[GitHub] lanking520 commented on a change in pull request #12830: Java Inference api and SSD example

[GitBox <gi...@apache.org>]

lanking520 commented on a change in pull request #12830: Java Inference api and SSD example
URL: https://github.com/apache/incubator-mxnet/pull/12830#discussion_r225358727
 
 

 ##########
 File path: scala-package/examples/src/main/java/org/apache/mxnetexamples/infer/javapi/objectdetector/SSDClassifierExample.java
 ##########
 @@ -0,0 +1,190 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.mxnetexamples.infer.javapi.objectdetector;
+
+import org.kohsuke.args4j.CmdLineParser;
+import org.kohsuke.args4j.Option;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import org.apache.mxnet.javaapi.*;
+import org.apache.mxnet.infer.javaapi.ObjectDetector;
+
+import java.awt.image.BufferedImage;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import javafx.util.Pair;
+
+import java.io.File;
+
+public class SSDClassifierExample {
+	@Option(name = "--model-path-prefix", usage = "the input model directory and prefix of the model")
+	private String modelPathPrefix = "/model/ssd_resnet50_512";
+	@Option(name = "--input-image", usage = "the input image")
+	private String inputImagePath = "/images/dog.jpg";
+	@Option(name = "--input-dir", usage = "the input batch of images directory")
+	private String inputImageDir = "/images/";
+	
+	final static Logger logger = LoggerFactory.getLogger(SSDClassifierExample.class);
+	
+	static List<List<Pair<String, List<Float>>>> runObjectDetectionSingle(String modelPathPrefix, String inputImagePath, List<Context> context) {
+		Shape inputShape = new Shape(new int[] {1, 3, 512, 512});
+		List<DataDesc> inputDescriptors = new ArrayList<DataDesc>();
+		inputDescriptors.add(new DataDesc("data", inputShape, DType.Float32(), "NCHW"));
+		BufferedImage img = ObjectDetector.loadImageFromFile(inputImagePath);
+		ObjectDetector objDetector = new ObjectDetector(modelPathPrefix, inputDescriptors, context, 0);
+		return objDetector.imageObjectDetect(img, 3);
+	}
+	
+	static List<List<List<Pair<String, List<Float>>>>> runObjectDetectionBatch(String modelPathPrefix, String inputImageDir, List<Context> context) {
+		Shape inputShape = new Shape(new int[]{1, 3, 512, 512});
+		List<DataDesc> inputDescriptors = new ArrayList<DataDesc>();
+		inputDescriptors.add(new DataDesc("data", inputShape, DType.Float32(), "NCHW"));
+		ObjectDetector objDetector = new ObjectDetector(modelPathPrefix, inputDescriptors, context, 0);
+		
+		// Loading batch of images from the directory path
+		List<List<String>> batchFiles = generateBatches(inputImageDir, 20);
+		List<List<List<Pair<String, List<Float>>>>> outputList = new ArrayList<List<List<Pair<String, List<Float>>>>>();
+		
+		for (List<String> batchFile : batchFiles) {
+			List<BufferedImage> imgList = ObjectDetector.loadInputBatch(batchFile);
+			// Running inference on batch of images loaded in previous step
+			List<List<Pair<String, List<Float>>>> tmp = objDetector.imageBatchObjectDetect(imgList, 5);
+			outputList.add(tmp);
+		}
+		return outputList;
+	}
+	
+	static List<List<String>> generateBatches(String inputImageDirPath, int batchSize) {
+		File dir = new File(inputImageDirPath);
+
+		List<List<String>> output = new ArrayList<List<String>>();
+		List<String> batch = new ArrayList<String>();
+		for (File imgFile : dir.listFiles()) {
+			batch.add(imgFile.getPath());
+			if (batch.size() == batchSize) {
+				output.add(batch);
+				batch = new ArrayList<String>();
+			}
+		}
+		if (batch.size() > 0) {
+			output.add(batch);
+		}
+		return output;
+	}
+	
+	public static void main(String[] args) {
+		SSDClassifierExample inst = new SSDClassifierExample();
+		CmdLineParser parser  = new CmdLineParser(inst);
+		try {
+			parser.parseArgument(args);
+		} catch (Exception e) {
+			logger.error(e.getMessage(), e);
+			parser.printUsage(System.err);
+			System.exit(1);
+		}
+		
+		String mdprefixDir = inst.modelPathPrefix;
+		String imgPath = inst.inputImagePath;
+		String imgDir = inst.inputImageDir;
+		
+		if (!checkExist(Arrays.asList(mdprefixDir + "-symbol.json", imgDir, imgPath))) {
+			logger.error("Model or input image path does not exist");
+			System.exit(1);
+		}
+		
+		List<Context> context = new ArrayList<Context>();
+		if (System.getenv().containsKey("SCALA_TEST_ON_GPU") &&
+				Integer.valueOf(System.getenv("SCALA_TEST_ON_GPU")) == 1) {
+			context.add(Context.gpu());
+		} else {
+			context.add(Context.cpu());
+		}
+		
+		try {
+			Shape inputShape = new Shape(new int[] {1, 3, 512, 512});
+			Shape outputShape = new Shape(new int[] {1, 6132, 6});
+			
+			
+			int width = inputShape.get(2);
+			int height = inputShape.get(3);
+			String outputStr = "\n";
+			
+			List<List<Pair<String, List<Float>>>> output = runObjectDetectionSingle(mdprefixDir, imgPath, context);
+			
+			for (List<Pair<String, List<Float>>> ele : output) {
+				for (Pair<String, List<Float>> i : ele) {
+					outputStr += "Class: " + i.getKey() + "\n";
+					List<Float> arr = i.getValue();
+					outputStr += "Probabilties: " + arr.get(0) + "\n";
+					
+					List<Float> coord = Arrays.asList(arr.get(1) * width, arr.get(2) * height, arr.get(3) * width, arr.get(4) * height);
+					StringBuilder sb = new StringBuilder();
+					for (float c: coord) {
+						sb.append(", ").append(c);
+					}
+					outputStr += "Coord:" + sb.substring(2)+ "\n";
+				}
+			}
+			logger.info(outputStr);
+			
+			List<List<List<Pair<String, List<Float>>>>> outputList = runObjectDetectionBatch(mdprefixDir, imgDir, context);
+			
+			outputStr = "\n";
+			int index = 0;
+			for (List<List<Pair<String, List<Float>>>> i: outputList) {
+				for (List<Pair<String, List<Float>>> j : i) {
+					outputStr += "*** Image " + (index + 1) + "***" + "\n";
+					for (Pair<String, List<Float>> k : j) {
+						outputStr += "Class: " + k.getKey() + "\n";
+						List<Float> arr = k.getValue();
+						outputStr += "Probabilties: " + arr.get(0) + "\n";
+						List<Float> coord = Arrays.asList(arr.get(1) * width, arr.get(2) * height, arr.get(3) * width, arr.get(4) * height);
+						
+						StringBuilder sb = new StringBuilder();
+						for (float c : coord) {
+							sb.append(", ").append(c);
+						}
+						outputStr += "Coord:" + sb.substring(2) + "\n";
+					}
+					index++;
+				}
+			}
+			logger.info(outputStr);
+			
+		} catch (Exception e) {
+			logger.error(e.getMessage(), e);
+			parser.printUsage(System.err);
+			System.exit(1);
+		}
+		System.exit(0);
+	}
+	
+	static Boolean checkExist(List<String> arr)  {
 
 Review comment:
   nitPick: checkFileExist

----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
 
For queries about this service, please contact Infrastructure at:
users@infra.apache.org


With regards,
Apache Git Services