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| # 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. | |
| """ | |
| Install opencv-python | |
| """ | |
| import numpy as np | |
| import cv2 | |
| import sys | |
| import codecs | |
| def describe(processor): | |
| processor.setDescription("Runs haar cascaade.") | |
| def onInitialize(processor): | |
| # is required, | |
| processor.addProperty("Path","Path to XML.","", True, False) | |
| class ContentExtract(object): | |
| def __init__(self): | |
| self.content = None | |
| def process(self, input_stream): | |
| self.content = input_stream.read() | |
| return len(self.content) | |
| def onTrigger(context, session): | |
| flow_file = session.get() | |
| if flow_file is not None: | |
| filename = context.getProperty("Path") | |
| face_cascade = cv2.CascadeClassifier(filename) | |
| imageextractor = ContentExtract() | |
| session.read(flow_file,imageextractor) | |
| nparr = np.fromstring(imageextractor.content, np.uint8) | |
| img_np = cv2.imdecode(nparr, cv2.IMREAD_COLOR) | |
| gray = cv2.cvtColor(img_np, cv2.COLOR_BGR2GRAY) | |
| # Detects faces of different sizes in the input image | |
| faces = face_cascade.detectMultiScale(gray, 1.3, 5) | |
| if sys.getsizeof(faces) > 0: | |
| flow_file.addAttribute("faces",str(sys.getsizeof(faces))) | |
| session.transfer(flow_file, REL_SUCCESS) |
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