andrewfayres commented on a change in pull request #13162: [MXNET-1198] MXNet Java API URL: https://github.com/apache/incubator-mxnet/pull/13162#discussion_r233640919
########## File path: scala-package/examples/src/main/java/org/apache/mxnetexamples/javaapi/infer/objectdetector/SSDClassifierExample.java ########## @@ -0,0 +1,199 @@ +/* + * 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.javaapi.infer.objectdetector; + +import org.apache.mxnet.infer.javaapi.ObjectDetectorOutput; +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; + +// scalastyle:off +import java.awt.image.BufferedImage; +// scalastyle:on + +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; + +import java.io.File; + +public class SSDClassifierExample { + @Option(name = "--model-path-prefix", usage = "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<ObjectDetectorOutput>> + 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 objDet = new ObjectDetector(modelPathPrefix, inputDescriptors, context, 0); + return objDet.imageObjectDetect(img, 3); + } + + static List<List<List<ObjectDetectorOutput>>> + 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 objDet = new ObjectDetector(modelPathPrefix, inputDescriptors, context, 0); + + // Loading batch of images from the directory path + List<List<String>> batchFiles = generateBatches(inputImageDir, 20); + List<List<List<ObjectDetectorOutput>>> outputList + = new ArrayList<List<List<ObjectDetectorOutput>>>(); + + for (List<String> batchFile : batchFiles) { + List<BufferedImage> imgList = ObjectDetector.loadInputBatch(batchFile); + // Running inference on batch of images loaded in previous step + List<List<ObjectDetectorOutput>> tmp + = objDet.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<ObjectDetectorOutput>> output + = runObjectDetectionSingle(mdprefixDir, imgPath, context); + + for (List<ObjectDetectorOutput> ele : output) { + for (ObjectDetectorOutput i : ele) { + outputStr += "Class: " + i.getClassName() + "\n"; + outputStr += "Probabilties: " + i.getProbability() + "\n"; + + List<Float> coord = Arrays.asList(i.getXMin() * width, + i.getXMax() * height, i.getYMin() * width, i.getYMax() * 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<ObjectDetectorOutput>>> outputList = + runObjectDetectionBatch(mdprefixDir, imgDir, context); + + outputStr = "\n"; + int index = 0; + for (List<List<ObjectDetectorOutput>> i: outputList) { + for (List<ObjectDetectorOutput> j : i) { + outputStr += "*** Image " + (index + 1) + "***" + "\n"; + for (ObjectDetectorOutput k : j) { + outputStr += "Class: " + k.getClassName() + "\n"; + outputStr += "Probabilties: " + k.getProbability() + "\n"; + List<Float> coord = Arrays.asList(k.getXMin() * width, + k.getXMax() * height, k.getYMin() * width, k.getYMax() * 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) { + Boolean exist = true; + for (String item : arr) { + exist = new File(item).exists() && exist; + if (!exist) { + logger.error("Cannot find: " + item); Review comment: This is also wrong in the existing scala example so fixing it there too. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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