, DecodeJpeg.channels(CHANNELS)), Float.class);
+			final Operand<Float> decodedImage = tf.dtypes
+				.cast(tf.image.decodeJpeg(input, DecodeJpeg.channels(CHANNELS)), Float.class);
 
-					final Operand<Float> resizedImageFloat =
-							tf.image.resizeBilinear(tf.expandDims(decodedImage, tf.constant(0)), newSize);
+			final Operand<Float> resizedImageFloat = tf.image
+				.resizeBilinear(tf.expandDims(decodedImage, tf.constant(0)), newSize);
 
-					tf.withName("resized_image").dtypes.cast(resizedImageFloat, UInt8.class);
-				});
+			tf.withName("resized_image").dtypes.cast(resizedImageFloat, UInt8.class);
+		});
 
 		this.semanticSegmentation = new GraphRunner("ImageTensor:0", "SemanticPredictions:0")
-				.withGraphDefinition(new ProtoBufGraphDefinition(new DefaultResourceLoader().getResource(modelUrl), true));
+			.withGraphDefinition(new ProtoBufGraphDefinition(new DefaultResourceLoader().getResource(modelUrl), true));
 
 		this.colorMapTensor = Tensor.create(colorMap).expect(Integer.class);
 
-		this.maskImageEncoding = new GraphRunner(Arrays.asList("color_map", "mask_pixels"), Arrays.asList("mask_png", "mask_rgb"))
-				.withGraphDefinition(tf -> {
-					Placeholder<Integer> colorTable = tf.withName("color_map").placeholder(Integer.class);
+		this.maskImageEncoding = new GraphRunner(Arrays.asList("color_map", "mask_pixels"),
+				Arrays.asList("mask_png", "mask_rgb"))
+			.withGraphDefinition(tf -> {
+				Placeholder<Integer> colorTable = tf.withName("color_map").placeholder(Integer.class);
 
-					Placeholder<Long> batchedMask = tf.withName("mask_pixels").placeholder(Long.class);
-					// Remove batch dimension
-					Squeeze<Long> mask = tf.squeeze(batchedMask, Squeeze.axis(Arrays.asList(0L)));
+				Placeholder<Long> batchedMask = tf.withName("mask_pixels").placeholder(Long.class);
+				// Remove batch dimension
+				Squeeze<Long> mask = tf.squeeze(batchedMask, Squeeze.axis(Arrays.asList(0L)));
 
-					Operand<Long> filteredMask = labelFilter(tf, mask, labelFilter);
+				Operand<Long> filteredMask = labelFilter(tf, mask, labelFilter);
 
-					// The mask can contain label values larger than the list of colors provided in the color map.
-					// To avoid out-of-index errors we will "normalize" the label values in the mask to MOD max-color-table-value.
-					Operand<Long> mask3 = NativeImageUtils.normalizeMaskLabels(tf, colorTable, filteredMask);
+				// The mask can contain label values larger than the list of colors
+				// provided in the color map.
+				// To avoid out-of-index errors we will "normalize" the label values in
+				// the mask to MOD max-color-table-value.
+				Operand<Long> mask3 = NativeImageUtils.normalizeMaskLabels(tf, colorTable, filteredMask);
 
-					Gather<Integer> maskRgb = tf.withName("mask_rgb").gather(colorTable, mask3, tf.constant(0));
+				Gather<Integer> maskRgb = tf.withName("mask_rgb").gather(colorTable, mask3, tf.constant(0));
 
-					Operand<String> png = tf.withName("mask_png").image.encodePng(tf.dtypes.cast(maskRgb, UInt8.class));
+				Operand<String> png = tf.withName("mask_png").image.encodePng(tf.dtypes.cast(maskRgb, UInt8.class));
 
-				});
+			});
 
 		this.maskTransparencyTensor = Tensor.create(maskTransparency).expect(Float.class);
 
-		this.alphaBlending = new GraphRunner(
-				Arrays.asList("input_image", "mask_image", "mask_transparency"), Arrays.asList("blended_png"))
-				.withGraphDefinition(tf -> {
-					// Input image [B, H, W, 3]
-					Cast<Float> inputImageRgb = tf.dtypes.cast(tf.withName("input_image").placeholder(UInt8.class), Float.class);
+		this.alphaBlending = new GraphRunner(Arrays.asList("input_image", "mask_image", "mask_transparency"),
+				Arrays.asList("blended_png"))
+			.withGraphDefinition(tf -> {
+				// Input image [B, H, W, 3]
+				Cast<Float> inputImageRgb = tf.dtypes.cast(tf.withName("input_image").placeholder(UInt8.class),
+						Float.class);
 
-					Placeholder<Integer> a = tf.withName("mask_image").placeholder(Integer.class);
-					Cast<Float> maskRgb = tf.dtypes.cast(a, Float.class);
+				Placeholder<Integer> a = tf.withName("mask_image").placeholder(Integer.class);
+				Cast<Float> maskRgb = tf.dtypes.cast(a, Float.class);
 
-					Squeeze<Float> inputImageRgb2 = tf.squeeze(inputImageRgb, Squeeze.axis(Arrays.asList(0L)));
+				Squeeze<Float> inputImageRgb2 = tf.squeeze(inputImageRgb, Squeeze.axis(Arrays.asList(0L)));
 
-					Placeholder<Float> maskTransparencyHolder = tf.withName("mask_transparency").placeholder(Float.class);
+				Placeholder<Float> maskTransparencyHolder = tf.withName("mask_transparency").placeholder(Float.class);
 
-					// Blend the transparent maskImage on top of the input image.
-					Operand<Float> blended = NativeImageUtils.alphaBlending(tf, maskRgb, inputImageRgb2, maskTransparencyHolder);
+				// Blend the transparent maskImage on top of the input image.
+				Operand<Float> blended = NativeImageUtils.alphaBlending(tf, maskRgb, inputImageRgb2,
+						maskTransparencyHolder);
 
-					// Cut
-					//Operand<Boolean> condition = tf.math.equal(a, tf.zerosLike(a));
-					//Operand<Float> blended = tf.where3(condition, tf.zerosLike(maskRgb), inputImageRgb2);
+				// Cut
+				// Operand<Boolean> condition = tf.math.equal(a, tf.zerosLike(a));
+				// Operand<Float> blended = tf.where3(condition, tf.zerosLike(maskRgb),
+				// inputImageRgb2);
 
-					// Encode PNG
-					tf.withName("blended_png").image.encodePng(tf.dtypes.cast(blended, UInt8.class));
+				// Encode PNG
+				tf.withName("blended_png").image.encodePng(tf.dtypes.cast(blended, UInt8.class));
 
-				});
+			});
 	}
 
 	public byte[] blendMask(byte[] image) {
 		try (Tensor inputTensor = Tensor.create(image); GraphRunnerMemory memory = new GraphRunnerMemory()) {
 
-			Map<String, Tensor<?>> blendedTensors =
-					this.imageNormalization.andThen(memory)                         // (input_image) -> (resized_image)   and memorize (resized_image)
-							.andThen(this.semanticSegmentation).andThen(memory)     // (ImageTensor:0) -> (SemanticPredictions:0) and memorize (SemanticPredictions:0)
-							.andThen(Functions.rename("SemanticPredictions:0", "mask_pixels")) // (SemanticPredictions:0) -> (mask_pixels)
-							.andThen(Functions.enrichWith("color_map", this.colorMapTensor))  // (mask_pixels) -> (mask_pixels, color_map)
-							.andThen(this.maskImageEncoding).andThen(memory)        // (color_map, mask_pixels) -> (mask_png, mask_rgb) and memorize (mask_png, mask_rgb)
-							.andThen(Functions.enrichFromMemory(
-									memory, "resized_image"))     // (mask_png, mask_rgb) -> (mask_png, mask_rgb, resized_image), e.g. join the normalizedImageTensor
-							.andThen(Functions.rename(
-									"resized_image", "input_image",
-									"mask_rgb", "mask_image"))                     // (mask_png, mask_rgb, resized_image) -> (mask_image, input_image)
-							.andThen(Functions.enrichWith("mask_transparency", this.maskTransparencyTensor)) // (mask_image, input_image) ->  (mask_image, input_image, mask_transparency)
-							.andThen(this.alphaBlending).andThen(memory)           // (mask_image, input_image, mask_transparency) -> (blended_png)
-							.apply(Collections.singletonMap("input_image", inputTensor)); // () -> (input_image)
+			Map<String, Tensor<?>> blendedTensors = this.imageNormalization.andThen(memory) // (input_image)
+																							// ->
+																							// (resized_image)
+																							// and
+																							// memorize
+																							// (resized_image)
+				.andThen(this.semanticSegmentation)
+				.andThen(memory) // (ImageTensor:0) -> (SemanticPredictions:0) and
+									// memorize (SemanticPredictions:0)
+				.andThen(Functions.rename("SemanticPredictions:0", "mask_pixels")) // (SemanticPredictions:0)
+																					// ->
+																					// (mask_pixels)
+				.andThen(Functions.enrichWith("color_map", this.colorMapTensor)) // (mask_pixels)
+																					// ->
+																					// (mask_pixels,
+																					// color_map)
+				.andThen(this.maskImageEncoding)
+				.andThen(memory) // (color_map, mask_pixels) -> (mask_png, mask_rgb) and
+									// memorize (mask_png, mask_rgb)
+				.andThen(Functions.enrichFromMemory(memory, "resized_image")) // (mask_png,
+																				// mask_rgb)
+																				// ->
+																				// (mask_png,
+																				// mask_rgb,
+																				// resized_image),
+																				// e.g.
+																				// join
+																				// the
+																				// normalizedImageTensor
+				.andThen(Functions.rename("resized_image", "input_image", "mask_rgb", "mask_image")) // (mask_png,
+																										// mask_rgb,
+																										// resized_image)
+																										// ->
+																										// (mask_image,
+																										// input_image)
+				.andThen(Functions.enrichWith("mask_transparency", this.maskTransparencyTensor)) // (mask_image,
+																									// input_image)
+																									// ->
+																									// (mask_image,
+																									// input_image,
+																									// mask_transparency)
+				.andThen(this.alphaBlending)
+				.andThen(memory) // (mask_image, input_image, mask_transparency) ->
+									// (blended_png)
+				.apply(Collections.singletonMap("input_image", inputTensor)); // () ->
+																				// (input_image)
 
 			byte[] blendedImage = blendedTensors.get("blended_png").bytesValue();
 
@@ -176,15 +222,21 @@ public class SemanticSegmentation implements AutoCloseable {
 	public long[][] maskPixels(byte[] image) {
 		try (Tensor inputTensor = Tensor.create(image); GraphRunnerMemory memory = new GraphRunnerMemory()) {
 
-			return this.imageNormalization.andThen(memory)                       // (input_image) -> (resized_image)   and memorize (resized_image)
-					.andThen(this.semanticSegmentation).andThen(memory)          // (ImageTensor:0) -> (SemanticPredictions:0) and memorize (SemanticPredictions:0)
-					.andThen(tensorMap -> {
-						Tensor<?> maskTensor = tensorMap.get("SemanticPredictions:0");
-						int width = (int) maskTensor.shape()[1];
-						int height = (int) maskTensor.shape()[2];
-						return maskTensor.copyTo(new long[1][width][height])[0]; // 1 == batch size
-					})
-					.apply(Collections.singletonMap("input_image", inputTensor)); // () -> (input_image)
+			return this.imageNormalization.andThen(memory) // (input_image) ->
+															// (resized_image) and
+															// memorize (resized_image)
+				.andThen(this.semanticSegmentation)
+				.andThen(memory) // (ImageTensor:0) -> (SemanticPredictions:0) and
+									// memorize (SemanticPredictions:0)
+				.andThen(tensorMap -> {
+					Tensor<?> maskTensor = tensorMap.get("SemanticPredictions:0");
+					int width = (int) maskTensor.shape()[1];
+					int height = (int) maskTensor.shape()[2];
+					return maskTensor.copyTo(new long[1][width][height])[0]; // 1 == batch
+																				// size
+				})
+				.apply(Collections.singletonMap("input_image", inputTensor)); // () ->
+																				// (input_image)
 		}
 	}
 
@@ -192,13 +244,25 @@ public class SemanticSegmentation implements AutoCloseable {
 
 		try (Tensor inputTensor = Tensor.create(image); GraphRunnerMemory memory = new GraphRunnerMemory()) {
 
-			return this.imageNormalization.andThen(memory)                        // (input_image) -> (resized_image)   and memorize (resized_image)
-					.andThen(this.semanticSegmentation).andThen(memory)           // (ImageTensor:0) -> (SemanticPredictions:0) and memorize (SemanticPredictions:0)
-					.andThen(Functions.rename("SemanticPredictions:0", "mask_pixels")) // (SemanticPredictions:0) -> (mask_pixels)
-					.andThen(Functions.enrichWith("color_map", this.colorMapTensor))  // (mask_pixels) -> (mask_pixels, color_map)
-					.andThen(this.maskImageEncoding).andThen(memory)              // (color_map, mask_pixels) -> (mask_png, mask_rgb) and memorize (mask_png, mask_rgb)
-					.andThen(tensorMap -> tensorMap.get("mask_png").bytesValue())
-					.apply(Collections.singletonMap("input_image", inputTensor)); // () -> (input_image)
+			return this.imageNormalization.andThen(memory) // (input_image) ->
+															// (resized_image) and
+															// memorize (resized_image)
+				.andThen(this.semanticSegmentation)
+				.andThen(memory) // (ImageTensor:0) -> (SemanticPredictions:0) and
+									// memorize (SemanticPredictions:0)
+				.andThen(Functions.rename("SemanticPredictions:0", "mask_pixels")) // (SemanticPredictions:0)
+																					// ->
+																					// (mask_pixels)
+				.andThen(Functions.enrichWith("color_map", this.colorMapTensor)) // (mask_pixels)
+																					// ->
+																					// (mask_pixels,
+																					// color_map)
+				.andThen(this.maskImageEncoding)
+				.andThen(memory) // (color_map, mask_pixels) -> (mask_png, mask_rgb) and
+									// memorize (mask_png, mask_rgb)
+				.andThen(tensorMap -> tensorMap.get("mask_png").bytesValue())
+				.apply(Collections.singletonMap("input_image", inputTensor)); // () ->
+																				// (input_image)
 		}
 	}
 
@@ -222,8 +286,7 @@ public class SemanticSegmentation implements AutoCloseable {
 
 		try (SemanticSegmentation segmentationService = new SemanticSegmentation(
 				"https://download.tensorflow.org/models/deeplabv3_mnv2_cityscapes_train_2018_02_05.tar.gz#frozen_inference_graph.pb",
-				SegmentationColorMap.loadColorMap("classpath:/colormap/citymap_colormap.json"), null, 0.45f)
-		) {
+				SegmentationColorMap.loadColorMap("classpath:/colormap/citymap_colormap.json"), null, 0.45f)) {
 			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/amsterdam-cityscape1.jpg");
 
 			// 1. Mask pixels
@@ -244,8 +307,7 @@ public class SemanticSegmentation implements AutoCloseable {
 
 		try (SemanticSegmentation segmentationService = new SemanticSegmentation(
 				"https://download.tensorflow.org/models/deeplabv3_xception_ade20k_train_2018_05_29.tar.gz#frozen_inference_graph.pb",
-				SegmentationColorMap.loadColorMap("classpath:/colormap/ade20k_colormap.json"), null, 0.45f)
-		) {
+				SegmentationColorMap.loadColorMap("classpath:/colormap/ade20k_colormap.json"), null, 0.45f)) {
 			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/interior.jpg");
 
 			// 1. Mask pixels
@@ -264,8 +326,7 @@ public class SemanticSegmentation implements AutoCloseable {
 
 		try (SemanticSegmentation segmentationService = new SemanticSegmentation(
 				"https://download.tensorflow.org/models/deeplabv3_mnv2_pascal_trainval_2018_01_29.tar.gz#frozen_inference_graph.pb",
-				SegmentationColorMap.loadColorMap("classpath:/colormap/black_white_colormap.json"), null, 0.45f)
-		) {
+				SegmentationColorMap.loadColorMap("classpath:/colormap/black_white_colormap.json"), null, 0.45f)) {
 			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/VikiMaxiAdi.jpg");
 
 			// 1. Mask pixels
@@ -283,4 +344,5 @@ public class SemanticSegmentation implements AutoCloseable {
 		}
 
 	}
+
 }

function/spring-semantic-segmentation-function/src/main/java/org/springframework/cloud/fn/semantic/segmentation/attic/SemanticSegmentationUtils.java

@@ -44,8 +44,8 @@ import static java.awt.image.BufferedImage.TYPE_3BYTE_BGR;
 
 /**
  *
- * Semantic image segmentation - the task of assigning a semantic label, such as "road", "sky", "person", "dog", to
- * every pixel in an image.
+ * Semantic image segmentation - the task of assigning a semantic label, such as "road",
+ * "sky", "person", "dog", to every pixel in an image.
  *
  * https://ai.googleblog.com/2018/03/semantic-image-segmentation-with.html
  * https://github.com/tensorflow/models/blob/master/research/deeplab/g3doc/model_zoo.md
@@ -65,11 +65,14 @@ public class SemanticSegmentationUtils {
 
 	/** INPUT_TENSOR_NAME . */
 	public static final String INPUT_TENSOR_NAME = "ImageTensor:0";
+
 	/** OUTPUT_TENSOR_NAME . */
 	public static final String OUTPUT_TENSOR_NAME = "SemanticPredictions:0";
 
 	private static final int BATCH_SIZE = 1;
+
 	private static final long CHANNELS = 3;
+
 	private static final int REQUIRED_INPUT_IMAGE_SIZE = 513;
 
 	public static BufferedImage scaledImage(String imagePath) {
@@ -100,9 +103,11 @@ public class SemanticSegmentationUtils {
 		int newHeight = (int) (originalImage.getHeight() * scale);
 
 		Image tmpImage = originalImage.getScaledInstance(newWidth, newHeight, Image.SCALE_DEFAULT);
-		//BufferedImage resizedImage = new BufferedImage(newWidth, newHeight, TYPE_INT_BGR);
+		// BufferedImage resizedImage = new BufferedImage(newWidth, newHeight,
+		// TYPE_INT_BGR);
 		BufferedImage resizedImage = new BufferedImage(newWidth, newHeight, TYPE_3BYTE_BGR);
-		//BufferedImage resizedImage = new BufferedImage(newWidth, newHeight, originalImage.getType());
+		// BufferedImage resizedImage = new BufferedImage(newWidth, newHeight,
+		// originalImage.getType());
 
 		Graphics2D g2d = resizedImage.createGraphics();
 		g2d.drawImage(tmpImage, 0, 0, null);
@@ -125,7 +130,8 @@ public class SemanticSegmentationUtils {
 		// ImageIO.read produces BGR-encoded images, while the model expects RGB.
 		byte[] data = bgrToRgb(toBytes(scaledImage));
 
-		// Expand dimensions since the model expects images to have shape: [1, None, None, 3]
+		// Expand dimensions since the model expects images to have shape: [1, None, None,
+		// 3]
 		long[] shape = new long[] { BATCH_SIZE, scaledImage.getHeight(), scaledImage.getWidth(), CHANNELS };
 
 		return Tensor.create(UInt8.class, shape, ByteBuffer.wrap(data));
@@ -201,7 +207,8 @@ public class SemanticSegmentationUtils {
 
 	public String serializeToJson(int[][] pixels) {
 		String masksBase64 = Base64.getEncoder().encodeToString(toBytes(pixels));
-		return String.format("{ \"columns\":%d, \"rows\":%d, \"masks\":\"%s\"}", pixels.length, pixels[0].length, masksBase64);
+		return String.format("{ \"columns\":%d, \"rows\":%d, \"masks\":\"%s\"}", pixels.length, pixels[0].length,
+				masksBase64);
 	}
 
 	public int[][] deserializeToMasks(String json) throws IOException {
@@ -221,7 +228,7 @@ public class SemanticSegmentationUtils {
 				b[bi + 0] = (byte) (i >> 24);
 				b[bi + 1] = (byte) (i >> 16);
 				b[bi + 2] = (byte) (i >> 8);
-				b[bi + 3] = (byte) (i /*>> 0*/);
+				b[bi + 3] = (byte) (i /* >> 0 */);
 				bi = bi + 4;
 			}
 		}
@@ -233,10 +240,7 @@ public class SemanticSegmentationUtils {
 		int bi = 0;
 		for (int i = 0; i < ic; i++) {
 			for (int j = 0; j < jc; j++) {
-				intResult[i][j] = (b[bi] << 24) +
-						(b[bi + 1] << 16) +
-						(b[bi + 2] << 8) +
-						b[bi + 3];
+				intResult[i][j] = (b[bi] << 24) + (b[bi + 1] << 16) + (b[bi + 2] << 8) + b[bi + 3];
 				bi = bi + 4;
 			}
 		}
@@ -246,14 +250,16 @@ public class SemanticSegmentationUtils {
 	public static void main(String[] args) throws IOException {
 
 		// PASCAL VOC 2012
-		//String tensorflowModelLocation = "file:/Users/ctzolov/Downloads/deeplabv3_mnv2_pascal_train_aug/frozen_inference_graph.pb";
-		//String imagePath = "classpath:/images/VikiMaxiAdi.jpg";
+		// String tensorflowModelLocation =
+		// "file:/Users/ctzolov/Downloads/deeplabv3_mnv2_pascal_train_aug/frozen_inference_graph.pb";
+		// String imagePath = "classpath:/images/VikiMaxiAdi.jpg";
 
 		// CITYSCAPE
-		//String tensorflowModelLocation = "file:/Users/ctzolov/Downloads/deeplabv3_mnv2_cityscapes_train/frozen_inference_graph.pb";
-		//String imagePath = "classpath:/images/amsterdam-cityscape1.jpg";
-		//String imagePath = "classpath:/images/amsterdam-channel.jpg";
-		//String imagePath = "classpath:/images/landsmeer.png";
+		// String tensorflowModelLocation =
+		// "file:/Users/ctzolov/Downloads/deeplabv3_mnv2_cityscapes_train/frozen_inference_graph.pb";
+		// String imagePath = "classpath:/images/amsterdam-cityscape1.jpg";
+		// String imagePath = "classpath:/images/amsterdam-channel.jpg";
+		// String imagePath = "classpath:/images/landsmeer.png";
 
 		// ADE20K
 		String tensorflowModelLocation = "file:/Users/ctzolov/Downloads/deeplabv3_xception_ade20k_train/frozen_inference_graph.pb";
@@ -261,7 +267,8 @@ public class SemanticSegmentationUtils {
 
 		BufferedImage inputImage = ImageIO.read(new DefaultResourceLoader().getResource(imagePath).getInputStream());
 
-		TensorFlowService tf = new TensorFlowService(new DefaultResourceLoader().getResource(tensorflowModelLocation), Arrays.asList(OUTPUT_TENSOR_NAME));
+		TensorFlowService tf = new TensorFlowService(new DefaultResourceLoader().getResource(tensorflowModelLocation),
+				Arrays.asList(OUTPUT_TENSOR_NAME));
 
 		SemanticSegmentationUtils segmentationService = new SemanticSegmentationUtils();
 
@@ -275,15 +282,24 @@ public class SemanticSegmentationUtils {
 
 		int height = (int) maskPixelsTensor.shape()[1];
 		int width = (int) maskPixelsTensor.shape()[2];
-		long[][] maskPixels = maskPixelsTensor.copyTo(new long[BATCH_SIZE][height][width])[0]; // take 0 because the batch size is 1.
+		long[][] maskPixels = maskPixelsTensor.copyTo(new long[BATCH_SIZE][height][width])[0]; // take
+																								// 0
+																								// because
+																								// the
+																								// batch
+																								// size
+																								// is
+																								// 1.
 
 		int[][] maskPixelsInt = segmentationService.toIntArray(maskPixels);
 
-		BufferedImage maskImage = segmentationService.createMaskImage(maskPixelsInt, scaledImage.getWidth(), scaledImage.getHeight(), 0.35);
+		BufferedImage maskImage = segmentationService.createMaskImage(maskPixelsInt, scaledImage.getWidth(),
+				scaledImage.getHeight(), 0.35);
 
 		BufferedImage blended = segmentationService.blendMask(maskImage, scaledImage);
 
 		ImageIO.write(maskImage, "png", new File("./semantic-segmentation/target/java2Dmask.jpg"));
 		ImageIO.write(blended, "png", new File("./semantic-segmentation/target/java2Dblended.jpg"));
 	}
+
 }

function/spring-spel-function/src/main/java/org/springframework/cloud/fn/spel/SpelFunctionConfiguration.java

@@ -40,8 +40,8 @@ public class SpelFunctionConfiguration {
 	public ExpressionEvaluatingTransformer expressionEvaluatingTransformer(
 			SpelFunctionProperties spelFunctionProperties) {
 
-		return new ExpressionEvaluatingTransformer(new SpelExpressionParser()
-				.parseExpression(spelFunctionProperties.getExpression()));
+		return new ExpressionEvaluatingTransformer(
+				new SpelExpressionParser().parseExpression(spelFunctionProperties.getExpression()));
 	}
 
 }

function/spring-spel-function/src/test/java/org/springframework/cloud/fn/spel/SpelFunctionApplicationTests.java

@@ -48,7 +48,8 @@ public class SpelFunctionApplicationTests {
 	@Test
 	public void testJson() {
 		Message<?> message = MessageBuilder.withPayload("{\"foo\":\"bar\"}")
-				.setHeader(MessageHeaders.CONTENT_TYPE, MimeTypeUtils.APPLICATION_JSON).build();
+			.setHeader(MessageHeaders.CONTENT_TYPE, MimeTypeUtils.APPLICATION_JSON)
+			.build();
 		final Message<?> transformed = this.transformer.apply(message);
 		assertThat(transformed.getPayload()).isEqualTo("{\"FOO\":\"BAR\"}");
 	}
@@ -57,4 +58,5 @@ public class SpelFunctionApplicationTests {
 	static class SpelFunctionTestApplication {
 
 	}
+
 }

function/spring-splitter-function/src/main/java/org/springframework/cloud/fn/splitter/SplitterFunctionConfiguration.java

@@ -60,8 +60,7 @@ public class SplitterFunctionConfiguration {
 	@ConditionalOnProperty(prefix = "splitter", name = "expression")
 	public AbstractMessageSplitter expressionSplitter(SplitterFunctionProperties splitterFunctionProperties) {
 		return new ExpressionEvaluatingSplitter(
-				new SpelExpressionParser()
-						.parseExpression(splitterFunctionProperties.getExpression()));
+				new SpelExpressionParser().parseExpression(splitterFunctionProperties.getExpression()));
 	}
 
 	@Bean
@@ -96,10 +95,12 @@ public class SplitterFunctionConfiguration {
 
 		@ConditionalOnProperty(prefix = "splitter", name = "charset")
 		static class Charset {
+
 		}
 
 		@ConditionalOnProperty(prefix = "splitter", name = "fileMarkers")
 		static class FileMarkers {
+
 		}
 
 	}

function/spring-splitter-function/src/main/java/org/springframework/cloud/fn/splitter/SplitterFunctionProperties.java

@@ -37,33 +37,29 @@ public class SplitterFunctionProperties {
 	private String expression;
 
 	/**
-	 * When expression is null, delimiters to use when tokenizing
-	 * {@link String} payloads.
+	 * When expression is null, delimiters to use when tokenizing {@link String} payloads.
 	 */
 	private String delimiters;
 
 	/**
-	 * Set to true or false to use a {@code FileSplitter} (to split
-	 * text-based files by line) that includes
-	 * (or not) beginning/end of file markers.
+	 * Set to true or false to use a {@code FileSplitter} (to split text-based files by
+	 * line) that includes (or not) beginning/end of file markers.
 	 */
 	private Boolean fileMarkers;
 
 	/**
-	 * When 'fileMarkers == true', specify if they should be produced
-	 * as FileSplitter.FileMarker objects or JSON.
+	 * When 'fileMarkers == true', specify if they should be produced as
+	 * FileSplitter.FileMarker objects or JSON.
 	 */
 	private boolean markersJson = true;
 
 	/**
-	 * The charset to use when converting bytes in text-based files
-	 * to String.
+	 * The charset to use when converting bytes in text-based files to String.
 	 */
 	private String charset;
 
 	/**
-	 * Add correlation/sequence information in headers to facilitate later
-	 * aggregation.
+	 * Add correlation/sequence information in headers to facilitate later aggregation.
 	 */
 	private boolean applySequence = true;
 
@@ -122,7 +118,8 @@ public class SplitterFunctionProperties {
 
 	@AssertTrue(message = "File properties are not allowed when an 'expression' or 'delimiters' property is provided")
 	public boolean isFilePropsAllowed() {
-		return !(this.expression != null || this.delimiters != null) || this.fileMarkers == null && this.charset == null;
+		return !(this.expression != null || this.delimiters != null)
+				|| this.fileMarkers == null && this.charset == null;
 	}
 
 }

function/spring-splitter-function/src/test/java/org/springframework/cloud/fn/splitter/SplitterFunctionApplicationTests.java

@@ -45,5 +45,7 @@ public class SplitterFunctionApplicationTests {
 
 	@SpringBootApplication
 	static class SplitterFunctionTestApplication {
+
 	}
+
 }

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/CommandLineArgumentsMessageMapper.java

@@ -21,4 +21,5 @@ import java.util.Collection;
 import org.springframework.integration.handler.MessageProcessor;
 
 public interface CommandLineArgumentsMessageMapper extends MessageProcessor<Collection<String>> {
+
 }

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/KeyValueListParser.java

@@ -23,7 +23,8 @@ import java.util.Map;
 import org.springframework.util.StringUtils;
 
 /**
- * Parses a comma delimited list of key value pairs in which the values can contain commas as well.
+ * Parses a comma delimited list of key value pairs in which the values can contain commas
+ * as well.
  *
  * @author Chris Schaeffer
  * @author David Turanski
@@ -63,4 +64,5 @@ abstract class KeyValueListParser {
 			properties.put(pair.substring(0, firstEquals).trim(), pair.substring(firstEquals + 1).trim());
 		}
 	}
+
 }

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/TaskLaunchRequest.java

@@ -25,6 +25,7 @@ import java.util.Map;
 import com.fasterxml.jackson.annotation.JsonProperty;
 
 public class TaskLaunchRequest {
+
 	@JsonProperty("args")
 	private List<String> commandlineArguments = new ArrayList<>();
 
@@ -62,4 +63,5 @@ public class TaskLaunchRequest {
 		this.commandlineArguments.addAll(args);
 		return this;
 	}
+
 }

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/TaskLaunchRequestFunctionConfiguration.java

@@ -36,13 +36,17 @@ import org.springframework.messaging.Message;
 import org.springframework.util.StringUtils;
 
 /**
- * Configuration for a {@link TaskLaunchRequestFunction}, provided as a common function that can be composed with other Suppliers or
- * Functions to transform any {@link Message} to a {@link TaskLaunchRequest} which may be used as input to the {@code TaskLauncherFunction} to launch a task.
+ * Configuration for a {@link TaskLaunchRequestFunction}, provided as a common function
+ * that can be composed with other Suppliers or Functions to transform any {@link Message}
+ * to a {@link TaskLaunchRequest} which may be used as input to the
+ * {@code TaskLauncherFunction} to launch a task.
  *
- * Command line arguments used by the task, as well as the task name itself may be statically configured or extracted from
- * the message contents, using SpEL. See {@link TaskLaunchRequestFunctionProperties} for details.
+ * Command line arguments used by the task, as well as the task name itself may be
+ * statically configured or extracted from the message contents, using SpEL. See
+ * {@link TaskLaunchRequestFunctionProperties} for details.
  *
- * It is also possible to provide your own implementations of {@link CommandLineArgumentsMessageMapper} and {@link TaskNameMessageMapper}.
+ * It is also possible to provide your own implementations of
+ * {@link CommandLineArgumentsMessageMapper} and {@link TaskNameMessageMapper}.
  *
  * @author David Turanski
  **/
@@ -58,9 +62,8 @@ public class TaskLaunchRequestFunctionConfiguration {
 	/**
 	 * A {@link java.util.function.Function} to transform a {@link Message} payload to a
 	 * {@link TaskLaunchRequest}.
-	 *
-	 * @param taskLaunchRequestMessageProcessor a {@link TaskLaunchRequestMessageProcessor}.
-	 *
+	 * @param taskLaunchRequestMessageProcessor a
+	 * {@link TaskLaunchRequestMessageProcessor}.
 	 * @return a {@code TaskLaunchRequest} Message.
 	 */
 	@Bean(name = TASK_LAUNCH_REQUEST_FUNCTION_NAME)
@@ -78,10 +81,8 @@ public class TaskLaunchRequestFunctionConfiguration {
 	@SuppressWarnings("SpringJavaInjectionPointsAutowiringInspection")
 	@Bean
 	public TaskLaunchRequestMessageProcessor taskLaunchRequestMessageProcessor(
-			TaskLaunchRequestSupplier taskLaunchRequestInitializer,
-			TaskLaunchRequestFunctionProperties properties,
-			EvaluationContext evaluationContext,
-			@Nullable TaskNameMessageMapper taskNameMessageMapper,
+			TaskLaunchRequestSupplier taskLaunchRequestInitializer, TaskLaunchRequestFunctionProperties properties,
+			EvaluationContext evaluationContext, @Nullable TaskNameMessageMapper taskNameMessageMapper,
 			@Nullable CommandLineArgumentsMessageMapper commandLineArgumentsMessageMapper) {
 
 		if (taskNameMessageMapper == null) {
@@ -92,8 +93,7 @@ public class TaskLaunchRequestFunctionConfiguration {
 			commandLineArgumentsMessageMapper = commandLineArgumentsMessageMapper(properties, evaluationContext);
 		}
 
-		return new TaskLaunchRequestMessageProcessor(taskLaunchRequestInitializer,
-				taskNameMessageMapper,
+		return new TaskLaunchRequestMessageProcessor(taskLaunchRequestInitializer, taskNameMessageMapper,
 				commandLineArgumentsMessageMapper);
 	}
 
@@ -103,11 +103,11 @@ public class TaskLaunchRequestFunctionConfiguration {
 	}
 
 	private TaskNameMessageMapper taskNameMessageMapper(TaskLaunchRequestFunctionProperties taskLaunchRequestProperties,
-														EvaluationContext evaluationContext) {
+			EvaluationContext evaluationContext) {
 		if (StringUtils.hasText(taskLaunchRequestProperties.getTaskNameExpression())) {
 			SpelExpressionParser expressionParser = new SpelExpressionParser();
 			Expression taskNameExpression = expressionParser
-					.parseExpression(taskLaunchRequestProperties.getTaskNameExpression());
+				.parseExpression(taskLaunchRequestProperties.getTaskNameExpression());
 			return new ExpressionEvaluatingTaskNameMessageMapper(taskNameExpression, evaluationContext);
 		}
 
@@ -122,23 +122,23 @@ public class TaskLaunchRequestFunctionConfiguration {
 	}
 
 	private static class TaskLaunchRequestPropertiesInitializer extends TaskLaunchRequestSupplier {
-		TaskLaunchRequestPropertiesInitializer(
-				TaskLaunchRequestFunctionProperties taskLaunchRequestProperties) {
 
-			this.commandLineArgumentSupplier(
-					() -> new ArrayList<>(taskLaunchRequestProperties.getArgs()));
+		TaskLaunchRequestPropertiesInitializer(TaskLaunchRequestFunctionProperties taskLaunchRequestProperties) {
 
-			this.deploymentPropertiesSupplier(
-					() -> KeyValueListParser.parseCommaDelimitedKeyValuePairs(
-							taskLaunchRequestProperties.getDeploymentProperties()));
+			this.commandLineArgumentSupplier(() -> new ArrayList<>(taskLaunchRequestProperties.getArgs()));
+
+			this.deploymentPropertiesSupplier(() -> KeyValueListParser
+				.parseCommaDelimitedKeyValuePairs(taskLaunchRequestProperties.getDeploymentProperties()));
 
 			this.taskNameSupplier(() -> taskLaunchRequestProperties.getTaskName());
 		}
+
 	}
 
 	private static class ExpressionEvaluatingTaskNameMessageMapper implements TaskNameMessageMapper {
 
 		private final Expression expression;
+
 		private final EvaluationContext evaluationContext;
 
 		ExpressionEvaluatingTaskNameMessageMapper(Expression expression, EvaluationContext evaluationContext) {
@@ -150,9 +150,11 @@ public class TaskLaunchRequestFunctionConfiguration {
 		public String processMessage(Message<?> message) {
 			return expression.getValue(evaluationContext, message).toString();
 		}
+
 	}
 
 	private static class ExpressionEvaluatingCommandLineArgsMapper implements CommandLineArgumentsMessageMapper {
+
 		private final Map<String, Expression> argExpressionsMap;
 
 		private final EvaluationContext evaluationContext;
@@ -163,8 +165,8 @@ public class TaskLaunchRequestFunctionConfiguration {
 			if (StringUtils.hasText(argExpressions)) {
 				SpelExpressionParser expressionParser = new SpelExpressionParser();
 
-				KeyValueListParser.parseCommaDelimitedKeyValuePairs(argExpressions).forEach(
-						(k, v) -> argExpressionsMap.put(k, expressionParser.parseExpression(v)));
+				KeyValueListParser.parseCommaDelimitedKeyValuePairs(argExpressions)
+					.forEach((k, v) -> argExpressionsMap.put(k, expressionParser.parseExpression(v)));
 			}
 		}
 
@@ -176,9 +178,10 @@ public class TaskLaunchRequestFunctionConfiguration {
 		private Collection<String> evaluateArgExpressions(Message<?> message) {
 			List<String> results = new LinkedList<>();
 			this.argExpressionsMap.forEach((k, expression) -> results
-					.add(String.format("%s=%s", k, expression.getValue(this.evaluationContext, message))));
+				.add(String.format("%s=%s", k, expression.getValue(this.evaluationContext, message))));
 			return results;
 		}
+
 	}
 
 }

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/TaskLaunchRequestFunctionProperties.java

@@ -57,9 +57,9 @@ public class TaskLaunchRequestFunctionProperties {
 	 */
 	private String taskName;
 
-
 	/**
-	 * A SpEL expression to extract the task name from each Message, using the Message as the evaluation context.
+	 * A SpEL expression to extract the task name from each Message, using the Message as
+	 * the evaluation context.
 	 */
 	private String taskNameExpression;
 

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/TaskLaunchRequestMessageProcessor.java

@@ -57,7 +57,7 @@ class TaskLaunchRequestMessageProcessor implements MessagePostProcessor {
 		taskLaunchRequest.addCommmandLineArguments(commandLineArgumentsMessageMapper.processMessage(message));
 
 		MessageBuilder<TaskLaunchRequest> builder = MessageBuilder.withPayload(taskLaunchRequest)
-				.copyHeaders(message.getHeaders());
+			.copyHeaders(message.getHeaders());
 		return adjustHeaders(builder).build();
 	}
 
@@ -65,4 +65,5 @@ class TaskLaunchRequestMessageProcessor implements MessagePostProcessor {
 		builder.setHeader(MessageHeaders.CONTENT_TYPE, MimeTypeUtils.APPLICATION_JSON);
 		return builder;
 	}
+
 }

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/TaskLaunchRequestSupplier.java

@@ -64,4 +64,5 @@ class TaskLaunchRequestSupplier implements Supplier<TaskLaunchRequest> {
 
 		return taskLaunchRequest;
 	}
+
 }

function/spring-task-launch-request-function/src/main/java/org/springframework/cloud/fn/task/launch/request/TaskNameMessageMapper.java

@@ -20,4 +20,5 @@ import org.springframework.integration.handler.MessageProcessor;
 
 @FunctionalInterface
 public interface TaskNameMessageMapper extends MessageProcessor<String> {
+
 }

function/spring-task-launch-request-function/src/test/java/org/springframework/cloud/fn/task/launch/request/KeyValueListParserTests.java

@@ -31,8 +31,8 @@ public class KeyValueListParserTests {
 
 	@Test
 	public void testParseSimpleDeploymentProperty() {
-		Map<String, String> deploymentProperties = KeyValueListParser.parseCommaDelimitedKeyValuePairs(
-				"app.sftp.param=value");
+		Map<String, String> deploymentProperties = KeyValueListParser
+			.parseCommaDelimitedKeyValuePairs("app.sftp.param=value");
 		assertTrue("Invalid number of deployment properties: " + deploymentProperties.size(),
 				deploymentProperties.size() == 1);
 		assertTrue("Expected deployment key not found", deploymentProperties.containsKey("app.sftp.param"));
@@ -41,8 +41,8 @@ public class KeyValueListParserTests {
 
 	@Test
 	public void testParseSimpleDeploymentPropertyMultipleValues() {
-		Map<String, String> deploymentProperties = KeyValueListParser.parseCommaDelimitedKeyValuePairs(
-				"app.sftp.param=value1,value2,value3");
+		Map<String, String> deploymentProperties = KeyValueListParser
+			.parseCommaDelimitedKeyValuePairs("app.sftp.param=value1,value2,value3");
 
 		assertTrue("Invalid number of deployment properties: " + deploymentProperties.size(),
 				deploymentProperties.size() == 1);
@@ -55,8 +55,7 @@ public class KeyValueListParserTests {
 		Map<String, String> argExpressions = KeyValueListParser.parseCommaDelimitedKeyValuePairs(
 				"arg1=payload.substr(0,2),arg2=headers['foo'],arg3=headers['bar']==false");
 
-		assertTrue("Invalid number of deployment properties: " + argExpressions.size(),
-				argExpressions.size() == 3);
+		assertTrue("Invalid number of deployment properties: " + argExpressions.size(), argExpressions.size() == 3);
 		assertTrue("Expected deployment key not found", argExpressions.containsKey("arg1"));
 		assertEquals("Invalid deployment value", "payload.substr(0,2)", argExpressions.get("arg1"));
 
@@ -69,8 +68,8 @@ public class KeyValueListParserTests {
 
 	@Test
 	public void testParseMultipleDeploymentPropertiesSingleValue() {
-		Map<String, String> deploymentProperties = KeyValueListParser.parseCommaDelimitedKeyValuePairs(
-				"app.sftp.param=value1,app.sftp.other.param=value2");
+		Map<String, String> deploymentProperties = KeyValueListParser
+			.parseCommaDelimitedKeyValuePairs("app.sftp.param=value1,app.sftp.other.param=value2");
 
 		assertTrue("Invalid number of deployment properties: " + deploymentProperties.size(),
 				deploymentProperties.size() == 2);
@@ -84,8 +83,8 @@ public class KeyValueListParserTests {
 	public void testParseMultipleDeploymentPropertiesMultipleValues() {
 		TaskLaunchRequestFunctionProperties taskLaunchRequestProperties = new TaskLaunchRequestFunctionProperties();
 
-		Map<String, String> deploymentProperties = KeyValueListParser.parseCommaDelimitedKeyValuePairs(
-				"app.sftp.param=value1,value2,app.sftp.other.param=other1,other2");
+		Map<String, String> deploymentProperties = KeyValueListParser
+			.parseCommaDelimitedKeyValuePairs("app.sftp.param=value1,value2,app.sftp.other.param=other1,other2");
 
 		assertTrue("Invalid number of deployment properties: " + deploymentProperties.size(),
 				deploymentProperties.size() == 2);
@@ -94,4 +93,5 @@ public class KeyValueListParserTests {
 		assertTrue("Expected deployment key not found", deploymentProperties.containsKey("app.sftp.other.param"));
 		assertEquals("Invalid deployment value", "other1,other2", deploymentProperties.get("app.sftp.other.param"));
 	}
+
 }

function/spring-task-launch-request-function/src/test/java/org/springframework/cloud/fn/task/launch/request/TaskLaunchRequestFunctionApplicationTests.java

@@ -45,18 +45,17 @@ public class TaskLaunchRequestFunctionApplicationTests {
 	@BeforeEach
 	public void setUp() {
 		springApplicationBuilder = new SpringApplicationBuilder(TaskLaunchRequestFunctionTestApplication.class)
-				.web(WebApplicationType.NONE);
+			.web(WebApplicationType.NONE);
 	}
 
 	@Test
 	@DirtiesContext
 	public void simpleDataflowTaskLaunchRequest() throws IOException {
 
-		ApplicationContext context = springApplicationBuilder.properties(
-				"spring.jmx.enabled=false",
-				"spring.cloud.function.definition=taskLaunchRequestFunction",
-				"task.launch.request.task-name=foo")
-				.run();
+		ApplicationContext context = springApplicationBuilder
+			.properties("spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
+					"task.launch.request.task-name=foo")
+			.run();
 
 		TaskLaunchRequest taskLaunchRequest = verifyAndreceiveTaskLaunchRequest(context);
 
@@ -69,16 +68,15 @@ public class TaskLaunchRequestFunctionApplicationTests {
 	@DirtiesContext
 	public void dataflowTaskLaunchRequestWithArgsAndDeploymentProperties() throws IOException {
 
-		ApplicationContext context = springApplicationBuilder.properties(
-				"spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
-				"task.launch.request.task-name=foo", "task.launch.request.args=foo=bar,baz=boo",
-				"task.launch.request.deploymentProperties=count=3")
-				.run();
+		ApplicationContext context = springApplicationBuilder
+			.properties("spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
+					"task.launch.request.task-name=foo", "task.launch.request.args=foo=bar,baz=boo",
+					"task.launch.request.deploymentProperties=count=3")
+			.run();
 		TaskLaunchRequest taskLaunchRequest = verifyAndreceiveTaskLaunchRequest(context);
 
 		assertThat(taskLaunchRequest.getTaskName()).isEqualTo("foo");
-		assertThat(taskLaunchRequest.getCommandlineArguments()).containsExactlyInAnyOrder("foo=bar",
-				"baz=boo");
+		assertThat(taskLaunchRequest.getCommandlineArguments()).containsExactlyInAnyOrder("foo=bar", "baz=boo");
 		assertThat(taskLaunchRequest.getDeploymentProperties()).containsOnly(entry("count", "3"));
 	}
 
@@ -86,10 +84,10 @@ public class TaskLaunchRequestFunctionApplicationTests {
 	@DirtiesContext
 	public void taskLaunchRequestWithCommandLineArgsMessageMapper() throws IOException {
 
-		ApplicationContext context = springApplicationBuilder.properties(
-				"spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
-				"task.launch.request.task-name=foo", "enhanceTLRArgs=true")
-				.run();
+		ApplicationContext context = springApplicationBuilder
+			.properties("spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
+					"task.launch.request.task-name=foo", "enhanceTLRArgs=true")
+			.run();
 
 		TaskLaunchRequest taskLaunchRequest = verifyAndreceiveTaskLaunchRequest(context);
 
@@ -102,12 +100,11 @@ public class TaskLaunchRequestFunctionApplicationTests {
 	@Test
 	@DirtiesContext
 	public void taskLaunchRequestWithArgExpressions() throws IOException {
-		ApplicationContext context = springApplicationBuilder.properties(
-				"spring.jmx.enabled=false",
-				"spring.cloud.function.definition=taskLaunchRequestFunction",
-				"task.launch.request.task-name=foo",
-				"task.launch.request.arg-expressions=foo=payload.toUpperCase(),bar=payload.substring(0,2)")
-				.run();
+		ApplicationContext context = springApplicationBuilder
+			.properties("spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
+					"task.launch.request.task-name=foo",
+					"task.launch.request.arg-expressions=foo=payload.toUpperCase(),bar=payload.substring(0,2)")
+			.run();
 
 		Message<String> message = MessageBuilder.withPayload("hello").build();
 
@@ -123,11 +120,10 @@ public class TaskLaunchRequestFunctionApplicationTests {
 	@Test
 	@DirtiesContext
 	public void taskLaunchRequestWithIntPayload() throws IOException {
-		ApplicationContext context = springApplicationBuilder.properties(
-				"spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
-				"task.launch.request.task-name=foo",
-				"task.launch.request.arg-expressions=i=payload")
-				.run();
+		ApplicationContext context = springApplicationBuilder
+			.properties("spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
+					"task.launch.request.task-name=foo", "task.launch.request.arg-expressions=i=payload")
+			.run();
 
 		TaskLaunchRequestFunction taskLaunchRequestFunction = context.getBean(TaskLaunchRequestFunction.class);
 
@@ -144,10 +140,10 @@ public class TaskLaunchRequestFunctionApplicationTests {
 	@Test
 	@DirtiesContext
 	public void taskNameExpression() throws IOException {
-		ApplicationContext context = springApplicationBuilder.properties(
-				"spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
-				"task.launch.request.task-name-expression=payload+'_task'")
-				.run();
+		ApplicationContext context = springApplicationBuilder
+			.properties("spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
+					"task.launch.request.task-name-expression=payload+'_task'")
+			.run();
 
 		TaskLaunchRequestFunction taskLaunchRequestFunction = context.getBean(TaskLaunchRequestFunction.class);
 
@@ -163,10 +159,10 @@ public class TaskLaunchRequestFunctionApplicationTests {
 	@Test
 	@DirtiesContext
 	public void customTaskNameExtractor() throws IOException {
-		ApplicationContext context = springApplicationBuilder.properties(
-				"spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
-				"customTaskNameExtractor=true")
-				.run();
+		ApplicationContext context = springApplicationBuilder
+			.properties("spring.jmx.enabled=false", "spring.cloud.function.definition=taskLaunchRequestFunction",
+					"customTaskNameExtractor=true")
+			.run();
 		TaskLaunchRequestFunction taskLaunchRequestFunction = context.getBean(TaskLaunchRequestFunction.class);
 
 		Message<String> message = MessageBuilder.withPayload("foo").build();
@@ -184,11 +180,10 @@ public class TaskLaunchRequestFunctionApplicationTests {
 		assertThat(request.getTaskName()).isEqualTo("defaultTask");
 	}
 
-	private TaskLaunchRequest verifyAndreceiveTaskLaunchRequest(ApplicationContext context)
-			throws IOException {
+	private TaskLaunchRequest verifyAndreceiveTaskLaunchRequest(ApplicationContext context) throws IOException {
 		TaskLaunchRequestFunction taskLaunchRequestFunction = context.getBean(TaskLaunchRequestFunction.class);
 		Message<TaskLaunchRequest> message = taskLaunchRequestFunction
-				.apply(MessageBuilder.withPayload(new byte[] {}).build());
+			.apply(MessageBuilder.withPayload(new byte[] {}).build());
 		assertThat(message).isNotNull();
 		return message.getPayload();
 	}
@@ -207,5 +202,7 @@ public class TaskLaunchRequestFunctionApplicationTests {
 		CommandLineArgumentsMessageMapper commandLineArgumentsProvider() {
 			return message -> Collections.singletonList("runtimeArg");
 		}
+
 	}
+
 }

function/spring-task-launch-request-function/src/test/java/org/springframework/cloud/fn/task/launch/request/TaskLaunchRequestFunctionPropertiesTests.java

@@ -73,4 +73,5 @@ public class TaskLaunchRequestFunctionPropertiesTests {
 	static class Conf {
 
 	}
+
 }

function/spring-twitter-function/src/main/java/org/springframework/cloud/fn/twitter/geo/TwitterGeoFunctionConfiguration.java

@@ -36,7 +36,6 @@ import org.springframework.context.annotation.Import;
 import org.springframework.messaging.Message;
 
 /**
- *
  * @author Christian Tzolov
  */
 @Configuration
@@ -103,11 +102,10 @@ public class TwitterGeoFunctionConfiguration {
 	}
 
 	@Bean
-	public Function<Message<?>, Message<byte[]>> twitterGeoFunction(
-			Function<Message<?>, GeoQuery> toGeoQuery,
-			Function<GeoQuery, List<Place>> places,
-			Function<Object, Message<byte[]>> managedJson) {
+	public Function<Message<?>, Message<byte[]>> twitterGeoFunction(Function<Message<?>, GeoQuery> toGeoQuery,
+			Function<GeoQuery, List<Place>> places, Function<Object, Message<byte[]>> managedJson) {
 
 		return toGeoQuery.andThen(places).andThen(managedJson)::apply;
 	}
+
 }

function/spring-twitter-function/src/main/java/org/springframework/cloud/fn/twitter/geo/TwitterGeoFunctionProperties.java

@@ -24,7 +24,6 @@ import org.springframework.expression.Expression;
 import org.springframework.expression.spel.standard.SpelExpressionParser;
 import org.springframework.validation.annotation.Validated;
 
-
 /**
  * @author Christian Tzolov
  */
@@ -35,8 +34,10 @@ public class TwitterGeoFunctionProperties {
 	private static final Expression DEFAULT_EXPRESSION = new SpelExpressionParser().parseExpression("payload");
 
 	public enum GeoType {
+
 		/** Geo retrieval type. */
 		reverse, search
+
 	}
 
 	/**
@@ -56,22 +57,24 @@ public class TwitterGeoFunctionProperties {
 	private Location location = new Location();
 
 	/**
-	 * Hints for the number of results to return. This does not guarantee that the number of results
-	 * returned will equal max_results, but instead informs how many 'nearby' results to return.
+	 * Hints for the number of results to return. This does not guarantee that the number
+	 * of results returned will equal max_results, but instead informs how many 'nearby'
+	 * results to return.
 	 */
 	private int maxResults = -1;
 
 	/**
-	 * Sets a hint on the 'region' in which to search. If a number, then this is a radius in meters, but it
-	 * can also take a string that is suffixed with ft to specify feet. If this is not passed in, then it is
-	 * assumed to be 0m. If coming from a device, in practice, this value is whatever accuracy the device
-	 * has measuring its location (whether it be coming from a GPS, WiFi triangulation, etc.).
+	 * Sets a hint on the 'region' in which to search. If a number, then this is a radius
+	 * in meters, but it can also take a string that is suffixed with ft to specify feet.
+	 * If this is not passed in, then it is assumed to be 0m. If coming from a device, in
+	 * practice, this value is whatever accuracy the device has measuring its location
+	 * (whether it be coming from a GPS, WiFi triangulation, etc.).
 	 */
 	private String accuracy = null;
 
 	/**
-	 * Minimal granularity of data to return. If this is not passed in, then neighborhood is assumed.
-	 * City can also be passed.
+	 * Minimal granularity of data to return. If this is not passed in, then neighborhood
+	 * is assumed. City can also be passed.
 	 */
 	private String granularity = null;
 
@@ -125,7 +128,8 @@ public class TwitterGeoFunctionProperties {
 
 	@AssertTrue(message = "Either the IP or the Location must be set")
 	public boolean isAtLeastOne() {
-		return this.getSearch().getIp() == null ^ (this.getLocation().getLat() == null && this.getLocation().getLon() == null);
+		return this.getSearch().getIp() == null
+				^ (this.getLocation().getLat() == null && this.getLocation().getLon() == null);
 	}
 
 	@AssertTrue(message = "The IP parameter is applicable only for 'Search' GeoType")
@@ -137,9 +141,10 @@ public class TwitterGeoFunctionProperties {
 	}
 
 	public static class Search {
+
 		/**
-		 * An IP address. Used when attempting to fix geolocation based off of the user's IP address.
-		 * Applicable only for 'search' geo type.
+		 * An IP address. Used when attempting to fix geolocation based off of the user's
+		 * IP address. Applicable only for 'search' geo type.
 		 */
 		private Expression ip = null;
 
@@ -163,6 +168,7 @@ public class TwitterGeoFunctionProperties {
 		public void setQuery(Expression query) {
 			this.query = query;
 		}
+
 	}
 
 	public static class Location {
@@ -177,7 +183,6 @@ public class TwitterGeoFunctionProperties {
 		 */
 		private Expression lon;
 
-
 		public Expression getLat() {
 			return lat;
 		}
@@ -193,5 +198,7 @@ public class TwitterGeoFunctionProperties {
 		public void setLon(Expression lon) {
 			this.lon = lon;
 		}
+
 	}
+
 }

function/spring-twitter-function/src/main/java/org/springframework/cloud/fn/twitter/trend/TwitterTrendFunctionConfiguration.java

@@ -59,8 +59,8 @@ public class TwitterTrendFunctionConfiguration {
 	}
 
 	@Bean
-	public Function<Message<?>, List<Location>> closestOrAvailableTrends(
-			TwitterTrendFunctionProperties properties, Twitter twitter) {
+	public Function<Message<?>, List<Location>> closestOrAvailableTrends(TwitterTrendFunctionProperties properties,
+			Twitter twitter) {
 		return message -> {
 			try {
 				if (properties.getClosest().getLat() != null && properties.getClosest().getLon() != null) {
@@ -80,12 +80,12 @@ public class TwitterTrendFunctionConfiguration {
 	}
 
 	@Bean
-	public Function<Message<?>, Message<byte[]>> twitterTrendFunction(
-			Function<Object, Message<byte[]>> managedJson, Function<Message<?>, Trends> trend,
-			TwitterTrendFunctionProperties properties, Function<Message<?>,
-			List<Location>> closestOrAvailableTrends) {
+	public Function<Message<?>, Message<byte[]>> twitterTrendFunction(Function<Object, Message<byte[]>> managedJson,
+			Function<Message<?>, Trends> trend, TwitterTrendFunctionProperties properties,
+			Function<Message<?>, List<Location>> closestOrAvailableTrends) {
 
-		return (properties.getTrendQueryType() == TwitterTrendFunctionProperties.TrendQueryType.trend) ?
-				trend.andThen(managedJson) : closestOrAvailableTrends.andThen(managedJson);
+		return (properties.getTrendQueryType() == TwitterTrendFunctionProperties.TrendQueryType.trend)
+				? trend.andThen(managedJson) : closestOrAvailableTrends.andThen(managedJson);
 	}
+
 }

function/spring-twitter-function/src/main/java/org/springframework/cloud/fn/twitter/trend/TwitterTrendFunctionProperties.java

@@ -33,10 +33,12 @@ public class TwitterTrendFunctionProperties {
 	private static final Expression DEFAULT_EXPRESSION = new SpelExpressionParser().parseExpression("payload");
 
 	enum TrendQueryType {
+
 		/** Retrieve trending places. */
 		trend,
 		/** Retrieve the Locations of trending places. */
 		trendLocation
+
 	}
 
 	private TrendQueryType trendQueryType = TrendQueryType.trend;
@@ -74,17 +76,18 @@ public class TwitterTrendFunctionProperties {
 	}
 
 	public static class Closest {
+
 		/**
-		 * If provided with a long parameter the available trend locations will be sorted by distance, nearest
-		 * to furthest, to the co-ordinate pair.
-		 * The valid ranges for longitude is -180.0 to +180.0 (West is negative, East is positive) inclusive.
+		 * If provided with a long parameter the available trend locations will be sorted
+		 * by distance, nearest to furthest, to the co-ordinate pair. The valid ranges for
+		 * longitude is -180.0 to +180.0 (West is negative, East is positive) inclusive.
 		 */
 		private Expression lat;
 
 		/**
-		 * If provided with a lat parameter the available trend locations will be sorted by distance, nearest to
-		 * furthest, to the co-ordinate pair. The valid ranges for longitude is -180.0 to +180.0 (West is negative,
-		 * East is positive) inclusive.
+		 * If provided with a lat parameter the available trend locations will be sorted
+		 * by distance, nearest to furthest, to the co-ordinate pair. The valid ranges for
+		 * longitude is -180.0 to +180.0 (West is negative, East is positive) inclusive.
 		 */
 		private Expression lon;
 
@@ -103,5 +106,7 @@ public class TwitterTrendFunctionProperties {
 		public void setLon(Expression lon) {
 			this.lon = lon;
 		}
+
 	}
+
 }

function/spring-twitter-function/src/main/java/org/springframework/cloud/fn/twitter/users/TwitterUsersFunctionConfiguration.java

@@ -35,7 +35,6 @@ import org.springframework.context.annotation.Import;
 import org.springframework.messaging.Message;
 
 /**
- *
  * @author Christian Tzolov
  */
 @Configuration
@@ -88,11 +87,12 @@ public class TwitterUsersFunctionConfiguration {
 
 	@Bean
 	/**
-	 * queryUsers - depends on the `twitter.users.type` property is either userSearch or userLookup.
-	 * managedJson - converts Users into JSON message payload.
+	 * queryUsers - depends on the `twitter.users.type` property is either userSearch or
+	 * userLookup. managedJson - converts Users into JSON message payload.
 	 */
 	public Function<Message<?>, Message<byte[]>> twitterUsersFunction(Function<Message<?>, List<User>> queryUsers,
 			Function<Object, Message<byte[]>> managedJson) {
 		return queryUsers.andThen(managedJson);
 	}
+
 }

function/spring-twitter-function/src/main/java/org/springframework/cloud/fn/twitter/users/TwitterUsersFunctionProperties.java

@@ -34,8 +34,10 @@ public class TwitterUsersFunctionProperties {
 	private static final Expression DEFAULT_EXPRESSION = new SpelExpressionParser().parseExpression("payload");
 
 	public enum UserQueryType {
+
 		/** User retrieval types. */
 		search, lookup
+
 	}
 
 	/**
@@ -45,14 +47,14 @@ public class TwitterUsersFunctionProperties {
 	private UserQueryType type = UserQueryType.search;
 
 	/**
-	 * Returns fully-hydrated user objects for specified by comma-separated values passed to the user_id and/or
-	 * screen_name parameters.
+	 * Returns fully-hydrated user objects for specified by comma-separated values passed
+	 * to the user_id and/or screen_name parameters.
 	 */
 	private final Lookup lookup = new Lookup();
 
 	/**
-	 * relevance-based search interface for querying by topical interest, full name, company name, location,
-	 * or other criteria.
+	 * relevance-based search interface for querying by topical interest, full name,
+	 * company name, location, or other criteria.
 	 */
 	private final Search search = new Search();
 
@@ -85,6 +87,7 @@ public class TwitterUsersFunctionProperties {
 	}
 
 	public static class Lookup {
+
 		/**
 		 * A comma separated list of user IDs, up to 100 are allowed in a single request.
 		 * You are strongly encouraged to use a POST for larger requests.
@@ -92,8 +95,9 @@ public class TwitterUsersFunctionProperties {
 		private Expression userId;
 
 		/**
-		 * A comma separated list of screen names, up to 100 are allowed in a single request.
-		 * You are strongly encouraged to use a POST for larger (up to 100 screen names) requests.
+		 * A comma separated list of screen names, up to 100 are allowed in a single
+		 * request. You are strongly encouraged to use a POST for larger (up to 100 screen
+		 * names) requests.
 		 */
 		private Expression screenName;
 
@@ -112,9 +116,11 @@ public class TwitterUsersFunctionProperties {
 		public void setScreenName(Expression screenName) {
 			this.screenName = screenName;
 		}
+
 	}
 
 	public static class Search {
+
 		/**
 		 * The search query to run against people search.
 		 */
@@ -140,5 +146,7 @@ public class TwitterUsersFunctionProperties {
 		public void setPage(int page) {
 			this.page = page;
 		}
+
 	}
+
 }

function/spring-twitter-function/src/test/java/org/springframework/cloud/fn/twitter/geo/TwitterGeoFunctionTest.java

@@ -58,14 +58,10 @@ import static org.mockserver.verify.VerificationTimes.once;
 /**
  * @author Christian Tzolov
  */
-@SpringBootTest(
-		webEnvironment = SpringBootTest.WebEnvironment.NONE,
-		properties = {
-				"twitter.connection.consumerKey=consumerKey666",
-				"twitter.connection.consumerSecret=consumerSecret666",
-				"twitter.connection.accessToken=accessToken666",
-				"twitter.connection.accessTokenSecret=accessTokenSecret666"
-		})
+@SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.NONE,
+		properties = { "twitter.connection.consumerKey=consumerKey666",
+				"twitter.connection.consumerSecret=consumerSecret666", "twitter.connection.accessToken=accessToken666",
+				"twitter.connection.accessTokenSecret=accessTokenSecret666" })
 @DirtiesContext(classMode = DirtiesContext.ClassMode.AFTER_CLASS)
 public abstract class TwitterGeoFunctionTest {
 
@@ -83,18 +79,12 @@ public abstract class TwitterGeoFunctionTest {
 	public static void recordRequestExpectation(Map<String, List<String>> parameters) {
 
 		mockClient
-				.when(
-						request()
-								.withMethod("GET")
-								.withPath("/geo/search.json")
-								.withQueryStringParameters(parameters),
-						unlimited())
-				.respond(
-						response()
-								.withStatusCode(200)
-								.withHeader("Content-Type", "application/json; charset=utf-8")
-								.withBody(TwitterTestUtils.asString("classpath:/response/search_places_amsterdam.json"))
-								.withDelay(TimeUnit.SECONDS, 1));
+			.when(request().withMethod("GET").withPath("/geo/search.json").withQueryStringParameters(parameters),
+					unlimited())
+			.respond(response().withStatusCode(200)
+				.withHeader("Content-Type", "application/json; charset=utf-8")
+				.withBody(TwitterTestUtils.asString("classpath:/response/search_places_amsterdam.json"))
+				.withDelay(TimeUnit.SECONDS, 1));
 
 	}
 
@@ -109,10 +99,8 @@ public abstract class TwitterGeoFunctionTest {
 		mockServer.stop();
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.geo.search.ip='127.0.0.1'",
-			"twitter.geo.search.query=payload.toUpperCase()"
-	})
+	@TestPropertySource(
+			properties = { "twitter.geo.search.ip='127.0.0.1'", "twitter.geo.search.query=payload.toUpperCase()" })
 	public static class TwitterGeoSearchByIPAndQueryTests extends TwitterGeoFunctionTest {
 
 		@Test
@@ -128,12 +116,10 @@ public abstract class TwitterGeoFunctionTest {
 
 			Message<?> received = twitterUsersFunction.apply(MessageBuilder.withPayload(inPayload).build());
 
-			mockClient.verify(request()
-							.withMethod("GET")
-							.withPath("/geo/search.json")
-							.withQueryStringParameter("ip", "127.0.0.1")
-							.withQueryStringParameter("query", "AMSTERDAM"),
-					once());
+			mockClient.verify(request().withMethod("GET")
+				.withPath("/geo/search.json")
+				.withQueryStringParameter("ip", "127.0.0.1")
+				.withQueryStringParameter("query", "AMSTERDAM"), once());
 
 			String outPayload = new String((byte[]) received.getPayload());
 
@@ -142,13 +128,11 @@ public abstract class TwitterGeoFunctionTest {
 			List places = new ObjectMapper().readValue(outPayload, List.class);
 			assertThat(places).hasSize(12);
 		}
+
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.geo.location.lat='52.378'",
-			"twitter.geo.location.lon='4.9'",
-			"twitter.geo.search.query=payload.toUpperCase()"
-	})
+	@TestPropertySource(properties = { "twitter.geo.location.lat='52.378'", "twitter.geo.location.lon='4.9'",
+			"twitter.geo.search.query=payload.toUpperCase()" })
 	public static class TwitterGeoSearchByLocationTests extends TwitterGeoFunctionTest {
 
 		@Test
@@ -165,13 +149,11 @@ public abstract class TwitterGeoFunctionTest {
 
 			Message<?> received = twitterUsersFunction.apply(MessageBuilder.withPayload(inPayload).build());
 
-			mockClient.verify(request()
-							.withMethod("GET")
-							.withPath("/geo/search.json")
-							.withQueryStringParameter("lat", "52.378")
-							.withQueryStringParameter("long", "4.9")
-							.withQueryStringParameter("query", "Amsterdam"),
-					once());
+			mockClient.verify(request().withMethod("GET")
+				.withPath("/geo/search.json")
+				.withQueryStringParameter("lat", "52.378")
+				.withQueryStringParameter("long", "4.9")
+				.withQueryStringParameter("query", "Amsterdam"), once());
 
 			String outPayload = new String((byte[]) received.getPayload());
 
@@ -180,13 +162,11 @@ public abstract class TwitterGeoFunctionTest {
 			List places = new ObjectMapper().readValue(outPayload, List.class);
 			assertThat(places).hasSize(12);
 		}
+
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.geo.type=reverse",
-			"twitter.geo.location.lat='52.378'",
-			"twitter.geo.location.lon='4.9'"
-	})
+	@TestPropertySource(properties = { "twitter.geo.type=reverse", "twitter.geo.location.lat='52.378'",
+			"twitter.geo.location.lon='4.9'" })
 	public static class TwitterGeoSearchByLocation2Tests extends TwitterGeoFunctionTest {
 
 		@Test
@@ -202,12 +182,10 @@ public abstract class TwitterGeoFunctionTest {
 
 			Message<?> received = twitterUsersFunction.apply(MessageBuilder.withPayload(inPayload).build());
 
-			mockClient.verify(request()
-							.withMethod("GET")
-							.withPath("/geo/search.json")
-							.withQueryStringParameter("lat", "52.378")
-							.withQueryStringParameter("long", "4.9"),
-					once());
+			mockClient.verify(request().withMethod("GET")
+				.withPath("/geo/search.json")
+				.withQueryStringParameter("lat", "52.378")
+				.withQueryStringParameter("long", "4.9"), once());
 
 			String outPayload = new String((byte[]) received.getPayload());
 
@@ -216,13 +194,12 @@ public abstract class TwitterGeoFunctionTest {
 			List places = new ObjectMapper().readValue(outPayload, List.class);
 			assertThat(places).hasSize(12);
 		}
+
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.geo.location.lat=#jsonPath(new String(payload),'$.location.lat')",
+	@TestPropertySource(properties = { "twitter.geo.location.lat=#jsonPath(new String(payload),'$.location.lat')",
 			"twitter.geo.location.lon=#jsonPath(new String(payload),'$.location.lon')",
-			"twitter.geo.search.query=#jsonPath(new String(payload),'$.country')"
-	})
+			"twitter.geo.search.query=#jsonPath(new String(payload),'$.country')" })
 	public static class TwitterGeoSearchJsonPathTests extends TwitterGeoFunctionTest {
 
 		@Test
@@ -237,18 +214,15 @@ public abstract class TwitterGeoFunctionTest {
 
 			String inPayload = "{ \"country\" : \"Netherlands\", \"location\" : { \"lat\" : 52.00 , \"lon\" : 5.0 } }";
 
-			Message<?> received = twitterUsersFunction.apply(MessageBuilder
-					.withPayload(inPayload)
-					.setHeader("contentType", MimeTypeUtils.APPLICATION_JSON_VALUE)
-					.build());
+			Message<?> received = twitterUsersFunction.apply(MessageBuilder.withPayload(inPayload)
+				.setHeader("contentType", MimeTypeUtils.APPLICATION_JSON_VALUE)
+				.build());
 
-			mockClient.verify(request()
-							.withMethod("GET")
-							.withPath("/geo/search.json")
-							.withQueryStringParameter("lat", "52.0")
-							.withQueryStringParameter("long", "5.0")
-							.withQueryStringParameter("query", "Netherlands"),
-					once());
+			mockClient.verify(request().withMethod("GET")
+				.withPath("/geo/search.json")
+				.withQueryStringParameter("lat", "52.0")
+				.withQueryStringParameter("long", "5.0")
+				.withQueryStringParameter("query", "Netherlands"), once());
 
 			String outPayload = new String((byte[]) received.getPayload());
 
@@ -257,23 +231,26 @@ public abstract class TwitterGeoFunctionTest {
 			List places = new ObjectMapper().readValue(outPayload, List.class);
 			assertThat(places).hasSize(12);
 		}
+
 	}
 
 	@SpringBootConfiguration
 	@EnableAutoConfiguration
 	@Import(TwitterGeoFunctionConfiguration.class)
 	public static class TwitterGeoFunctionTestApplication {
+
 		@Bean
 		@Primary
 		public twitter4j.conf.Configuration twitterConfiguration2(TwitterConnectionProperties properties,
 				Function<TwitterConnectionProperties, ConfigurationBuilder> toConfigurationBuilder) {
 
-			Function<TwitterConnectionProperties, ConfigurationBuilder> mockedConfiguration =
-					toConfigurationBuilder.andThen(
-							new TwitterTestUtils().mockTwitterUrls(
-									String.format("http://%s:%s", MOCK_SERVER_IP, MOCK_SERVER_PORT)));
+			Function<TwitterConnectionProperties, ConfigurationBuilder> mockedConfiguration = toConfigurationBuilder
+				.andThen(new TwitterTestUtils()
+					.mockTwitterUrls(String.format("http://%s:%s", MOCK_SERVER_IP, MOCK_SERVER_PORT)));
 
 			return mockedConfiguration.apply(properties).build();
 		}
+
 	}
+
 }

function/spring-twitter-function/src/test/java/org/springframework/cloud/fn/twitter/trend/TwitterTrendFunctionTests.java

@@ -52,14 +52,10 @@ import static org.mockserver.verify.VerificationTimes.once;
 /**
  * @author Christian Tzolov
  */
-@SpringBootTest(
-		webEnvironment = SpringBootTest.WebEnvironment.NONE,
-		properties = {
-				"twitter.connection.consumerKey=consumerKey666",
-				"twitter.connection.consumerSecret=consumerSecret666",
-				"twitter.connection.accessToken=accessToken666",
-				"twitter.connection.accessTokenSecret=accessTokenSecret666"
-		})
+@SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.NONE,
+		properties = { "twitter.connection.consumerKey=consumerKey666",
+				"twitter.connection.consumerSecret=consumerSecret666", "twitter.connection.accessToken=accessToken666",
+				"twitter.connection.accessTokenSecret=accessTokenSecret666" })
 @DirtiesContext(classMode = DirtiesContext.ClassMode.AFTER_CLASS)
 public abstract class TwitterTrendFunctionTests {
 
@@ -70,6 +66,7 @@ public abstract class TwitterTrendFunctionTests {
 	private static ClientAndServer mockServer;
 
 	private static MockServerClient mockClient;
+
 	private static HttpRequest trendsRequest;
 
 	@Autowired
@@ -80,10 +77,8 @@ public abstract class TwitterTrendFunctionTests {
 		mockServer = ClientAndServer.startClientAndServer(MOCK_SERVER_PORT);
 		mockClient = new MockServerClient(MOCK_SERVER_IP, MOCK_SERVER_PORT);
 
-		trendsRequest = setExpectation(request()
-				.withMethod("GET")
-				.withPath("/trends/place.json")
-				.withQueryStringParameter("id", "2972"));
+		trendsRequest = setExpectation(
+				request().withMethod("GET").withPath("/trends/place.json").withQueryStringParameter("id", "2972"));
 	}
 
 	@AfterAll
@@ -92,23 +87,16 @@ public abstract class TwitterTrendFunctionTests {
 	}
 
 	public static HttpRequest setExpectation(HttpRequest request) {
-		mockClient
-				.when(request, exactly(1))
-				.respond(response()
-						.withStatusCode(200)
-						.withHeaders(
-								new Header("Content-Type", "application/json; charset=utf-8"),
-								new Header("Cache-Control", "public, max-age=86400"))
-						.withBody(TwitterTestUtils.asString("classpath:/response/trends.json"))
-						.withDelay(TimeUnit.SECONDS, 1)
-				);
+		mockClient.when(request, exactly(1))
+			.respond(response().withStatusCode(200)
+				.withHeaders(new Header("Content-Type", "application/json; charset=utf-8"),
+						new Header("Cache-Control", "public, max-age=86400"))
+				.withBody(TwitterTestUtils.asString("classpath:/response/trends.json"))
+				.withDelay(TimeUnit.SECONDS, 1));
 		return request;
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.trend.locationId='2972'",
-			"twitter.connection.rawJson=true"
-	})
+	@TestPropertySource(properties = { "twitter.trend.locationId='2972'", "twitter.connection.rawJson=true" })
 	public static class TwitterTrendPayloadTests extends TwitterTrendFunctionTests {
 
 		@Test
@@ -117,24 +105,26 @@ public abstract class TwitterTrendFunctionTests {
 			mockClient.verify(trendsRequest, once());
 			assertThat(received).isNotNull();
 		}
+
 	}
 
 	@SpringBootConfiguration
 	@EnableAutoConfiguration
 	@Import(TwitterTrendFunctionConfiguration.class)
 	public static class TwitterTrendFunctionTestApplication {
+
 		@Bean
 		@Primary
 		public twitter4j.conf.Configuration twitterConfiguration2(TwitterConnectionProperties properties,
 				Function<TwitterConnectionProperties, ConfigurationBuilder> toConfigurationBuilder) {
 
-			Function<TwitterConnectionProperties, ConfigurationBuilder> mockedConfiguration =
-					toConfigurationBuilder.andThen(
-							new TwitterTestUtils().mockTwitterUrls(
-									String.format("http://%s:%s", MOCK_SERVER_IP, MOCK_SERVER_PORT)));
+			Function<TwitterConnectionProperties, ConfigurationBuilder> mockedConfiguration = toConfigurationBuilder
+				.andThen(new TwitterTestUtils()
+					.mockTwitterUrls(String.format("http://%s:%s", MOCK_SERVER_IP, MOCK_SERVER_PORT)));
 
 			return mockedConfiguration.apply(properties).build();
 		}
+
 	}
 
 }

function/spring-twitter-function/src/test/java/org/springframework/cloud/fn/twitter/users/TwitterUsersFunctionTests.java

@@ -55,14 +55,10 @@ import static org.mockserver.verify.VerificationTimes.once;
 /**
  * @author Christian Tzolov
  */
-@SpringBootTest(
-		webEnvironment = SpringBootTest.WebEnvironment.NONE,
-		properties = {
-				"twitter.connection.consumerKey=consumerKey666",
-				"twitter.connection.consumerSecret=consumerSecret666",
-				"twitter.connection.accessToken=accessToken666",
-				"twitter.connection.accessTokenSecret=accessTokenSecret666"
-		})
+@SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.NONE,
+		properties = { "twitter.connection.consumerKey=consumerKey666",
+				"twitter.connection.consumerSecret=consumerSecret666", "twitter.connection.accessToken=accessToken666",
+				"twitter.connection.accessTokenSecret=accessTokenSecret666" })
 @DirtiesContext(classMode = DirtiesContext.ClassMode.AFTER_CLASS)
 public abstract class TwitterUsersFunctionTests {
 
@@ -73,8 +69,11 @@ public abstract class TwitterUsersFunctionTests {
 	private static ClientAndServer mockServer;
 
 	private static MockServerClient mockClient;
+
 	private static HttpRequest searchUsersRequest;
+
 	private static HttpRequest lookupUsersRequest;
+
 	private static HttpRequest lookupUsersRequest2;
 
 	@Autowired
@@ -84,16 +83,12 @@ public abstract class TwitterUsersFunctionTests {
 	Function<Message<?>, Message<byte[]>> twitterUsersFunction;
 
 	public static HttpRequest setExpectation(HttpRequest request, String responseUri) {
-		mockClient
-				.when(request, exactly(1))
-				.respond(response()
-						.withStatusCode(200)
-						.withHeaders(
-								new Header("Content-Type", "application/json; charset=utf-8"),
-								new Header("Cache-Control", "public, max-age=86400"))
-						.withBody(TwitterTestUtils.asString(responseUri))
-						.withDelay(TimeUnit.SECONDS, 1)
-				);
+		mockClient.when(request, exactly(1))
+			.respond(response().withStatusCode(200)
+				.withHeaders(new Header("Content-Type", "application/json; charset=utf-8"),
+						new Header("Cache-Control", "public, max-age=86400"))
+				.withBody(TwitterTestUtils.asString(responseUri))
+				.withDelay(TimeUnit.SECONDS, 1));
 		return request;
 	}
 
@@ -102,25 +97,20 @@ public abstract class TwitterUsersFunctionTests {
 		mockServer = ClientAndServer.startClientAndServer(MOCK_SERVER_PORT);
 		mockClient = new MockServerClient(MOCK_SERVER_IP, MOCK_SERVER_PORT);
 
-		searchUsersRequest = setExpectation(request()
-						.withMethod("GET")
-						.withPath("/users/search.json")
-						.withQueryStringParameter("q", "tzolov")
-						.withQueryStringParameter("page", "3"),
-				"classpath:/response/search_users.json");
+		searchUsersRequest = setExpectation(request().withMethod("GET")
+			.withPath("/users/search.json")
+			.withQueryStringParameter("q", "tzolov")
+			.withQueryStringParameter("page", "3"), "classpath:/response/search_users.json");
 
-		lookupUsersRequest = setExpectation(request()
-						.withMethod("GET")
-						.withPath("/users/lookup.json")
-						.withQueryStringParameter("user_id",
-								"710705860343963648,326896547,267603736,781497571629989888,838754923"),
+		lookupUsersRequest = setExpectation(request().withMethod("GET")
+			.withPath("/users/lookup.json")
+			.withQueryStringParameter("user_id", "710705860343963648,326896547,267603736,781497571629989888,838754923"),
 				"classpath:/response/lookup_users_id.json");
 
-		lookupUsersRequest2 = setExpectation(request()
-						.withMethod("GET")
-						.withPath("/users/lookup.json")
-						.withQueryStringParameter("screen_name",
-								"TzolovMarto,Rabotnik57,antzolov,peyo_tzolov,ivantzolov"),
+		lookupUsersRequest2 = setExpectation(
+				request().withMethod("GET")
+					.withPath("/users/lookup.json")
+					.withQueryStringParameter("screen_name", "TzolovMarto,Rabotnik57,antzolov,peyo_tzolov,ivantzolov"),
 				"classpath:/response/lookup_users_id.json");
 	}
 
@@ -129,10 +119,7 @@ public abstract class TwitterUsersFunctionTests {
 		mockServer.stop();
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.users.type=search",
-			"twitter.users.search.query=payload"
-	})
+	@TestPropertySource(properties = { "twitter.users.type=search", "twitter.users.search.query=payload" })
 	public static class TwitterSearchUsersTests extends TwitterUsersFunctionTests {
 
 		@Test
@@ -143,12 +130,11 @@ public abstract class TwitterUsersFunctionTests {
 			List list = mapper.readValue(new String((byte[]) received.getPayload()), List.class);
 			assertThat(list).hasSize(20);
 		}
+
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.users.type=lookup",
-			"twitter.users.lookup.userId='710705860343963648,326896547,267603736,781497571629989888,838754923'"
-	})
+	@TestPropertySource(properties = { "twitter.users.type=lookup",
+			"twitter.users.lookup.userId='710705860343963648,326896547,267603736,781497571629989888,838754923'" })
 	public static class TwitterLookupUserIdLiteralTests extends TwitterUsersFunctionTests {
 
 		@Test
@@ -161,12 +147,11 @@ public abstract class TwitterUsersFunctionTests {
 			List list = mapper.readValue(new String((byte[]) received.getPayload()), List.class);
 			assertThat(list).hasSize(5);
 		}
+
 	}
 
-	@TestPropertySource(properties = {
-			"twitter.users.type=lookup",
-			"twitter.users.lookup.screenName=#jsonPath(payload,'$[*].code')"
-	})
+	@TestPropertySource(properties = { "twitter.users.type=lookup",
+			"twitter.users.lookup.screenName=#jsonPath(payload,'$[*].code')" })
 	public static class TwitterLookupScreenNamePayloadTests extends TwitterUsersFunctionTests {
 
 		@Test
@@ -182,23 +167,26 @@ public abstract class TwitterUsersFunctionTests {
 			List list = mapper.readValue(new String((byte[]) received.getPayload()), List.class);
 			assertThat(list).hasSize(5);
 		}
+
 	}
 
 	@SpringBootConfiguration
 	@EnableAutoConfiguration
 	@Import(TwitterUsersFunctionConfiguration.class)
 	static class TwitterUsersFunctionTestApplication {
+
 		@Bean
 		@Primary
 		public twitter4j.conf.Configuration twitterConfiguration2(TwitterConnectionProperties properties,
 				Function<TwitterConnectionProperties, ConfigurationBuilder> toConfigurationBuilder) {
 
-			Function<TwitterConnectionProperties, ConfigurationBuilder> mockedConfiguration =
-					toConfigurationBuilder.andThen(
-							new TwitterTestUtils().mockTwitterUrls(
-									String.format("http://%s:%s", MOCK_SERVER_IP, MOCK_SERVER_PORT)));
+			Function<TwitterConnectionProperties, ConfigurationBuilder> mockedConfiguration = toConfigurationBuilder
+				.andThen(new TwitterTestUtils()
+					.mockTwitterUrls(String.format("http://%s:%s", MOCK_SERVER_IP, MOCK_SERVER_PORT)));
 
 			return mockedConfiguration.apply(properties).build();
 		}
+
 	}
+
 }