Java tutorial
/* * 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 com.jeremydyer.nifi; import org.apache.commons.io.IOUtils; import org.apache.nifi.components.PropertyDescriptor; import org.apache.nifi.flowfile.FlowFile; import org.apache.nifi.processor.*; import org.apache.nifi.annotation.behavior.ReadsAttribute; import org.apache.nifi.annotation.behavior.ReadsAttributes; import org.apache.nifi.annotation.behavior.WritesAttribute; import org.apache.nifi.annotation.behavior.WritesAttributes; import org.apache.nifi.annotation.documentation.CapabilityDescription; import org.apache.nifi.annotation.documentation.SeeAlso; import org.apache.nifi.annotation.documentation.Tags; import org.apache.nifi.processor.exception.ProcessException; import org.apache.nifi.processor.io.InputStreamCallback; import org.apache.nifi.processor.io.OutputStreamCallback; import org.apache.nifi.processor.util.StandardValidators; import org.json.JSONArray; import org.json.JSONObject; import org.opencv.core.*; import org.opencv.imgcodecs.Imgcodecs; import org.opencv.imgproc.Imgproc; import org.opencv.objdetect.CascadeClassifier; import java.io.IOException; import java.io.InputStream; import java.io.OutputStream; import java.util.*; import java.util.concurrent.atomic.AtomicReference; @Tags({ "opencv, object detection" }) @CapabilityDescription("Detects objects from the input images based on the configured OpenCV CascadeClassifier loaded." + "This Processor REQUIRES the OpenCV native Java bindings be installed on the NiFi instance") @SeeAlso({}) @ReadsAttributes({ @ReadsAttribute(attribute = "", description = "") }) @WritesAttributes({ @WritesAttribute(attribute = "object.detection.name", description = ""), @WritesAttribute(attribute = "object.detection.id", description = "") }) public class ObjectDetectionProcessor extends AbstractProcessor { public static final PropertyDescriptor DETECTION_DEFINITION_JSON = new PropertyDescriptor.Builder() .name("Object Detection Definition").description("JSON detection definition").required(true) .addValidator(StandardValidators.NON_EMPTY_VALIDATOR).build(); public static final Relationship REL_ORIGINAL = new Relationship.Builder().name("original") .description("original input").build(); public static final Relationship REL_OBJECT_DETECTED = new Relationship.Builder().name("object_detected") .description("object detected in image").build(); public static final Relationship REL_NO_OBJECT_DETECTED = new Relationship.Builder().name("no_object_detected") .description("no desired object detected in the image").build(); public static final Relationship REL_FAILURE = new Relationship.Builder().name("failure") .description("failure during processing").build(); private List<PropertyDescriptor> descriptors; private Set<Relationship> relationships; @Override protected void init(final ProcessorInitializationContext context) { final List<PropertyDescriptor> descriptors = new ArrayList<PropertyDescriptor>(); descriptors.add(DETECTION_DEFINITION_JSON); this.descriptors = Collections.unmodifiableList(descriptors); final Set<Relationship> relationships = new HashSet<Relationship>(); relationships.add(REL_ORIGINAL); relationships.add(REL_OBJECT_DETECTED); relationships.add(REL_NO_OBJECT_DETECTED); relationships.add(REL_FAILURE); this.relationships = Collections.unmodifiableSet(relationships); //Load the OpenCV Native Library System.loadLibrary(Core.NATIVE_LIBRARY_NAME); } @Override public Set<Relationship> getRelationships() { return this.relationships; } @Override public final List<PropertyDescriptor> getSupportedPropertyDescriptors() { return descriptors; } @Override public void onTrigger(final ProcessContext context, final ProcessSession session) throws ProcessException { final FlowFile original = session.get(); if (original == null) { return; } final JSONObject JSON = new JSONObject(context.getProperty(DETECTION_DEFINITION_JSON).getValue()); session.read(original, new InputStreamCallback() { @Override public void process(InputStream inputStream) throws IOException { try { byte[] imgData = IOUtils.toByteArray(inputStream); Mat image = Imgcodecs.imdecode(new MatOfByte(imgData), Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE); //Loops through all of the detection definitions JSONArray dds = JSON.getJSONArray("DetectionDefinition"); for (int i = 0; i < dds.length(); i++) { JSONObject dd = dds.getJSONObject(i); detectObjects(session, original, dd, image); } } catch (Exception ex) { getLogger().error(ex.getMessage()); ex.printStackTrace(); } } }); session.transfer(original, REL_ORIGINAL); } final public Mat detectObjects(final ProcessSession session, FlowFile original, final JSONObject dd, final Mat image) { CascadeClassifier objectDetector = new CascadeClassifier(dd.getString("opencv_xml_cascade_path")); MatOfRect objectDetections = new MatOfRect(); objectDetector.detectMultiScale(image, objectDetections); //getLogger().error("Detected " + objectDetections.toArray().length + " " + dd.getString("name") + " objects in the input flowfile"); final AtomicReference<Mat> croppedImageReference = new AtomicReference<>(); int counter = 0; for (int i = 0; i < objectDetections.toArray().length; i++) { final Rect rect = objectDetections.toArray()[i]; FlowFile detection = session.write(session.create(original), new OutputStreamCallback() { @Override public void process(OutputStream outputStream) throws IOException { Mat croppedImage = null; //Should the image be cropped? If so there is no need to draw bounds because that would be the same as the cropping if (dd.getBoolean("crop")) { Rect rectCrop = new Rect(rect.x, rect.y, rect.width, rect.height); croppedImage = new Mat(image, rectCrop); MatOfByte updatedImage = new MatOfByte(); Imgcodecs.imencode(".jpg", croppedImage, updatedImage); croppedImageReference.set(croppedImage); outputStream.write(updatedImage.toArray()); } else { //Should the image have a border drawn around it? if (dd.getBoolean("drawBounds")) { Mat imageWithBorder = image.clone(); Imgproc.rectangle(imageWithBorder, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(255, 255, 255)); MatOfByte updatedImage = new MatOfByte(); Imgcodecs.imencode(".jpg", imageWithBorder, updatedImage); outputStream.write(updatedImage.toArray()); } else { MatOfByte updatedImage = new MatOfByte(); Imgcodecs.imencode(".jpg", image, updatedImage); outputStream.write(updatedImage.toArray()); } } } }); Map<String, String> atts = new HashMap<>(); atts.put("object.detection.name", dd.getString("name")); atts.put("object.detection.id", new Long(System.currentTimeMillis() + counter).toString()); counter++; detection = session.putAllAttributes(detection, atts); session.transfer(detection, REL_OBJECT_DETECTED); } Mat childResponse = null; if (croppedImageReference.get() != null) { childResponse = croppedImageReference.get(); } else { childResponse = image; } if (dd.has("children")) { JSONArray children = dd.getJSONArray("children"); if (children != null) { for (int i = 0; i < children.length(); i++) { JSONObject ddd = children.getJSONObject(i); childResponse = detectObjects(session, original, ddd, childResponse); } } } return childResponse; } }