AWS Code Sample

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# Copyright 2010-2019, Inc. or its affiliates. All Rights Reserved. # # This file is licensed under the Apache License, Version 2.0 (the "License"). # You may not use this file except in compliance with the License. A copy of the # License is located at # # # # This file 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. import boto3 from PIL import Image # To install package: pip install Pillow def ShowBoundingBoxPositions(imageHeight, imageWidth, box, rotation): """Calculate the bounding box surrounding an identified face. The calculation takes the image rotation into account. :param imageHeight: Height of entire image in pixels :param imageWidth: Width of entire image in pixels :param box: Dictionary containing bounding box data points :param rotation: Image orientation determined by Rekognition """ # Calculate left and top points taking image rotation into account left = 0 top = 0 if rotation == 'ROTATE_0': left = imageWidth * box['Left'] top = imageHeight * box['Top'] if rotation == 'ROTATE_90': left = imageHeight * (1 - (box['Top'] + box['Height'])) top = imageWidth * box['Left'] if rotation == 'ROTATE_180': left = imageWidth - (imageWidth * (box['Left'] + box['Width'])) top = imageHeight * (1 - (box['Top'] + box['Height'])) if rotation == 'ROTATE_270': left = imageHeight * box['Top'] top = imageWidth * (1- box['Left'] - box['Width'] ) print('Bounding box of face:') print(f' Left: {round(left)}, Top: {round(top)}, ' f'Width: {round(imageWidth * box["Width"])}, ' f'Height: {round(imageHeight * box["Height"])}') if __name__ == "__main__": """Exercise the Rekognition recognize_celebrities() method and ShowBoundingBoxPositions()""" # Set the photo variable to the image filename to process photo = 'CELEBRITY_PHOTO.JPG' # Extract the image width, height, and EXIF data try: with as image: width, height = image.size exif = None if 'exif' in exif =['exif'] except IOError as e: print(e) exit(1) print(f'File name: {photo}') print(f'Image width, height: {width}, {height}') # Read the entire image into memory try: with open(photo, 'rb') as f: image_binary = except IOError as e: print(e) exit(2) # Detect the celebrities in the photo client = boto3.client('rekognition', region_name='us-east-1') response = client.recognize_celebrities(Image={'Bytes': image_binary}) if 'OrientationCorrection' in response: print(f'Image orientation: {response["OrientationCorrection"]}') else: print('No estimated orientation. Check the image\'s Exif metadata.') # List the identified celebrities print('Detected celebrities...') celebrities = response['CelebrityFaces'] if not celebrities: print('No celebrities detected') else: for celebrity in celebrities: print(f'\nName: {celebrity["Name"]}') print(f'Match confidence: {celebrity["MatchConfidence"]}') # List the bounding box that surrounds the face if 'OrientationCorrection' in response: ShowBoundingBoxPositions(height, width, celebrity['Face']['BoundingBox'], response['OrientationCorrection'])

Sample Details

Service: rekognition

Last tested: 2019-04-09

Author: AWS

Type: snippet

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