semantic segmentation processor

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

@@ -16,6 +16,13 @@
 
 package org.springframework.cloud.fn.semantic.segmentation;
 
+import java.io.InputStream;
+import java.util.Arrays;
+
+import com.fasterxml.jackson.databind.ObjectMapper;
+
+import org.springframework.core.io.DefaultResourceLoader;
+
 /**
  *
  * Visualizes the segmentation results via specified color map.
@@ -303,4 +310,54 @@ public final class SegmentationColorMap {
 			System.arraycopy(_CITYMAP_COLORMAP[i], 0, CITYMAP_COLORMAP[i], 0, _CITYMAP_COLORMAP[i].length);
 		}
 	}
+
+	public static int[][] loadColorMap(String resourceUri) {
+		try {
+			InputStream colorMapIs = new DefaultResourceLoader().getResource(resourceUri).getInputStream();
+			ColorMap colorMap = new ObjectMapper().readValue(colorMapIs, ColorMap.class);
+			return colorMap.getColormap();
+		}
+		catch (Exception exception) {
+			throw new RuntimeException(exception);
+		}
+	}
+
+	public static class ColorMap {
+		private String name;
+		private String info;
+		private int[][] colormap;
+
+		public String getName() {
+			return name;
+		}
+
+		public void setName(String name) {
+			this.name = name;
+		}
+
+		public String getInfo() {
+			return info;
+		}
+
+		public void setInfo(String info) {
+			this.info = info;
+		}
+
+		public int[][] getColormap() {
+			return colormap;
+		}
+
+		public void setColormap(int[][] colormap) {
+			this.colormap = colormap;
+		}
+
+		@Override
+		public String toString() {
+			return "ColorMap{" +
+					"name='" + name + '\'' +
+					"info='" + info + '\'' +
+					", colormap=" + Arrays.deepToString(colormap) +
+					'}';
+		}
+	}
 }

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

@@ -25,6 +25,7 @@ import java.util.Map;
 
 import javax.imageio.ImageIO;
 
+import com.fasterxml.jackson.databind.ObjectMapper;
 import org.tensorflow.Operand;
 import org.tensorflow.Tensor;
 import org.tensorflow.op.Ops;
@@ -219,33 +220,31 @@ public class SemanticSegmentation implements AutoCloseable {
 
 	public static void main(String[] args) throws IOException {
 
-		//String inputImageUri = "file:/Users/ctzolov/Dev/projects/mindmodel/mind-model-services/semantic-segmentation/src/test/resources/images/VikiMaxiAdi.jpg";
-		String outputBlendedImagePath = "./semantic-segmentation/target/blendedImage.png";
-		String outputMaskImagePath = "./semantic-segmentation/target/maskImage.png";
-
-
 		try (SemanticSegmentation segmentationService = new SemanticSegmentation(
 				"http://download.tensorflow.org/models/deeplabv3_mnv2_cityscapes_train_2018_02_05.tar.gz#frozen_inference_graph.pb",
-				SegmentationColorMap.CITYMAP_COLORMAP, 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
 			long[][] maskPixels = segmentationService.maskPixels(inputImage);
 
+			String json = new ObjectMapper().writeValueAsString(maskPixels);
+
 			// 2. Alpha Blending
 			byte[] blended = segmentationService.blendMask(inputImage);
-			ImageIO.write(ImageIO.read(new ByteArrayInputStream(blended)), "png", new File(outputBlendedImagePath));
+			ImageIO.write(ImageIO.read(new ByteArrayInputStream(blended)), "png",
+					new File("./functions/function/semantic-segmentation-function/target/blendedImage.png"));
 
 			// 3. Mask Image
 			byte[] maskImage = segmentationService.maskImage(inputImage);
-			ImageIO.write(ImageIO.read(new ByteArrayInputStream(maskImage)), "png", new File(outputMaskImagePath));
+			ImageIO.write(ImageIO.read(new ByteArrayInputStream(maskImage)), "png",
+					new File("./functions/function/semantic-segmentation-function/target/maskImage.png"));
 		}
 
-
 		try (SemanticSegmentation segmentationService = new SemanticSegmentation(
 				"http://download.tensorflow.org/models/deeplabv3_xception_ade20k_train_2018_05_29.tar.gz#frozen_inference_graph.pb",
-				SegmentationColorMap.ADE20K_COLORMAP, null, 0.45f)
+				SegmentationColorMap.loadColorMap("classpath:/colormap/ade20k_colormap.json"), null, 0.45f)
 		) {
 			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/interior.jpg");
 
@@ -255,17 +254,17 @@ public class SemanticSegmentation implements AutoCloseable {
 			// 2. Alpha Blending
 			byte[] blended = segmentationService.blendMask(inputImage);
 			ImageIO.write(ImageIO.read(new ByteArrayInputStream(blended)), "png",
-					new File("./semantic-segmentation/target/inventory-blendedImage.png"));
+					new File("./functions/function/semantic-segmentation-function/target/inventory-blendedImage.png"));
 
 			// 3. Mask Image
 			byte[] maskImage = segmentationService.maskImage(inputImage);
 			ImageIO.write(ImageIO.read(new ByteArrayInputStream(maskImage)), "png",
-					new File("./semantic-segmentation/target/inventory-MaskImage.png"));
+					new File("./functions/function/semantic-segmentation-function/target/inventory-MaskImage.png"));
 		}
 
 		try (SemanticSegmentation segmentationService = new SemanticSegmentation(
 				"http://download.tensorflow.org/models/deeplabv3_mnv2_pascal_trainval_2018_01_29.tar.gz#frozen_inference_graph.pb",
-				SegmentationColorMap.BLACK_WHITE_COLORMAP, null, 0.45f)
+				SegmentationColorMap.loadColorMap("classpath:/colormap/black_white_colormap.json"), null, 0.45f)
 		) {
 			byte[] inputImage = GraphicsUtils.loadAsByteArray("classpath:/images/VikiMaxiAdi.jpg");
 
@@ -275,12 +274,12 @@ public class SemanticSegmentation implements AutoCloseable {
 			// 2. Alpha Blending
 			byte[] blended = segmentationService.blendMask(inputImage);
 			ImageIO.write(ImageIO.read(new ByteArrayInputStream(blended)), "png",
-					new File("./semantic-segmentation/target/pascal-blendedImage.png"));
+					new File("./functions/function/semantic-segmentation-function/target/pascal-blendedImage.png"));
 
 			// 3. Mask Image
 			byte[] maskImage = segmentationService.maskImage(inputImage);
 			ImageIO.write(ImageIO.read(new ByteArrayInputStream(maskImage)), "png",
-					new File("./semantic-segmentation/target/pascal-MaskImage.png"));
+					new File("./functions/function/semantic-segmentation-function/target/pascal-MaskImage.png"));
 		}
 
 	}

function/semantic-segmentation-function/src/main/resources/colormap/ade20k_colormap.json

@@ -0,0 +1,156 @@
+{
+    "name" : "ade20k",
+    "info" : "ADE20K (http://groups.csail.mit.edu/vision/datasets/ADE20K/)",
+    "colormap" :[
+			[ 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 ]]
+}

function/semantic-segmentation-function/src/main/resources/colormap/black_white_colormap.json

@@ -0,0 +1,8 @@
+{
+    "name" : "black_white",
+    "info" : "Black and white color map",
+    "colormap" :[
+            [ 0, 0, 0 ],
+            [ 127, 127, 127 ],
+            [ 255, 255, 255 ]]
+}

function/semantic-segmentation-function/src/main/resources/colormap/citymap_colormap.json

@@ -0,0 +1,24 @@
+{
+ "name" : "citymap",
+ "info" : "Cityscapes dataset (https://www.cityscapes-dataset.com).",
+ "colormap" :[
+        [ 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 ]]
+}

function/semantic-segmentation-function/src/main/resources/colormap/mapillary_colormap.json

@@ -0,0 +1,71 @@
+{
+    "name" : "mapillary",
+    "info" : "Mapillary Vistas (https://research.mapillary.com).",
+    "colormap" :[
+			[ 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 ]]
+}